for Journals by Title or ISSN
for Articles by Keywords
help
  Subjects -> COMPUTER SCIENCE (Total: 1994 journals)
    - ANIMATION AND SIMULATION (27 journals)
    - ARTIFICIAL INTELLIGENCE (75 journals)
    - AUTOMATION (40 journals)
    - COMPUTER ARCHITECTURE (9 journals)
    - COMPUTER ASSISTED INSTRUCTION (25 journals)
    - COMPUTER ENGINEERING (11 journals)
    - COMPUTER GAMES (16 journals)
    - COMPUTER GRAPHICS (32 journals)
    - COMPUTER PROGRAMMING (20 journals)
    - COMPUTER SCIENCE (1233 journals)
    - COMPUTER SECURITY (44 journals)
    - CYBERNETICS AND ROBOTICS (62 journals)
    - DATA BASE MANAGEMENT (15 journals)
    - DATA COMMUNICATIONS AND NETWORKS (75 journals)
    - DATA MINING (23 journals)
    - ELECTRONIC DATA PROCESSING (17 journals)
    - INFORMATION SYSTEMS (93 journals)
    - INTERNET (91 journals)
    - SOCIAL WEB (46 journals)
    - SOFTWARE (34 journals)
    - THEORY OF COMPUTING (6 journals)

COMPUTER SCIENCE (1233 journals)

The end of the list has been reached or no journals were found for your choice.
Journal Cover Control Engineering Practice
  [SJR: 1.245]   [H-I: 67]   [40 followers]  Follow
    
   Hybrid Journal Hybrid journal (It can contain Open Access articles)
   ISSN (Print) 0967-0661
   Published by Elsevier Homepage  [2817 journals]
  • Nonlinear model predictive control of functional electrical stimulation
    • Abstract: Publication date: Available online 26 April 2016
      Source:Control Engineering Practice
      Author(s): Nicholas Kirsch, Naji Alibeji, Nitin Sharma
      Minimizing the amount of electrical stimulation can potentially mitigate the adverse effects of muscle fatigue during functional electrical stimulation (FES) induced limb movements. A gradient projection-based model predictive controller is presented for optimal control of a knee extension elicited via FES. A control Lyapunov function was used as a terminal cost to ensure stability of the model predictive control. The controller validation results show that the algorithm can be implemented in real-time with a steady-state RMS error of less than 2°. The experiments also show that the controller follows step changes in desired angles and is robust to external disturbances.


      PubDate: 2016-04-28T14:13:04Z
       
  • Fractional robust PID control of a solar furnace
    • Abstract: Publication date: Available online 25 April 2016
      Source:Control Engineering Practice
      Author(s): M. Beschi, F. Padula, A. Visioli
      This paper deals with the fractional control of the temperature in solar furnace plants. As for all the concentrated solar plants, the solar furnace can be modeled as a nonlinear system, where the dynamics strongly depends on the operating temperature. However, to improve the effectiveness of this technology, the control system should guarantee an acceptable performance independently from the operating point. In order to overcome this problem, we propose to use the generalized isodamping technique, where we aim at achieving the invariance of the control loop phase margin with respect to the plant operating point through a properly designed fractional-order proportional-integral-derivative controller. A gain-scheduling algorithm is also introduced to cope with wide plant variations. Simulation and experimental results show the effectiveness of the proposed methodology.


      PubDate: 2016-04-28T14:13:04Z
       
  • A multiple model filtering approach to transmission line fault diagnosis
    • Abstract: Publication date: July 2016
      Source:Control Engineering Practice, Volume 52
      Author(s): Qiu Qin, N. Eva Wu
      This paper provides justification and implementation for a multiple model filtering approach to diagnosis of transmission line three-phase short to ground faults in the presence of protection misoperations. This approach utilizes the electric network dynamics and wide area measurements to provide diagnosis outcomes. A second focus of this paper is on the reduction of computational complexity of the diagnosis algorithm. This issue is addressed by a two-step heuristic. The first step designs subsystem models through measurement selection. The second step reduces the dynamic model order. The performance of the diagnosis algorithms are evaluated on a simulated WSCC 9-bus system.


      PubDate: 2016-04-28T14:13:04Z
       
  • Proportional-integral based fuzzy sliding mode control of the milling head
    • Abstract: Publication date: August 2016
      Source:Control Engineering Practice, Volume 53
      Author(s): Pengbing Zhao, Yaoyao Shi, Jin Huang
      A-axis (that is, the milling head) is an essential assembly in the five-axis CNC machine tools, positioning precision of which directly affects the machining accuracy and surface qualities of the processed parts. Considering the influence of nonlinear friction and uncertain cutting force on the control precision of the A-axis, a novel fuzzy sliding mode control (FSMC) based on the proportional-integral (PI) control is designed according to the parameters adaptation. Main idea of the control scheme is employing the fuzzy systems to approximate the unknown nonlinear functions and adopting the PI control to eliminate the input chattering. Simulation analyses and experimental results illustrate that the designed control strategy is robust to the uncertain load and the parameters perturbation.
      Graphical abstract image

      PubDate: 2016-04-28T14:13:04Z
       
  • System identification of the upper part of Murray River
    • Abstract: Publication date: July 2016
      Source:Control Engineering Practice, Volume 52
      Author(s): Hasan Arshad Nasir, Erik Weyer
      Data based modelling is an important tool for obtaining models of rivers. In this paper we consider several identification methods, namely Prediction Error Method, Maximum Likelihood, continuous time system identification, Refined Instrumental Variable method (used within the context of Data-Based Mechanistic modelling) and Subspace Identification Method, and apply them to real data from the Murray River in Australia. Both Multiple-Input Single-Output models where the output is the water level in a lake and Multiple-Input, Multiple-Output models where in addition a flow is also modelled, are considered. The models are compared in terms of their accuracy on validation data and on how easily the methods can incorporate prior knowledge.


      PubDate: 2016-04-28T14:13:04Z
       
  • Robust auto-landing of fixed-wing UAVs using neuro-adaptive design
    • Abstract: Publication date: Available online 23 April 2016
      Source:Control Engineering Practice
      Author(s): Pradeep R. Ambati, Radhakant Padhi
      An innovative neuro-adaptive design philosophy is presented in this paper embedding a Sobolev norm based Lyapunov function for directional learning of the unknown function, which is capable of learning both the unknown function in the system model and its Jacobian. This facilitates fast learning (model adaptation) without much of transient effects. The updated model is then used in the framework of dynamic inversion to design the guidance (outer) loop as well as the control (inner) loop. Using this philosophy a robust adaptive nonlinear guidance and control design is presented for robust automatic landing. The performance of the proposed approach is successfully verified through numerous simulation studies using the six degrees-of-freedom (six-DOF) nonlinear model of a prototype UAV. All possible disturbance effects that arise in practice, namely modeling inaccuracies, wind disturbances and ground effect, have been considered in the simulation studies.


