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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  [2970 journals]
  • Supervisory control of a heavy-duty diesel engine with an electrified
           waste heat recovery system
    • Abstract: Publication date: September 2016
      Source:Control Engineering Practice, Volume 54
      Author(s): Emanuel Feru, Nikolce Murgovski, Bram de Jager, Frank Willems
      This paper presents an integrated energy and emission management strategy, called Integrated Powertrain Control (IPC), for an Euro-VI diesel engine with an electrified waste heat recovery system. This strategy optimizes the CO 2 – NO x trade-off by minimizing the operational costs associated with fuel consumption, AdBlue dosage, and active particulate filter regeneration, while satisfying the tailpipe emission constraints. For comparison purposes, the proposed control strategy is applied to different powertrain configurations: with and without waste heat recovery (WHR) system and a WHR system equipped with a battery for energy storage. The potential of each studied configuration is evaluated over the World Harmonized Transient Cycle for cold-start and hot-start conditions. In comparison to the existing Euro VI engine without WHR system, it is shown in simulations that the optimal IPC strategy with an electrified WHR system and battery provides an additional 3.5% CO2 emission reduction and 19% particulate matter reduction, while satisfying the NO x emission constraint.


      PubDate: 2016-06-17T18:00:49Z
       
  • Petri-net-based robust supervisory control of automated manufacturing
           systems
    • Abstract: Publication date: September 2016
      Source:Control Engineering Practice, Volume 54
      Author(s): Hao Yue, Keyi Xing, Hesuan Hu, Weimin Wu, Hongye Su
      Supervisory control that ensures deadlock-free and nonblocking operation has been an active research area of manufacturing engineering. So far, most of deadlock control policies in the existing literature assume that allocated resources are reliable. Additionally, a large number of methods are for systems of simple sequential processes with resources (S3PRs), where a part uses only one copy of one resource at each processing step. In contrast, we investigate the automated manufacturing systems (AMSs) that can be modeled by a class of Petri nets, namely S*PUR. S*PUR is a generalization of the S*PR Petri net model, while S*PR is a superclass of S3PR. This work addresses the robust supervision for deadlock avoidance in S*PUR. Specifically, we take into account unreliable resources that may break down while working or being in idle, and the considered AMSs allow the use of multiple copies of different resources per operation stage. Our objective is to control the system so that: 1) when there are breakdowns, the system can continue producing parts of some types whose production does not need any failed resources; and 2) given the correction of all faults, it is possible to complete all the on-going part instances remaining in the system. We illustrate the characteristics of a desired supervisor through several examples, define the corresponding properties of robustness, and develop a control policy that satisfies such properties.


      PubDate: 2016-06-17T18:00:49Z
       
  • Disturbance rejection of battery/ultracapacitor hybrid energy sources
    • Abstract: Publication date: September 2016
      Source:Control Engineering Practice, Volume 54
      Author(s): Ping Dai, Sébastien Cauet, Patrick Coirault
      This paper contributes an active control strategy to reject disturbances in hybrid energy source systems applied in hybrid electric vehicles. The disturbances include persistent disturbances introduced by engine torque ripples compensation, and transient disturbances caused by transient load power demands. The disturbance rejection is achieved via singular perturbation theory. The original system is a Port-Controlled Hamiltonian (PCH) system, and the controller is designed based on interconnection and damping assignment. Experimental results verify the effectiveness of the disturbance rejection control.


      PubDate: 2016-06-17T18:00:49Z
       
  • Nonlinear state estimation for suspension control applications: a
           Takagi-Sugeno Kalman filtering approach
    • Abstract: Publication date: Available online 15 June 2016
      Source:Control Engineering Practice
      Author(s): Nils Pletschen, Klaus J. Diepold
      A new nonlinear state estimation approach, which combines classical Kalman filter theory and Takagi-Sugeno (TS) modeling, is proposed in this paper. To ensure convergence of the TS observer, conditions are derived that explicitly account for the TS model's confined region of validity. Thereby, the secured domain of attraction (DA) of the TS error dynamics is maximized within given bounds. The TS Kalman filtering concept is then applied to a hybrid vehicle suspension configuration, whose nonlinear dynamics are exactly represented by a continuous-time TS system. The benefit of the novel estimation technique is analyzed in comparison with the well-known EKF and UKF variants in simulations and experiments of a passive and an actively controlled suspension configuration in a quarter-car set-up. Employing a real road profile as disturbance input, the TS Kalman filter shows the highest estimation quality of the concepts studied. Moreover, as its computational complexity adds up to only one third of the one involved with the classical methods, the new approach operates remarkably efficient.