      PubDate: 2016-04-24T02:11:46Z
       
  • New variable gain super-twisting sliding mode observer for sensorless
           vector control of nonsinusoidal back-EMF PMSM
    • Abstract: Publication date: July 2016
      Source:Control Engineering Practice, Volume 52
      Author(s): Cassio Luciano Baratieri, Humberto Pinheiro
      This paper presents a new discrete-time super-twisting sliding mode observer with variable gains for sensorless nonsinusoidal vector control of permanent magnet synchronous motors. This observer is adopted to estimate the back electromotive forces (back-EMF) that are required for the rotor speed estimation and for the nonsinusoidal vector control. In addition, their gains are time-varying to minimize the chattering. So, they are adjusted based on internal states of the super-twisting algorithm. The stability analysis is investigated from the Lyapunov theory for discrete-time systems. Finally, simulation and experimental results are presented to demonstrate the good performance and the effectiveness of the proposed observer.


      PubDate: 2016-04-24T02:11:46Z
       
  • Detecting broken rotor bars in induction motors with model-based support
           vector classifiers
    • Abstract: Publication date: July 2016
      Source:Control Engineering Practice, Volume 52
      Author(s): Mohammed Obaid Mustafa, Damiano Varagnolo, George Nikolakopoulos, Thomas Gustafsson
      We propose a methodology for testing the sanity of motors when both healthy and faulty data are unavailable. More precisely, we consider a model-based Support Vector Classification (SVC) method for the detection of broken bars in three phase asynchronous motors at full load conditions, using features based on the spectral analysis of the stator's steady state current (more specifically, the amplitude of the lift sideband harmonic and the amplitude at fundamental frequency). We diverge from the mainstream focus on using SVCs trained from measured data, and instead derive a classifier that is constructed entirely using theoretical considerations. The advantage of this approach is that it does not need training steps (an expensive, time consuming and often practically infeasible task), i.e., operators are not required to have both healthy and faulty data from a system for checking it. We describe what are the theoretical properties and fundamental limitations of using model based SVC methodologies, provide conditions under which using SVC tests is statistically optimal, and present some experimental results to prove the effectiveness of the suggested scheme.


      PubDate: 2016-04-20T02:11:39Z
       
  • A two-stage method for predicting and scheduling energy in an
           oxygen/nitrogen system of the steel industry
    • Abstract: Publication date: July 2016
      Source:Control Engineering Practice, Volume 52
      Author(s): Zhongyang Han, Jun Zhao, Wei Wang, Ying Liu
      As essential energy resources in steel industry, oxygen and nitrogen are massively utilized in many production procedures, such as iron-making by blast furnaces, steel-making by converters, etc. The trends of the energy generation/consumption flows along with the related scheduling works play a pivotal role on the energy management of steel enterprises. Aiming at an oxygen/nitrogen system of a steel plant in China, a two-stage predictive scheduling method is proposed in this study for resolving the optimal energy decision-making problem. Given the high cost of time consuming on the load change of air separation units (ASU) of the oxygen/nitrogen system, a Granular-Computing (GrC)-based prediction model is firstly established at the stage of prediction, which extends the predicting length to even a day based on data segment rather than generic point-wise mode. At the stage of optimal scheduling, a mixed-integer program model is constructed on the basis of constraining the number of adjustable energy units, which considers not only the actual capacity of the energy devices, but the practical energy conversion procedure as well. The experiments employing the real data coming from this plant also involve two stages, the long-term prediction and the energy scheduling, and the experimental results exhibit both satisfactory accuracy and practicability. Furthermore, the results of system application also indicate the effectiveness of the proposed method.


      PubDate: 2016-04-20T02:11:39Z
       
  • Structural analysis based sensors fault detection and isolation of
           cylindrical lithium-ion batteries in automotive applications
    • Abstract: Publication date: July 2016
      Source:Control Engineering Practice, Volume 52
      Author(s): Zhentong Liu, Qadeer Ahmed, Jiyu Zhang, Giorgio Rizzoni, Hongwen He
      The battery sensors fault diagnosis is of great importance to guarantee the battery performance, safety and life as the operations of battery management system (BMS) mainly depend on the embedded current, voltage and temperature sensor measurements. This paper presents a systematic model-based fault diagnosis scheme to detect and isolate the current, voltage and temperature sensor fault. The proposed scheme relies on the sequential residual generation using structural analysis theory and statistical inference residual evaluation. Structural analysis handles the pre-analysis of sensor fault detectability and isolability possibilities without the accurate knowledge of battery parameters, which is useful in the early design stages of diagnostic system. It also helps to find the analytical redundancy part of the battery model, from which subsets of equations are extracted and selected to construct diagnostic tests. With the help of state observes and other advanced techniques, these tests are ensured to be efficient by taking care of the inaccurate initial State-of-Charge (SoC) and derivation of variables. The residuals generated from diagnostic tests are further evaluated by a statistical inference method to make a reliable diagnostic decision. Finally, the proposed diagnostic scheme is experimentally validated and some experimental results are presented.


      PubDate: 2016-04-20T02:11:39Z
       
  • Editorial Board
    • Abstract: Publication date: June 2016
      Source:Control Engineering Practice, Volume 51




      PubDate: 2016-04-20T02:11:39Z
       
  • Contents list
    • Abstract: Publication date: June 2016
      Source:Control Engineering Practice, Volume 51




      PubDate: 2016-04-20T02:11:39Z
       
  • Nonlinear controller for bispectral index tracking: Robustness and on-line
           retuning
    • Abstract: Publication date: Available online 16 April 2016
      Source:Control Engineering Practice
      Author(s): Filipa N. Nogueira, Teresa Mendonça, Paula Rocha
      In this paper, the performance of a control law designed for the automatic administration of propofol and of remifentanil in order to track a desired level for the bispectral index (BIS), used as a measure of the depth of anesthesia, is analyzed under the presence of model parameters uncertainties. It is theoretically proved and illustrated by simulations that under these circumstances the controller has a very good performance as the BIS converges to a value contained in a neighborhood of the desired BIS level. A retuning strategy in order to improve the BIS tracking under the presence of uncertainties was also theoretically deduced. Simulations show that this strategy leads to BIS tracking improvement. The performance of the controller in clinical environment is illustrated by a clinical case.


      PubDate: 2016-04-20T02:11:39Z
       
  • An extremum-seeking control approach for constrained robotic motion tasks
    • Abstract: Publication date: July 2016
      Source:Control Engineering Practice, Volume 52
      Author(s): Vasiliki Koropouli, Azwirman Gusrialdi, Sandra Hirche, Dongheui Lee
      In this paper, we propose two adaptive control schemes for multiple-input systems for execution of robot end-effector movements in the presence of parametric system uncertainties. The design of these schemes is based on Model Reference Adaptive Control (MRAC) while the adaptation of the controller parameters is achieved by Extremum Seeking Control (ESC). The two control schemes, which are called Multiple-Input ESC–MRAC and Multiple-Input Adaptive-Dynamic-Inversion ESC–MRAC, are suitable for linear and nonlinear systems respectively. Lyapunov and averaging analysis shows that the proposed schemes achieve practical asymptotic reference state tracking. The proposed methods are evaluated in simulations and in a real-world robotic experiment.


      PubDate: 2016-04-20T02:11:39Z
       
  • Control-based load-balancing techniques: Analysis and performance
           evaluation via a randomized optimization approach
    • Abstract: Publication date: July 2016
      Source:Control Engineering Practice, Volume 52
      Author(s): Alessandro Vittorio Papadopoulos, Cristian Klein, Martina Maggio, Jonas Dürango, Manfred Dellkrantz, Francisco Hernández-Rodriguez, Erik Elmroth, Karl-Erik Årzén
      Cloud applications are often subject to unexpected events like flashcrowds and hardware failures. Users that expect a predictable behavior may abandon an unresponsive application when these events occur. Researchers and engineers addressed this problem on two separate fronts: first, they introduced replicas – copies of the application with the same functionality – for redundancy and scalability; second, they added a self-adaptive feature called brownout inside cloud applications to bound response times by modulating user experience. The presence of multiple replicas requires a dedicated component to direct incoming traffic: a load-balancer. Existing load-balancing strategies based on response times interfere with the response time controller developed for brownout-compliant applications. In fact, the brownout approach bounds response times using a control action. Hence, the response time, that was used to aid load-balancing decision, is not a good indicator of how well a replica is performing. To fix this issue, this paper reviews some proposal for brownout-aware load-balancing and provides a comprehensive experimental evaluation that compares them. To provide formal guarantees on the load-balancing performance, we use a randomized optimization approach and apply the scenario theory. We perform an extensive set of experiments on a real machine, extending the popular lighttpd web server and load-balancer, and obtaining a production-ready implementation. Experimental results show an improvement of the user experience over Shortest Queue First (SQF)—believed to be near-optimal in the non-adaptive case. The improved user experience is obtained preserving the response time predictability.


      PubDate: 2016-04-20T02:11:39Z
       
  • Vibration control of a Stirling engine with an electromagnetic active
           tuned mass damper
    • Abstract: Publication date: June 2016
      Source:Control Engineering Practice, Volume 51
      Author(s): Ali Hassan, Angel Torres-Perez, Stefan Kaczmarczyk, Phil Picton
      Active tuned mass damper (ATMD) systems have been used extensively to reduce vibrations in machines. The motivation of this study is attenuating the vibrations in a Free-Piston Stirling Engine/Linear Alternator (FPSE/LA) for a frequency band of 47–53Hz using an electromagnetic ATMD that employs a linear Voice Coil Motor (VCM) for periodic excitation rejection. To the authors’ knowledge, however several approaches to minimize vibrations in Stirling machines have been patented, the technique proposed in this research differs from other patented work by the simplicity of the proposed control law which aims to attenuate the engine vibrations at the fundamental operating frequency. The proposed control system features a zero-placement technique that utilizes both relative or absolute position and velocity feedback from the system response as well as a feedthrough measurement of the disturbance frequency that is used to determine the position gain online. The performance of the control system with the ATMD was evaluated both theoretically and experimentally. A test rig emulating the vibration behavior of the Stirling engine, featuring an electrodynamic shaker and an ATMD was developed and a model of the rig is presented and validated. A novel experimental procedure of identifying unknown stiffness and unknown dynamic mass of a spring–mass system is also presented. Similarly, another experimental procedure of determining the damping coefficient in the electromagnetic ATMD is shown. The implementation findings illustrate that the proposed active controller succeeds in broadening the attenuation band from 50±0.5Hz to between 45Hz and 55Hz.


      PubDate: 2016-04-08T11:57:21Z
       
  • Design and evaluation of a model predictive vehicle control algorithm for
           automated driving using a vehicle traffic simulator
    • Abstract: Publication date: June 2016
      Source:Control Engineering Practice, Volume 51
      Author(s): Jongsang Suh, Kyongsu Yi, Jiyeol Jung, Kyungjun Lee, Hyokjin Chong, Bongchul Ko
      This paper describes the design and evaluation of a model predictive control algorithm for automated driving on a motorway using a vehicle traffic simulator. For the development of a highly automated driving control algorithm, motion planning is necessary to satisfy driving condition in various road traffic situations. There are two key issues in motion planning of automated driving vehicles. One of the key issues is how to handle potentially dangerous situations that could occur in order to guarantee the safety of vehicles. The second key issue is how to guarantee the disturbance rejection of the controller under model uncertainties and external disturbances. To improve safety with respect to the future behaviors of subject vehicles, not the current states but rather the predicted behaviors of surrounding vehicles should be considered. The desired driving mode and a safe driving envelope are determined based on the probabilistic prediction of surrounding vehicles behaviors over a finite prediction horizon. To obtain the desired steering angle and longitudinal acceleration for maintaining the subject vehicle in the safe driving envelope during a finite prediction horizon, a motion planning controller is designed based on an model predictive control (MPC) approach. The developed control algorithm has been successfully implemented on a vehicle electronic control unit (ECU). The proposed control algorithm has been evaluated on a real-time vehicle traffic simulator. The throttle, brake, and steering control inputs and the controlled vehicle behavior have been compared to those of manual driving.


      PubDate: 2016-04-08T11:57:21Z
       
  • Guidance using bearing-only measurements with three beacons in the plane
    • Abstract: Publication date: June 2016
      Source:Control Engineering Practice, Volume 51
      Author(s): Minh Hoang Trinh, Gwi-Han Ko, Viet Hoang Pham, Kwang-Kyo Oh, Hyo-Sung Ahn
      This paper proposes a bearing-only measurement based guidance algorithm for a mobile agent to navigate in a two-dimensional plane. Based on the bearing vectors and the subtended angles related to three stationary beacons, the proposed algorithm allows the agent to reach its desired location. We show that the agent reaches its desired location globally asymptotically based on Lyapunov stability theory. Under some assumptions, the agent is also proved to reach the desired location exponentially based on Lyapunov's indirect method. Simulations and actual experimental tests on quadrotor system are also provided to verify the effectiveness of the proposed algorithm in outdoor environment.