      PubDate: 2016-06-17T18:00:49Z
       
  • Contents list continued
    • Abstract: Publication date: August 2016
      Source:Control Engineering Practice, Volume 53




      PubDate: 2016-06-13T05:04:24Z
       
  • Contents list
    • Abstract: Publication date: August 2016
      Source:Control Engineering Practice, Volume 53




      PubDate: 2016-06-13T05:04:24Z
       
  • Editorial Board
    • Abstract: Publication date: July 2016
      Source:Control Engineering Practice, Volume 52




      PubDate: 2016-06-13T05:04:24Z
       
  • Contents list
    • Abstract: Publication date: July 2016
      Source:Control Engineering Practice, Volume 52




      PubDate: 2016-06-13T05:04:24Z
       
  • Intelligent coordinated controller design for a 600MW supercritical boiler
           unit based on expanded-structure neural network inverse models
    • Abstract: Publication date: August 2016
      Source:Control Engineering Practice, Volume 53
      Author(s): Liangyu Ma, Kwang Y. Lee, Zhiyan Wang
      Under present widespread automatic generation control (AGC) centered on regional power grid, a large-capacity coal-fired supercritical (SC) power unit often operates under wide-range variable load conditions. Since a SC once-through boiler unit is represented by a typical multivariable system with large inertia and non-linear, slow time-variant and time-delay characteristics, it often makes the coordinated control quality deteriorate under wide-range loading conditions, and thus influences the unit load response speed and leads to heavy fluctuation of the main steam pressure. To improve the SC unit’s coordinated control quality with advanced intelligent control strategy, the neural-network (NN) based expanded-structure inverse system models of a 600MW SC boiler unit were investigated. A feedforward neural network with time-delayed inputs and time-delayed output feedbacks was adopted to establish the inverse models for the load and the main steam pressure characteristics. Based on the model, a neural network inverse coordinated control scheme was designed and tested in a full-scope power plant simulator of the given SC power unit, which showed that the proposed coordinated control scheme can achieve better control results compared to the original PID coordinated control.


      PubDate: 2016-06-13T05:04:24Z
       
  • Performance assessment of thermal power plant load control system based on
           covariance index
    • Abstract: Publication date: September 2016
      Source:Control Engineering Practice, Volume 54
      Author(s): Wang Yinsong, Li Shizhe, Tian Jingyu, Zhao Zheng
      This paper proposes a novel method of performance assessment for load control system of thermal power unit. Load control system is the most important multivariable control system. It is necessary to monitor and evaluate the performance of it. The performance evaluation index system based on covariance is defined, and the performance evaluation rules are given. In MATLAB, the double input and double output object model of the load control system is established, and the dynamic characteristics of the load control system are analyzed under the BF and TF mode. The simulation data, which is based on the parameters retuning, is used as the “benchmark data”, and the simulation data of different controllers are collected as “monitoring data”. For most of the time, the thermal power plant is under the coordinated control mode, and the principle and strategy of the two coordinated control are analyzed, and the engineering realization scheme is given. Operation data in different time periods of two different thermal power plants was acquisition and preprocessing respectively. The principle of selecting “benchmark data” is the minimum of pressure parameter. Two data segments were selected as “benchmark data”, performance assessment and analysis was carried on the data from other time periods. The results show that the validity and reliability of the method based on the evaluation index. In short, the data of the simulation and the load control system of power plant are used to demonstrate the effectiveness of the method.


      PubDate: 2016-06-13T05:04:24Z
       
  • Vehicle sideslip estimator using load sensing bearings
    • Abstract: Publication date: September 2016
      Source:Control Engineering Practice, Volume 54
      Author(s): Anil Kunnappillil Madhusudhanan, Matteo Corno, Edward Holweg
      This paper investigates the potential of load based vehicle sideslip estimation. Different techniques to measure tyre forces have been presented over the years; so far no technique has made it to the market. This paper considers a new technology based on load sensing bearings, which provides tyre force measurements. Based on the features of the sensor, a vehicle sideslip angle estimator is designed, analyzed and tested. The paper shows that direct tyre force sensing has mainly two advantages over traditional model-based estimators: primarily, it avoids the use of tyre models, which are heavily affected by uncertainties and modeling errors and secondarily, providing measurements on the road plane, it is less prone to errors introduced by roll and pitch dynamics. Extensive simulation tests along with a detailed analysis of experimental tests performed on an instrumented vehicle prove that the load based estimation outperforms the kinematic model-based benchmark yielding a root mean square error of 0.15°.