      PubDate: 2016-04-08T11:57:21Z
       
  • CEP special issue on smart power system control
    • Abstract: Publication date: Available online 5 April 2016
      Source:Control Engineering Practice
      Author(s): István Erlich



      PubDate: 2016-04-08T11:57:21Z
       
  • Single screw extrusion control: A comprehensive review and directions for
           improvements
    • Abstract: Publication date: June 2016
      Source:Control Engineering Practice, Volume 51
      Author(s): Chamil Abeykoon
      Polymer extrusion is usually a complex process, particularly due to the coupled nature of process parameters, and hence highly prone to fluctuations. Although a number of different approaches have been attempted in research/industry over the last few decades for extrusion control, it is still experiencing some problems in achieving consistent product quality. Presently, most of the polymer processing extruders are equipped with PID controllers mainly for the control of the screw speed and barrel temperatures in their set limits. It seems that only both of these controllers are commonly used as the major aids of process control to achieve the required melt quality. Although, the quality of the melt output (i.e., a thermally homogeneous melt output which is constant in quantity and quality over the time) is the key variable in polymer extrusion, only a few control techniques are available which make control decisions by observing the actual melt flow quality. Therefore, the development of new control strategies which consider the actual melt quality, perhaps incorporating industrially popular nonlinear techniques such as artificial intelligence, should be highly valuable. In this work, a critical evaluation is made on the state-of-the-art of the previous control approaches in polymer extrusion in industry and research while identifying their limitations. Then, some of the possible directions for future research and also to develop an advanced process control strategy are presented by eliminating a few of the existing limitations.


      PubDate: 2016-04-08T11:57:21Z
       
  • Time-varying oscillation detector based on improved LMD and robust
           Lempel–Ziv complexity
    • Abstract: Publication date: June 2016
      Source:Control Engineering Practice, Volume 51
      Author(s): Lei Xie, Xun Lang, Junghui Chen, Alexander Horch, Hongye Su
      A novel method based on improved local mean decomposition (LMD) for oscillation detection is proposed. Due to its capability to analyze amplitude and frequency modulated signals, LMD is especially suitable for characterizing time-varying control loop oscillations. In contrast to empirical mode decomposition (EMD), the improved LMD performs better in the following aspects: (i) ability to extract both single/multiple oscillations in process output, (ii) robustness to noise, and (iii) capability to handle non-stationary trends. In addition, improved LMD can precisely characterize the time-varying oscillations without distortion and frequency leakage even for short time series. Finally, a robust Lempel–Ziv complexity based statistic for time-varying oscillation detection is presented. Simulation examples and industrial applications are provided to demonstrate the effectiveness of the proposed LMD oscillation detector.


      PubDate: 2016-03-31T01:01:38Z
       
  • Model-based feedforward register control of roll-to-roll web printing
           systems
    • Abstract: Publication date: June 2016
      Source:Control Engineering Practice, Volume 51
      Author(s): Zhihua Chen, Ying Zheng, Minjing Zhou, David Shan-Hill Wong, Lijuan Chen, Zhonghua Deng
      Roll-to-roll (R2R) printing press provides a continuous printing process to print the multi-color patterns onto a web. To correctly print patterns on webs without the register error, it is necessary to regulate the web tension and transport velocity. In this paper, a mathematical model is built for R2R web printing system, and a model-based feedforward PD (MFPD) control method is proposed to reduce the effects of interaction in adjacent print units whose print cylinders are driven by electrical line shafts and is compared with other control methods. The proposed control method is applied to an industrial 7-color gravure printing register system. The register error can be controlled in the range of ±0.1mm at a steady high speed, which meets the requirement of modern industrial application.


      PubDate: 2016-03-31T01:01:38Z
       
  • Fault tolerant control of a simulated hydroelectric system
    • Abstract: Publication date: June 2016
      Source:Control Engineering Practice, Volume 51
      Author(s): Silvio Simani, Stefano Alvisi, Mauro Venturini
      This paper analyses the application of two fault tolerant control schemes to a hydroelectric model developed in the Matlab and Simulink environments. The proposed fault tolerant controllers are exploited for regulating the speed of the Francis turbine included in the hydraulic system. The nonlinear behaviour of the hydraulic turbine and the inelastic water hammer effects are taken into account in order to develop a high-fidelity simulator of this dynamic plant. The first fault tolerant control solution relies on an adaptive control design, which exploits the recursive identification of a linear parametric time-varying model of the monitored system. The second scheme proposed uses the identification of a fuzzy model that is exploited for the reconstruction of the fault affecting the system under diagnosis. In this way, the fault estimation and its accommodation is possible. Note that these strategies, which are both based on identification approaches, are suggested for enhancing the application of the suggested fault tolerant control methodologies. These characteristics of the study represent key issues when on-line implementations are considered for a viable application of the proposed fault tolerant control schemes. The faults considered in this paper affect the electric servomotor used as a governor, the hydraulic turbine speed sensor, and the hydraulic turbine system, and are imposed both separately and simultaneously. Moreover, the complete drop of the rotational speed sensor is also analysed. Monte-Carlo simulations are also used for analysing the most important issues of the proposed schemes in the presence of parameter variations. Moreover, the performances achieved by means of the proposed solutions are compared to those of a standard PID controller already developed for the considered model. Finally, these strategies serve to highlight the potential application of the proposed control strategies to real hydraulic systems.


      PubDate: 2016-03-26T00:45:13Z
       
  • Finite-time fault-tolerant control for flutter of wing
    • Abstract: Publication date: June 2016
      Source:Control Engineering Practice, Volume 51
      Author(s): Gao Ming-Zhou, Cai Guo-Ping, Nan Ying
      In this paper, we use the radial basis function neural network and the finite-time H ∞ adaptive fault-tolerant control technique to deal with the flutter problem of wings with propulsion system, which is affected by input saturation, time delay, time-varying parameter uncertainties and external disturbances. Then sensor and actuator faults are both considered in the control design. The theory content of this article includes the trajectory optimization, modeling of wing flutter and fault-tolerant controller design. The stability of the finite-time H ∞ adaptive fault-tolerant controller is theoretically proved. Finally, simulation results are given to demonstrate the effectiveness of the scheme.