      PubDate: 2016-06-13T05:04:24Z
       
  • Distributed generation system control strategies with PV and fuel cell in
           microgrid operation
    • Abstract: Publication date: August 2016
      Source:Control Engineering Practice, Volume 53
      Author(s): Wenlei Bai, M. Reza Abedi, Kwang Y. Lee
      Control strategies of distributed generation (DG) are investigated for different combination of DG and storage units in a microgrid. In this paper the authors proposed a microgrid structure which consists of a detailed photovoltaic (PV) array model, a solid oxide fuel cell (SOFC) and various loads. Real and reactive power (PQ) control and droop control are developed for microgrid operation. In grid-connected mode, PQ control is developed by controlling the active and reactive power output of DGs in accordance with assigned references. Two PI controllers were used in the PQ controller, and a novel heuristic method, artificial bee colony (ABC), was adopted to tune the PI parameters. DGs can be controlled by droop control both under grid-connected and islanded modes. Droop control implements power reallocation between DGs based on predefined droop characteristics whenever load changes or the microgrid is connected/disconnected to the grid, while the microgrid voltage and frequency is maintained at appropriate levels. Through voltage, frequency, and power characteristics in the simulation under different scenarios, the proposed control strategies have demonstrated to work properly and effectively. The simulation results also show the effectiveness of tuning PI parameters by the ABC.


      PubDate: 2016-06-13T05:04:24Z
       
  • Plasma q-profile control in tokamaks using a damping assignment
           passivity-based approach
    • Abstract: Publication date: September 2016
      Source:Control Engineering Practice, Volume 54
      Author(s): Ngoc Minh Trang Vu, Rémy Nouailletas, Laurent Lefèvre, Federico Felici
      The IDA-PBC based on PCH model for tokamak q-profile is investigated. Two scenarios are carried out. The first one is the resistive diffusion model for the magnetic poloidal flux. The second one is extended with the thermal diffusion. A feedforward control is used to ensure the compatibility with the actuator physical ability. An IDA-PBC feedback is proposed to improve the system stabilization and convergence speed. The controllers are validated in the simulation using RAPTOR code and tested in TCV, the result is analyzed and the followed discussion proposed the required improvement for the next experiments.


      PubDate: 2016-06-13T05:04:24Z
       
  • Unknown-input observer design for motorcycle lateral dynamics: TS approach
    • Abstract: Publication date: September 2016
      Source:Control Engineering Practice, Volume 54
      Author(s): Mohammed El-Habib Dabladji, Dalil Ichalal, Hichem Arioui, Saïd Mammar
      In this paper, a nonlinear observer is designed in order to estimate the lateral dynamics of motorcycles. A nonlinear model of motorcycle's lateral dynamics is considered and is transformed in a Takagi-Sugeno (TS) exact form. An unknown input (UI) nonlinear observer is then designed in order to reconstruct the state variables whatever the forward velocity variations. The observer convergence study is based on the Lyapunov theory. The boundedness of the state estimation error is guaranteed thanks to the Input to State Stability (ISS) property. The observer has been tested on a nonlinear multibody model.


      PubDate: 2016-06-13T05:04:24Z
       
  • Digital memory look-up based implementation of sliding mode control for
           dc–dc converters
    • Abstract: Publication date: September 2016
      Source:Control Engineering Practice, Volume 54
      Author(s): Bibaswan Banerjee, Ramchandra M. Kotecha, Wayne W. Weaver
      Switched power electronic converters involve different control actions for different system events. A local control strategy may be developed which reacts only to some local information available to each component without any communication between the different system components located far away in real time. The purpose of this paper is to present a low cost memory based control strategy in a dc–dc boost converter. The control employed in this work is based on a sliding-mode hysteretic control strategy where the sliding manifold is derived a priori and stored as a look-up table in digital memory hardware. The proposed control implementation strategy is low cost and offers a robust dynamic response that is used to mitigate many disturbances in the system.


      PubDate: 2016-06-13T05:04:24Z
       
  • Power system observability and dynamic state estimation for stability
           monitoring using synchrophasor measurements
    • Abstract: Publication date: August 2016
      Source:Control Engineering Practice, Volume 53
      Author(s): Kai Sun, Junjian Qi, Wei Kang
      Growing penetration of intermittent resources such as renewable generations increases the risk of instability in a power grid. This paper introduces the concept of observability and its computational algorithms for a power grid monitored by the wide-area measurement system (WAMS) based on synchrophasors, e.g. phasor measurement units (PMUs). The goal is to estimate real-time states of generators, especially for potentially unstable trajectories, the information that is critical for the detection of rotor angle instability of the grid. The paper studies the number and siting of synchrophasors in a power grid so that the state of the system can be accurately estimated in the presence of instability. An unscented Kalman filter (UKF) is adopted as a tool to estimate the dynamic states that are not directly measured by synchrophasors. The theory and its computational algorithms are illustrated in detail by using a 9-bus 3-generator power system model and then tested on a 140-bus 48-generator Northeast Power Coordinating Council power grid model. Case studies on those two systems demonstrate the performance of the proposed approach using a limited number of synchrophasors for dynamic state estimation for stability assessment and its robustness against moderate inaccuracies in model parameters.


      PubDate: 2016-06-13T05:04:24Z
       
  • Characterization of power systems near their stability boundary using the
           sub-Gramian method
    • Abstract: Publication date: August 2016
      Source:Control Engineering Practice, Volume 53
      Author(s): Igor B. Yadykin, Dmitry E. Kataev, Alexey B. Iskakov, Vladislav K. Shipilov
      There is increasing demand for an effective method to analyze the stability of modern power systems that are nearing their stability boundaries. This demand stems from the burgeoning use of distributed generation and renewable energy sources. We propose a new method that facilitates small-signal stability analysis of power systems, based on the spectral decomposition of a square H 2 norm of the transfer function. Compared with the dynamics of the H 2 and H ∞ norms of the transfer functions, analyzing the behavior of individual eigen-components allows earlier identification of pre-fault conditions. Because each eigen-component is associated with a particular eigenvector, the potential sources of instability can be easily localized and tracked in real time. We analyze an important class of systems operating under pre-fault conditions near the boundary of stability. In such cases, we demonstrate that several weakly stable modes can increase the system energy up to a critical level much earlier, owing to their synergetic effect. In simulation experiments, the proposed method is applied to a stability analysis of an actual power grid on Russky Island, which is connected to an adjacent power grid on the mainland. The simulation results are analyzed and discussed. In particular, in numerical experiments we observe an interaction of weakly stable oscillating modes in the form of low-frequency beating.


      PubDate: 2016-06-13T05:04:24Z
       
  • Model predictive load–frequency control taking into account
           imbalance uncertainty
    • Abstract: Publication date: August 2016
      Source:Control Engineering Practice, Volume 53
      Author(s): Anne Mai Ersdal, Lars Imsland, Kjetil Uhlen, Davide Fabozzi, Nina F. Thornhill
      Nonlinear model predictive control (NMPC) is investigated for load frequency control (LFC) of an interconnected power system which is exposed to increasing wind power penetration. The robustified NMPC (RNMPC) proposed here uses knowledge of the estimated worst-case deviation in wind-power production to make the NMPC more robust. The NMPC is based on a simplified system model that is updated using state- and parameter estimation by Kalman filters, and it takes into account limitations on among others tie-line power flow. Tests on a proxy of the Nordic power system show that the RNMPC is able to fulfill system constraints under worst-case deviations in wind-power production, where the nominal NMPC is not.


      PubDate: 2016-06-13T05:04:24Z
       
  • Fault tolerant emergency control to preserve power system stability
    • Abstract: Publication date: August 2016
      Source:Control Engineering Practice, Volume 53
      Author(s): Andreas S. Pedersen, Jan H. Richter, Mojtaba Tabatabaeipour, Hjörtur Jóhannsson, Mogens Blanke
      This paper introduces a method for fault-masking and system reconfiguration in power transmission systems. The paper demonstrates how faults are handled by reconfiguring remaining controls through utilisation of wide-area measurement in real time. It is shown how reconfiguration can be obtained using a virtual actuator concept, which covers Lure-type systems. The paper shows the steps needed to calculate a virtual actuator, which relies on the solution of a linear matrix inequality. The solution is shown to work with existing controls by adding a compensation signal. Simulation results of a benchmark system show ability of the reconfiguration to maintain stability.