      PubDate: 2016-03-26T00:45:13Z
       
  • Editorial Board
    • Abstract: Publication date: May 2016
      Source:Control Engineering Practice, Volume 50




      PubDate: 2016-03-22T00:31:27Z
       
  • Contents list
    • Abstract: Publication date: May 2016
      Source:Control Engineering Practice, Volume 50




      PubDate: 2016-03-22T00:31:27Z
       
  • Load compensation based on frame considering low-order dominant harmonics
           and distorted power system
    • Abstract: Publication date: June 2016
      Source:Control Engineering Practice, Volume 51
      Author(s): Mehdi Fallah, Mitra Imani, Mostafa Abarzadeh, Hossein Madadi Kojabadi, Mohammad Hejri
      In this paper, by considering voltage distortion and frequency variation, the control strategy of synchronous reference frame (SRF) for three-phase shunt active power filter has been improved. In the SRF compensation method a conventional low pass filter (CLPF) is used to extract the dc component of the d-axis current (I d). Unfortunately in the presence of low-order harmonics of the load current (second and third ones), the transient response time is increased. If the amplitude of these harmonics are high, the distortions in CLPF output signal are increased, and as a result, the desired compensation cannot be achieved. In this paper to overcome this problem, a novel numerical LPF is designed and implemented based on variable forgetting factor-recursive least squares (VFF-RLS). The advantages of the proposed filter over CLPFs include independence of the load current harmonic components, fast dynamic and high accuracy of the response. Moreover, due to the malfunction of the conventional phase locked loop (PLL) in polluted and variable frequency environment, a second order generation integrator-frequency locked loop (SOGI-FLL) based on fuzzy logic controller (FLC) and wavelet transform (WT) is proposed. Effectiveness of the proposed method is evaluated with both simulations and experimental results in a three-phase power system.


      PubDate: 2016-03-17T00:15:46Z
       
  • Modified dynamic surface approach with bias torque for multi-motor
           servomechanism
    • Abstract: Publication date: May 2016
      Source:Control Engineering Practice, Volume 50
      Author(s): Minlin Wang, Xuemei Ren, Qiang Chen, Shubo Wang, Xuehui Gao
      This paper presents a modified neural dynamic surface control (DSC) with an adaptive bias torque for the multi-motor servomechanism (MMS) with backlash, friction and other disturbances. By introducing a continuous hybrid differentiator to replace the first-order filter in each step, a modified DSC is developed to improve the load tracking precision of MMS. However, when the MMS enters the backlash band, only DSC cannot guarantee the load tracking performance. Thus, an adaptive bias torque is firstly proposed based on the prescribed performance function technique to compensate the backlash nonlinearity and guarantee the load tracking performance of MMS. In addition, the unknown dynamics including the friction and other disturbances are approximated by using wavelet echo state networks where the weights are all updated online. By means of Lyapunov stability theory, the semi-globally uniformly ultimately bounded (SGUUB) property of all signals in the closed-loop system is proved. Finally, simulations and experimental results based on a four-motor servomechanism are presented to show the effectiveness of the proposed approach.


      PubDate: 2016-03-13T20:19:24Z
       
  • An improved weighted recursive PCA algorithm for adaptive fault detection
    • Abstract: Publication date: May 2016
      Source:Control Engineering Practice, Volume 50
      Author(s): Ivan Portnoy, Kevin Melendez, Horacio Pinzon, Marco Sanjuan
      A novel weighted adaptive recursive fault detection technique based on Principal Component Analysis (PCA) is proposed to address the issue of the increment in false alarm rate in process monitoring schemes due to the natural, slow and normal process changes (aging), which often occurs in real processes. It has been named as weighted adaptive recursive PCA (WARP). The aforementioned problem is addressed recursively by updating the eigenstructure (eigenvalues and eigenvectors) of the statistical detection model when the false alarm rate increases given the awareness of non-faulty condition. The update is carried out by incorporating the new available information within a specific online process dataset, instead of keeping a fixed statistical model such as conventional PCA does. To achieve this recursive updating, equations for means, standard deviations, covariance matrix, eigenvalues and eigenvectors are developed. The statistical thresholds and the number of principal components are updated as well. A comparison between the proposed algorithm and other recursive PCA-based algorithms is carried out in terms of false alarm rate, misdetection rate, detection delay and its computational complexity. WARP features a significant reduction of the computational complexity while maintaining a similar performance on false alarm rate, misdetection rate and detection delay compared to that of the other existing PCA-based recursive algorithms. The computational complexity is assessed in terms of the Floating Operation Points (FLOPs) needed to carry out the update.
      Graphical abstract image

      PubDate: 2016-03-13T20:19:24Z
       
  • Process monitoring via enhanced neighborhood preserving embedding
    • Abstract: Publication date: May 2016
      Source:Control Engineering Practice, Volume 50
      Author(s): Bing Song, Shuai Tan, Hongbo Shi
      A novel process monitoring scheme named enhanced neighborhood preserving embedding (ENPE) is proposed. Neighborhood preserving embedding (NPE) only considers the reconstruction error on the basis of each local neighborhood is linear. For the purpose of addressing both the reconstruction error and the distance, the dual weight matrix and the enhanced objective function are constructed in the ENPE method. Finally, under a numerical example and the Tennessee Eastman (TE) benchmark, the superiority of the proposed ENPE method is evaluated through comparing with principal component analysis (PCA) and NPE.


      PubDate: 2016-03-08T19:57:29Z
       
  • Airship robust path-tracking: A tutorial on airship modelling and
           gain-scheduling control design
    • Abstract: Publication date: May 2016
      Source:Control Engineering Practice, Volume 50
      Author(s): Alexandra Moutinho, José Raul Azinheira, Ely C. de Paiva, Samuel S. Bueno
      This paper provides a tutorial view on airship path-tracking under wind disturbances. It addresses the relevant aspects towards this objective, namely the airship modelling, the dynamics analysis over the flight envelope, and the step-by-step design of a gain-scheduling control. The required parts to build a proper airship simulator are given: airship dynamics and actuation, and wind disturbances. A path-tracking gain-scheduling controller is designed and its performance and robustness evaluated in the simulation environment described for a complete airship mission consisting of vertical takeoff and landing, cruise flight and ground-hover, under realistic wind disturbances. Throughout the paper, considerations are done regarding the airship behavior and limitations, as well as what can be accomplished and how.
      Graphical abstract image Highlights

      PubDate: 2016-03-08T19:57:29Z
       
  • Experimental evaluation of anti-windup extremum seeking control for
           airside economizers
    • Abstract: Publication date: May 2016
      Source:Control Engineering Practice, Volume 50
      Author(s): Baojie Mu, Yaoyu Li, John M. House, Timothy I. Salsbury
      The performance of anti-windup extremum seeking control (ESC) as a model free online optimization strategy is evaluated by experimental studies for energy efficient operation of both chilled-water and direct-expansion airside economizers. For the chilled-water based system, the ESC takes the chilled-water valve control signal as the feedback, and controls the outdoor air damper (OAD) position to minimize the cooling coil load. For the direct-expansion system, the ESC takes the total electricity power consumption as the feedback, and controls the OAD position to minimize the power consumption. Experimental results verify the effectiveness of the ESC scheme for model-free operation without temperature and humidity measurements.