      PubDate: 2016-06-13T05:04:24Z
       
  • Bridging the gap between the linear and nonlinear predictive control:
           Adaptations for efficient building climate control
    • Abstract: Publication date: August 2016
      Source:Control Engineering Practice, Volume 53
      Author(s): Matej Pčolka, Eva Žáčeková, Rush Robinett, Sergej Čelikovský, Michael Šebek
      The linear model predictive control which is frequently used for building climate control benefits from the fact that the resulting optimization task is convex (thus easily and quickly solvable). On the other hand, the nonlinear model predictive control enables the use of a more detailed nonlinear model and it takes advantage of the fact that it addresses the optimization task more directly, however, it requires a more computationally complex algorithm for solving the non-convex optimization problem. In this paper, the gap between the linear and the nonlinear one is bridged by introducing a predictive controller with linear time-dependent model. Making use of linear time-dependent model of the building, the newly proposed controller obtains predictions which are closer to reality than those of linear time invariant model, however, the computational complexity is still kept low since the optimization task remains convex. The concept of linear time-dependent predictive controller is verified on a set of numerical experiments performed using a high fidelity model created in a building simulation environment and compared to the previously mentioned alternatives. Furthermore, the model for the nonlinear variant is identified using an adaptation of the existing model predictive control relevant identification method and the optimization algorithm for the nonlinear predictive controller is adapted such that it can handle also restrictions on discrete-valued nature of the manipulated variables. The presented comparisons show that the current adaptations lead to more efficient building climate control.


      PubDate: 2016-06-13T05:04:24Z
       
  • Model-based motion control for multi-axis servohydraulic shaking tables
    • Abstract: Publication date: August 2016
      Source:Control Engineering Practice, Volume 53
      Author(s): A.R. Plummer
      The shaking table is an essential testing tool in the development of earthquake resistant buildings and infrastructure, so improving its performance is an important contribution to saving lives. Currently the bandwidth and accuracy of shaking tables is such that earthquake motion often cannot be replicated with the desired fidelity. A new model-based motion control method is presented for multi-axis shaking tables. The ability of this method to decouple the control axes is demonstrated. A linear parameter varying modal control approach is used – i.e. the modes of vibration of the system are controlled individually, with the modal decomposition repeated at each time step to account for parameter variations. For each mode, a partial non-linear dynamic inversion is performed in the control loop. Feedback is based on a combination of position and acceleration measurements. A command feedforward method is proposed to increase the tracking bandwidth, thus the controller has a two degree-of-freedom structure. Experimental and simulation results are presented for a large (43t total) six degree-of-freedom shaking table. The simulation results are based on a detailed, validated model of the table. Experimental results show that the controller gives exceptional performance compared a conventional proportional controller: for example the horizontal acceleration bandwidth is six-times higher at over 100Hz, which is also many times higher than the hydraulic resonant frequency. These results will allow a step change in earthquake simulation accuracy.
      Graphical abstract image

      PubDate: 2016-06-13T05:04:24Z
       
  • Data-driven monitoring and validation of experiments on automotive engine
           test beds
    • Abstract: Publication date: September 2016
      Source:Control Engineering Practice, Volume 54
      Author(s): Adel Haghani, Torsten Jeinsch, Mathias Roepke, Steven X. Ding, Nick Weinhold
      Engine test beds are widely used to estimate automotive engine parameters and design controllers in the preliminary development phase. The controller parameters are optimized to fulfill emission, fuel consumption and driving comfort requirements and they will be further validated on chassis dynamometer and road driving experiments. It is common that the results of two experiments deviate, due to some external disturbances or faults. The main purpose of this paper is to demonstrate the application of data-driven fault diagnosis techniques to detect the deviations in the experiments and analyze their root-causes to reduce the costs and time of the engine design and its control concept. To this end, two different methods are introduced for detection of the problems in the experiment. Based on the results of the detection step, a fault isolation technique has been proposed to support test engineers in finding the cause of the deviations. The results have been demonstrated on an industrial engine test bed and the effectiveness of the methods is discussed.


      PubDate: 2016-06-13T05:04:24Z
       
  • Editorial Board
    • Abstract: Publication date: August 2016
      Source:Control Engineering Practice, Volume 53




      PubDate: 2016-06-13T05:04:24Z
       
  • Nonlinear system identification—Application for industrial
           hydro-static drive-line
    • Abstract: Publication date: September 2016
      Source:Control Engineering Practice, Volume 54
      Author(s): Julian Stoev, Johan Schoukens
      The goal of the paper is to describe the added value and complexities of nonlinear system identification applied to a large scale industrial test setup. The additional important insights provided by the frequency domain nonlinear approach are significant and for such systems the nonlinear system identification is important, for example to estimate the noise and non-linearities levels, which can indicate mechanical and configuration issues. It is not the goal to provide a final full-scale model, but to explore what is the applicability of the nonlinear system identification theories for a complex multi-physical non-academic test-case.


      PubDate: 2016-06-13T05:04:24Z
       
  • Control strategies for automatic generation control over MTDC grids
    • Abstract: Publication date: September 2016
      Source:Control Engineering Practice, Volume 54
      Author(s): Paul Mc Namara, Ronan Meere, Terence O'Donnell, Seán McLoone
      Increasingly in power systems, there is a trend towards the sharing of reserves and integration of markets over wide areas in order to enable increased penetration of renewable sources in interconnected power systems. In this paper, a number of simple PI and gain based Model Predictive Control algorithms are proposed for Automatic Generation Control in AC areas connected to Multi-Terminal Direct Current grids. The paper discusses how this approach improves the sharing of secondary reserves and could assist in achieving EU energy targets for 2030 and beyond.


      PubDate: 2016-06-13T05:04:24Z
       
  • Real-time optimization of an industrial steam-methane reformer under
           distributed sensing
    • Abstract: Publication date: September 2016
      Source:Control Engineering Practice, Volume 54
      Author(s): Ankur Kumar, Michael Baldea, Thomas F. Edgar
      Industrial hydrogen production takes place in large-scale steam methane reformer (SMR) units, whose energy efficiency depends on the interior spatial temperature distribution. In this paper, a control-relevant empirical reduced-order SMR model is presented that predicts the furnace temperature distribution based on fuel input to a group of burners. The model is calibrated using distributed temperature measurements from an array of infrared cameras. The model is employed to optimize in real-time the temperature distribution and increase the energy efficiency in an industrial furnace. Experimental results confirm that the proposed framework has excellent performance.


      PubDate: 2016-06-13T05:04:24Z
       
  • Distributed identification and control of spatially interconnected systems
           with application to an actuated beam
    • Abstract: Publication date: September 2016
      Source:Control Engineering Practice, Volume 54
      Author(s): Qin Liu, Herbert Werner
      This paper presents a case study on modelling and control of spatially interconnected systems. Considered is a vibration control problem, with experimental results on a flexible beam that is equipped with an array of piezo sensors and actuators. The sensor–actuator array induces a spatial discretization of the beam into an array of interconnected subsystems. Models are experimentally identified that have the structure of spatially interconnected systems. Based on the identified models, distributed control schemes are designed by solving a linear matrix inequality (LMI) problem that has the size of a single subsystem. Modelling and control is considered for both spatially invariant and spatially varying systems; in the latter case the system is represented as linear parameter-varying (LPV) system that is scheduled not over time but over space. Simulation and experimental closed-loop results demonstrate the practicality and efficiency of the underlying framework.


      PubDate: 2016-06-13T05:04:24Z
       
  • Modeling and optimization method featuring multiple operating modes for
           improving carbon efficiency of iron ore sintering process
    • Abstract: Publication date: September 2016
      Source:Control Engineering Practice, Volume 54
      Author(s): Xin Chen, Xiaoxia Chen, Min Wu, Jinhua She
      Iron ore sintering is one of the most energy-consuming processes in steelmaking. Since its main source of energy is the combustion of carbon, it is important to improve the carbon efficiency to save energy and to reduce undesired emissions. A modeling and optimization method based on the characteristics of the sintering process has been developed to do that. It features multiple operating modes and employs the comprehensive carbon ratio (CCR) as a measure of carbon efficiency. The method has two parts. The first part is the modeling of multiple operating modes of the sintering process. K-means clustering is used to identify the operating modes; and for each mode, a predictive model is built that contains two submodels, one for predicting the state parameters and one for predicting the CCR. The submodels are built using back-propagation neural networks (BPNNs). An analysis of material and energy flow, and correlation analyses of process data and the CCR, are used to determine the most appropriate inputs for the submodels. The second part of the method is optimization based on a determination of the optimal operating mode. The problem of how to reduce the CCR is formulated as a two-step optimization problem, and particle swarm optimization is used to solve it. Finally, verification of the modeling and optimization method based on actual process data shows that it improves the carbon efficiency of iron ore sintering.


      PubDate: 2016-06-13T05:04:24Z
       
  • Day-ahead economic optimization of energy use in an olive mill
    • Abstract: Publication date: September 2016
      Source:Control Engineering Practice, Volume 54
      Author(s): Pablo Báez-González, Alejandro J. del Real, Miguel A. Ridao Carlini, Carlos Bordons
      This article presents an economic case study on biomass and power dispatch focused on the olive oil extraction industry. A method is proposed to minimize the energy cost associated to olive oil production. This is realized through load shaping and optimal selection of the destination of subproducts and wastes. The mill and the loads linked to the extraction process are modeled using the energy hub concept, and an Economic Model Predictive Control (EMPC) based power and biomass dispatcher is introduced. The control strategy has been simulated over different scenarios to validate the optimization scheme.