      PubDate: 2016-03-08T19:57:29Z
       
  • High speed laser scanning microscopy by iterative learning control of a
           galvanometer scanner
    • Abstract: Publication date: May 2016
      Source:Control Engineering Practice, Volume 50
      Author(s): Han Woong Yoo, Shingo Ito, Georg Schitter
      Iterative learning control (ILC) for a galvanometer scanner is proposed to achieve high speed, linear, and accurate bidirectional scanning for scanning laser microscopy. A galvanometer scanner, as a low stiffness actuator, is first stabilized with a feedback control compensating for disturbances and nonlinearities at low frequencies, and ILC is applied for the control of the fast scanning motion. For stable inversion of the non-minimum phase zeros, a time delay approximation and a zero phase approximation are used for design of ILC, and their attainable bandwidths are analyzed. Experimental results verify the benefits of ILC of its wide control bandwidth, enabling a faster, more linear, and more accurate scanning without a phase lag and a gain mismatch. At the scan rate of 4112 lines per second, the root mean square (RMS) error of the ILC can be reduced by a factor of 73 in comparison with the feedback controlled galvanometer scanner of the commercial system.


      PubDate: 2016-03-08T19:57:29Z
       
  • A methodology and a software tool for sensor data
           validation/reconstruction: Application to the Catalonia regional water
           network
    • Abstract: Publication date: April 2016
      Source:Control Engineering Practice, Volume 49
      Author(s): Miquel À. Cugueró-Escofet, Diego García, Joseba Quevedo, Vicenç Puig, Santiago Espin, Jaume Roquet
      In this paper, a sensor data validation/reconstruction methodology applicable to water networks and its implementation by means of a software tool are presented. The aim is to guarantee that the sensor data are reliable and complete in case that sensor faults occur. The availability of such dataset is of paramount importance in order to successfully use the sensor data for further tasks e.g. water billing, network efficiency assessment, leak localization and real-time operational control. The methodology presented here is based on a sequence of tests and on the combined use of spatial models (SM) and time series models (TSM) applied to the sensors used for real-time monitoring and control of the water network. Spatial models take advantage of the physical relations between different system variables (e.g. flow and level sensors in hydraulic systems) while time series models take advantage of the temporal redundancy of the measured variables (here by means of a Holt–Winters (HW) time series model). First, the data validation approach, based on several tests of different complexity, is described to detect potential invalid or missing data. Then, the reconstruction process is based on a set of spatial and time series models used to reconstruct the missing/invalid data with the model estimation providing the best fit. A software tool implementing the proposed data validation and reconstruction methodology is also described. Finally, results obtained applying the proposed methodology to a real case study based on the Catalonia regional water network is used to illustrate its performance.


      PubDate: 2016-02-25T19:27:25Z
       
  • Plant-wide root cause identification using plant key performance
           indicators (KPIs) with application to a paper machine
    • Abstract: Publication date: April 2016
      Source:Control Engineering Practice, Volume 49
      Author(s): Moncef Chioua, Margret Bauer, Su-Liang Chen, Jan C. Schlake, Guido Sand, Werner Schmidt, Nina F. Thornhill
      Previously, plant-wide disturbance analysis has looked into the propagation of faults through an industrial production process by investigating process measurements. However, the extent of the analysis has mostly been limited to a section of a plant. In this work, we propose a top-down approach which investigates measurements of the complete plant and identifies a section where the disturbance originates. Root cause analysis is carried out thereafter to pinpoint the faulty asset. The proposed approach has three novel elements: Using key performance indicators (KPI) as reference and starting point of the analysis, restricting measurements to a measurement type (e.g. flow) thus focusing on a section and applying the novel method of contribution plots of spectral PCA T 2 statistic to find the contribution of each measurement towards the disturbance observed in the KPI. The approach is described and carried out on a paper machine where a quality KPI showed an established oscillation.


      PubDate: 2016-02-25T19:27:25Z
       
  • Multi-leak diagnosis in pipelines based on Extended Kalman Filter
    • Abstract: Publication date: April 2016
      Source:Control Engineering Practice, Volume 49
      Author(s): J.A. Delgado-Aguiñaga, G. Besançon, O. Begovich, J.E. Carvajal
      A model-based approach to detect and isolate non-concurrent multiple leaks in a pipeline is proposed, only using pressure and flow sensors placed at the pipeline ends. The approach relies on a nonlinear modeling derived from Water–Hammer equations, and related Extended Kalman Filters used to estimate leak coefficients. This extends former results developed for the single leak case, but with the difficulty that the model is modified at each new leak occurrence. A model adaptation strategy is thus proposed, allowing us to monitor indeed each new leak, and no matter where it appears. Experimental results illustrate the performance of the proposed algorithm.


      PubDate: 2016-02-25T19:27:25Z
       
  • IFC - Editorial Board / Funding body / agreements policies
    • Abstract: Publication date: April 2016
      Source:Control Engineering Practice, Volume 49




      PubDate: 2016-02-25T19:27:25Z
       
  • Design of experiments and statistical process control using wavelets
           analysis
    • Abstract: Publication date: April 2016
      Source:Control Engineering Practice, Volume 49
      Author(s): Achraf Cohen, Teodor Tiplica, Abdessamad Kobi
      In this paper, three new connections between Wavelets analysis and Statistical Quality Control are proposed. Firstly, we show that the Discrete Wavelet Transform, using Haar wavelet, is equivalent to the Xbar-R control scheme. Results concerning the distribution of wavelets coefficients, using others wavelets families, are presented, and then a new control chart, called DeWave, is proposed, in order to monitor the variability of the process. Secondly, the equivalence between the Likelihood Ratio and the Continuous Wavelet Transform, in terms of estimating the change time, is presented. Finally, we demonstrate that the Discrete Wavelet Transform is an equivalent representation of factorial Design Of Experiments.