      PubDate: 2016-06-13T05:04:24Z
       
  • Canonical variate analysis for performance degradation under faulty
           conditions
    • Abstract: Publication date: September 2016
      Source:Control Engineering Practice, Volume 54
      Author(s): C. Ruiz-Cárcel, L. Lao, Y. Cao, D. Mba
      Condition monitoring of industrial processes can minimize maintenance and operating costs while increasing the process safety and enhancing the quality of the product. In order to achieve these goals it is necessary not only to detect and diagnose process faults, but also to react to them by scheduling the maintenance and production according to the condition of the process. The objective of this investigation is to test the capabilities of canonical variate analysis (CVA) to estimate performance degradation and predict the behavior of a system affected by faults. Process data was acquired from a large-scale experimental multiphase flow facility operated under changing operational conditions where process faults were seeded. The results suggest that CVA can be used effectively to evaluate how faults affect the process variables in comparison to normal operation. The method also predicted future process behavior after the appearance of faults, modeling the system using data collected during the early stages of degradation.


      PubDate: 2016-06-13T05:04:24Z
       
  • An adaptive sliding mode observer for lithium-ion battery state of charge
           and state of health estimation in electric vehicles
    • Abstract: Publication date: September 2016
      Source:Control Engineering Practice, Volume 54
      Author(s): Jiani Du, Zhitao Liu, Youyi Wang, Changyun Wen
      As the demand for electric vehicle (EV)'s remaining operation range and power supply life, Lithium-ion (Li-ion) battery state of charge (SOC) and state of health (SOH) estimation are important in battery management system (BMS). In this paper, a proposed adaptive observer based on sliding mode method is used to estimate SOC and SOH of the Li-ion battery. An equivalent circuit model with two resistor and capacitor (RC) networks is established, and the model equations in specific structure with uncertainties are given and analyzed. The proposed adaptive sliding mode observer is applied to estimate SOC and SOH based on the established battery model with uncertainties, and it can avoid the chattering effects and improve the estimation performance. The experiment and simulation estimation results show that the proposed adaptive sliding mode observer has good performance and robustness on battery SOC and SOH estimation.


      PubDate: 2016-06-13T05:04:24Z
       
  • Predictive iterative learning control with experimental validation
    • Abstract: Publication date: August 2016
      Source:Control Engineering Practice, Volume 53
      Author(s): Liuping Wang, Chris T. Freeman, Eric Rogers
      This paper develops an iterative learning control law that exploits recent results in the area of predictive repetitive control where a priori information about the characteristics of the reference signal is embedded in the control law using the internal model principle. The control law is based on receding horizon control and Laguerre functions can be used to parameterize the future control trajectory if required. Error convergence of the resulting controlled system is analyzed. To evaluate the performance of the design, including comparative aspects, simulation results from a chemical process control problem and supporting experimental results from application to a robot with two inputs and two outputs are given.


      PubDate: 2016-05-14T12:24:30Z
       
  • Data-driven Fault Detection and Diagnosis for HVAC water chillers
    • Abstract: Publication date: August 2016
      Source:Control Engineering Practice, Volume 53
      Author(s): A. Beghi, R. Brignoli, L. Cecchinato, G. Menegazzo, M. Rampazzo, F. Simmini
      Faulty operations of Heating, Ventilation and Air Conditioning (HVAC) chiller systems can lead to discomfort for the users, energy wastage, system unreliability and shorter equipment life. Faults need to be early diagnosed to prevent further deterioration of the system behaviour and energy losses. Since it is not a common practice to collect historical data regarding unforeseen phenomena and abnormal behaviours for HVAC installations, in this paper, a semi-supervised data-driven approach is employed for fault detection and isolation that makes no use of a priori knowledge about abnormal phenomena. The proposed method exploits Principal Component Analysis (PCA) to distinguish anomalies from normal operation variability and a reconstruction-based contribution approach to isolate variables related to faults. The diagnosis task is then tackled by means of a decision table that associates the influence of faults to certain characteristic features. The Fault Detection and Diagnosis (FDD) algorithm performance is assessed by exploiting experimental datasets from two types of water chiller systems.