      PubDate: 2016-02-25T19:27:25Z
       
  • Reference trajectory tuning of model predictive control
    • Abstract: Publication date: May 2016
      Source:Control Engineering Practice, Volume 50
      Author(s): André Shigueo Yamashita, Paulo Martin Alexandre, Antonio Carlos Zanin, Darci Odloak
      An approach to minimize tuning effort of nominal Model Predictive Control algorithms is proposed. The algorithm dynamically calculates output set points to accommodate user-defined output importance, which is more intuitive than selecting values for the MPC weighing matrices. Instead of tuning the weights on the outputs deviations from their set points, weights on the input values and input increments, which are the usual tuning parameters of MPC, the desired output control performance of the MPC can be specified by performance factors. The proposed method extends the existing methods that consider a reference trajectory for the output tracking to the case of zone control and input targets. The proposed method also assumes that, as in most commercial MPC packages, the controller has two layers: a static layer and an extended dynamic layer. The method is illustrated by three case studies, contemplating both SISO and MIMO systems. It is observed that: the output set point tracking performance can be changed without modifying the MPC tuning weights, the approach is capable of achieving similar performance to conventional MPC tuned by multiobjective optimization techniques from the literature, with a fraction of computer effort, and it can be integrated with Real Time Optimization algorithms to control complex systems, always respecting output constraints.


      PubDate: 2016-02-20T12:37:52Z
       
  • Nonlinear PI control for variable pitch wind turbine
    • Abstract: Publication date: Available online 17 February 2016
      Source:Control Engineering Practice
      Author(s): Yaxing Ren, Liuying Li, Joseph Brindley, Lin Jiang
      Wind turbine uses a pitch angle controller to reduce the power captured above the rated wind speed and release the mechanical stress of the drive train. This paper investigates a nonlinear PI (N-PI) based pitch angle controller, by designing an extended-order state and perturbation observer to estimate and compensate unknown time-varying nonlinearities and disturbances. The proposed N-PI does not require the accurate model and uses only one set of PI parameters to provide a global optimal performance under wind speed changes. Simulation verification is based on a simplified two-mass wind turbine model and a detailed aero-elastic wind turbine simulator (FAST), respectively. Simulation results show that the N-PI controller can provide better dynamic performances of power regulation, load stress reduction and actuator usage, comparing with the conventional PI and gain-scheduled PI controller, and better robustness against of model uncertainties than feedback linearization control.


      PubDate: 2016-02-20T12:37:52Z
       
  • Practical relevance of faults, diagnosis methods, and tolerance measures
           in elastically actuated robots
    • Abstract: Publication date: Available online 16 February 2016
      Source:Control Engineering Practice
      Author(s): Philipp Beckerle
      Elastically actuated robots promise safe human–robot interaction and energy-efficient motions. Yet, increased complexity and critical operation states might increase the practical fault risk. This paper explores faults in such robots using expert data from the field and identifies components that show increased fault occurrence: the highest fault sensitivity occurs in kinematics, electronics, sensors, and software. Since elastic actuators are an active field of research, few cases of industrial application exist and thus most experts in this study have academic background. Beyond assessing fault sensitivity, countermeasures such as redundant design are compiled. A brief literature review discusses fault diagnosis and fault-tolerant design with respect to these insights. Despite the availability of a few promising methods in robotics, neither diagnosis nor tolerance do receive sufficient recognition leaving potential for practical application.


      PubDate: 2016-02-20T12:37:52Z
       
  • Nonlinear aircraft sensor fault reconstruction in the presence of
           disturbances validated by real flight data
    • Abstract: Publication date: Available online 15 February 2016
      Source:Control Engineering Practice
      Author(s): Peng Lu, Erik-Jan van Kampen, Cornelis de Visser, Qiping Chu
      This paper proposes an approach for Inertial Measurement Unit sensor fault reconstruction by exploiting a ground speed-based kinematic model of the aircraft flying in a rotating earth reference system. Two strategies for the validation of sensor fault reconstruction are presented: closed-loop validation and open-loop validation. Both strategies use the same kinematic model and a newly-developed Adaptive Two-Stage Extended Kalman Filter to estimate the states and faults of the aircraft. Simulation results demonstrate the effectiveness of the proposed approach compared to an approach using an airspeed-based kinematic model. Furthermore, the major contribution is that the proposed approach is validated using real flight test data including the presence of external disturbances such as turbulence. Three flight scenarios are selected to test the performance of the proposed approach. It is shown that the proposed approach is robust to model uncertainties, unmodeled dynamics and disturbances such as time-varying wind and turbulence. Therefore, the proposed approach can be incorporated into aircraft Fault Detection and Isolation systems to enhance the performance of the aircraft.


      PubDate: 2016-02-16T12:24:15Z
       
  • Multiphase rotor current observers for current predictive control: A
           five-phase case study
    • Abstract: Publication date: Available online 9 February 2016
      Source:Control Engineering Practice
      Author(s): Cristina Martín, Manuel R. Arahal, Federico Barrero, Mario J. Durán
      The use of multiphase drives has gained importance in recent times due to some advantages that they provide over conventional three-phase ones. High performance stator current control can be achieved by means of direct command of voltage source inverter. In this context finite-state model predictive control is a very flexible strategy that has been recently proposed and analyzed. Nevertheless, its implementation must solve the problem of estimating rotor quantities, being the conventional solution a simple backtracking procedure. In this respect, observers appear as an attractive alternative. However, while they have been used with FOC, sensorless drives and for fault detection, they have not been used yet for predictive control of drives as a way to provide rotor values estimates. In this paper the authors propose to incorporate a full-order rotor current observer in a finite-state model predictive controller of a five-phase induction machine. Pole placement design based on Butterworth filters is used. The new estimation scheme and the standard procedure are compared. By means of experimental tests, the differences between both approaches and the benefits of including a rotor observer are illustrated and verified.


      PubDate: 2016-02-12T11:14:48Z
       
  • Control architecture and design method of reconfigurable manufacturing
           systems
    • Abstract: Publication date: Available online 5 February 2016
      Source:Control Engineering Practice
      Author(s): Robson Marinho da Silva, Fabrício Junqueira, Diolino J. Santos Filho, Paulo E. Miyagi
      This paper proposes a control architecture for reconfigurable manufacturing systems and its design method based on Petri nets (Input Output Place Transition and Production Flow Schema), Service-Oriented Architecture and Holonic and Multi-Agent System techniques, among other good practices. The control architecture integrates value-added activities, information and resources. The method considers the exchange of knowledge among heterogeneous business workflow of manufacturing subsystems in different geographical locations, and allows modeling process, product, machine and device control. An example demonstrates advantages of the resulting control system.
      Graphical abstract image Highlights

      PubDate: 2016-02-12T11:14:48Z
       
  • Design of a composite recurrent Laguerre orthogonal polynomial neural
           network control system with ameliorated particle swarm optimization for a
           continuously variable transmission system
    • Abstract: Publication date: April 2016
      Source:Control Engineering Practice, Volume 49
      Author(s): Chih-Hong Lin
      Because the nonlinear and time-varying characteristics of the V-belt continuously variable transmission system driven by a permanent magnet synchronous motor (PMSM) are unknown, improving the control performance of the linear control design is time-consuming. To overcome difficulties in the design of a linear controller for the PMSM servo-driven V-belt continuously variable transmission system with lumped nonlinear load disturbances, a composite recurrent Laguerre orthogonal polynomial neural network (NN) control system with ameliorated particle swarm optimization (PSO), which has the online learning capability to respond to the nonlinear time-varying system, was developed. The composite recurrent Laguerre orthogonal polynomial NN control system can perform inspector control, recurrent Laguerre orthogonal polynomial NN control which involves an adaptation law, and recouped control which involves an estimation law. Moreover, the adaptation law of online parameters in the recurrent Laguerre orthogonal polynomial NN is based on the Lyapunov stability theorem. The use of ameliorated particle swarm optimization yielded two optimal learning rates for the parameters, which helped improve convergence. Finally, comparison of the experimental results of the present study with those of previous studies demonstrated the high control performance of the proposed control scheme.


      PubDate: 2016-02-12T11:14:48Z
       
  • On the limit cycle stabilization of a DC/DC three-cell converter
    • Abstract: Publication date: April 2016
      Source:Control Engineering Practice, Volume 49
      Author(s): M. Benmiloud, A. Benalia, M. Defoort, M. Djemai
      This paper investigates a new state feedback controller design for DC/DC three-cell converter. The high dynamic performances of the converter have been translated into a desired limit cycle stabilization problem. The state feedback is established using hybrid automaton formalism, which allows us to design independently a transitory state and steady state control schemes. Finite-time convergence of the trajectory to the steady state and the local asymptotic stability of the desired limit cycle under the proposed controller are proved analytically. Simulation and experimental results confirm the theoretical results and show the effectiveness and robustness of the hybrid controller in spite of load variations.


      PubDate: 2016-02-12T11:14:48Z
       
  • Control performance assessment based on sensor fusion techniques
    • Abstract: Publication date: April 2016
      Source:Control Engineering Practice, Volume 49
      Author(s): S. Afshar Khamseh, A. Khaki Sedigh, B. Moshiri, A. Fatehi
      Control performance assessment techniques are widely studied and many performance assessment indices have been proposed. In this paper, a control performance assessment technique for multi-loop control systems is presented based on the decision fusion strategy. Since decisions based on individual indices can lead to erroneous results, decision fusion of different indices can improve the assessment accuracy, especially in multi-loop control systems in the presence of loop interactions. Performance assessment indices are individually evaluated and decisions based on these indices are fused. The results of simulation and practical implementation on series cascade control structures illustrate the effectiveness of the proposed algorithm.


      PubDate: 2016-02-12T11:14:48Z
       
  • Intelligent control of a prosthetic ankle joint using gait recognition
    • Abstract: Publication date: April 2016
      Source:Control Engineering Practice, Volume 49
      Author(s): Anh Mai, Sesh Commuri
      Desire for better prosthetic feet for below-knee amputees has motivated the development of several active and highly functional devices. These devices are equipped with controlled actuators in order to replicate biomechanical characteristics of the human ankle, improve the amputee gait, and reduce the amount of metabolic energy consumed during locomotion. However, the functioning of such devices on human subjects is difficult to test due to changing gait, unknown ankle dynamics, complicated interaction between the foot and the ground, as well as between the residual limb and the prosthesis. Commonly used approaches in control of prosthetic feet treat these effects as disturbances and ignore them, thereby degrading the performance and efficiency of the devices. In this paper, an artificial neural network-based hierarchical controller is proposed that first recognizes the amputees' intent from the actual measured gait data, then selects a displacement profile for the prosthetic joint based on the amputees' intent, and then adaptively compensates for the unmodeled dynamics and disturbances for closed loop stability with guaranteed tracking performance. Detailed theoretical analysis is carried out to establish the stability and robustness of the proposed approach. The performance of the controller presented in this paper is demonstrated using actual gait data collected from human subjects. Numerical simulations are used to demonstrate the advantages of the proposed strategy over conventional approaches to the control of the prosthetic ankle, especially when the presence of noise, uncertainty in terrain interaction, disturbance torques, variations in gait parameters, and changes in gait are considered.


      PubDate: 2016-02-12T11:14:48Z
       
  • Modeling, state estimation and nonlinear model predictive control of
           cathode exhaust gas mass flow for PEM fuel cells
    • Abstract: Publication date: Available online 3 February 2016
      Source:Control Engineering Practice
      Author(s): M. Schultze, J. Horn
      Polymer electrolyte membrane fuel cells are efficient energy converters and provide electrical energy, water and oxygen depleted air with a low oxygen content as exhaust gas if fed with air. Due to their low emission of greenhouse gases and noise they are investigated as replacement for auxiliary power units currently used for electrical power supply on aircraft. Oxygen depleted air, called ODA-gas, with an oxygen concentration of 10–11% and a low humidity can be used for tank-inerting on aircraft. A challenging task is controlling the fuel cell system for generation of dehumidified ODA-gas mass flow while simultaneously keeping bounds and gradients on control inputs. This task is attacked by a nonlinear model predictive control. Not all system states can be measured and some states measured exhibit a significant time delay. A nonlinear state estimation strategy builds the entire system state and compensates for the delay. The nonlinear model predictive control and the state estimation are derived from the system model, which is presented. Simulation and experimental results are shown.


      PubDate: 2016-02-12T11:14:48Z
       
  • Advanced decision control system for effluent violations removal in
           wastewater treatment plants
    • Abstract: Publication date: Available online 29 January 2016
      Source:Control Engineering Practice
      Author(s): I. Santín, C. Pedret, R. Vilanova, M. Meneses
      This paper presents the application of control strategies for wastewater treatment plants with the goal of effluent limits violations removal as well as achieving a simultaneous improvement of effluent quality and reduction of operational costs. The evaluation is carried out with the Benchmark Simulation Model No. 2. The automatic selection of the suitable control strategy is based on risk detection of effluent violations by Artificial Neural Networks. Fuzzy Controllers are implemented to improve the denitrification or nitrification process based on the proposed objectives. Model Predictive Control is applied for the improvement of dissolved oxygen tracking.


      PubDate: 2016-02-01T15:16:35Z
       
 
 
JournalTOCs
School of Mathematical and Computer Sciences
Heriot-Watt University
Edinburgh, EH14 4AS, UK
Email: journaltocs@hw.ac.uk
Tel: +00 44 (0)131 4513762
Fax: +00 44 (0)131 4513327
 
About JournalTOCs
API
Help
News (blog, publications)
JournalTOCs on Twitter   JournalTOCs on Facebook

JournalTOCs © 2009-2015