      PubDate: 2016-05-14T12:24:30Z
       
  • Current-sensor fault detection and isolation for induction-motor drives
           using a geometric approach
    • Abstract: Publication date: August 2016
      Source:Control Engineering Practice, Volume 53
      Author(s): F. Aguilera, P.M. de la Barrera, C.H. De Angelo, D.R. Espinoza Trejo
      This work presents the design of a current-sensor fault detection and isolation system for induction-motor drives. A differential geometric approach is addressed to determine if faults can be detected and isolated in drives with two line current sensors by using a model based strategy. A set of subsystems is obtained based on the observability co-distribution, whose outputs are decoupled from the load torque (detectability) and only affected by one of the sensors (isolability). A bank of observers is designed for these subsystems in order to obtain residuals for the fault detection and isolation. It is demonstrated that the proposed strategy allows detecting single and multiple sensor faults, including disconnection, offset and gain faults. Experimental results validate the proposal.


      PubDate: 2016-05-14T12:24:30Z
       
  • A compound control method for the rejection of spatially periodic and
           uncertain disturbances of rotary machines and its implementation under
           uniform time sampling
    • Abstract: Publication date: August 2016
      Source:Control Engineering Practice, Volume 53
      Author(s): Xin Huo, Xin-Gang Tong, Kang-Zhi Liu, Ke-Mao Ma
      In this paper, a compound control which combines a spatial internal model with a linear extended state observer (LESO) is proposed for continuously rotating machines. It is implemented digitally based on a uniform time sampling. An angular position-based internal model is synthesized in the spatial domain to suppress the spatially periodic disturbances existing in rotary machines, which is actuated with a fixed sampling period by introducing the angular position to the internal model in real-time. Further, an LESO is designed to estimate non-periodic disturbances and uncertain dynamics acting on the system so as to reduce the steady state error of the position output with respect to ramp angular position reference input. Comparisons and experimental results are presented to illustrate the feasibility and effectiveness of the compound control method.


      PubDate: 2016-05-14T12:24:30Z
       
  • New enhanced performance robust control design scheme for grid-connected
           VSI
    • Abstract: Publication date: August 2016
      Source:Control Engineering Practice, Volume 53
      Author(s): Asim H. Syed, M.A. Abido
      In this paper, a new method for intelligent robust control design is presented that achieves the best possible convergence rate of the system, utilizing the knowledge on the range of uncertain parameter. Thus resulting in enhanced stability and performance. The proposed method is applied to the grid-connected voltage source inverter (VSI) system with uncertainties in grid-impedance. Simulation and experimental results illustrate the efficacy of the proposed scheme. Comparison with existing methods shows that the proposed scheme can provide better reference tracking, stability for a wider uncertainty range, and improved transient and steady-state performance with low implementation cost.


      PubDate: 2016-05-14T12:24:30Z
       
  • Experimentally verified generalized KYP Lemma based iterative learning
           control design
    • Abstract: Publication date: August 2016
      Source:Control Engineering Practice, Volume 53
      Author(s): Wojciech Paszke, Eric Rogers, Krzysztof Gałkowski
      This paper considers iterative learning control law design for plants modeled by discrete linear dynamics using repetitive process stability theory. The resulting one step linear matrix inequality based design produces a stabilizing feedback controller in the time domain and a feedforward controller that guarantees convergence in the trial-to-trial domain. Additionally, application of the generalized Kalman–Yakubovich–Popov (KYP) lemma allows a direct treatment of differing finite frequency range performance specifications. The results are also extended to plants with relative degree greater than unity. To support the algorithm development, the results from an experimental implementation are given, where the performance requirements include specifications over various finite frequency ranges.


      PubDate: 2016-05-14T12:24:30Z
       
  • Fractional attitude-reactive control for robust quadrotor position
           stabilization without resolving underactuation
    • Abstract: Publication date: August 2016
      Source:Control Engineering Practice, Volume 53
      Author(s): C. Izaguirre-Espinosa, A.J. Muñoz-Vázquez, A. Sánchez-Orta, V. Parra-Vega, G. Sanahuja
      Quadrotors are Unmanned Aerial Systems (UAS), whose nonlinearities, uncertainties, and unavoidable aerodynamic disturbances stand for a difficult control problem. Additionally, the highly nonlinear coupling between the position and the orientation dynamics exacerbates the underactuation problem when the objective is the position tracking. In this paper, aiming at designing a robust position controller without resolving underactuation, a novel “reactive orientation control” is proposed. The orientation controller is model-free and it is build upon differintegral fractional operators to react to a continuous and bounded additive term that stands for an affine exogenous position controller. Such term indeed becomes an attitude disturbance that is purposely injected to displace the quadrotor towards the desired position of the underactuated coordinates. The closed-loop analysis shows that the norm of the transfer function between the disturbance and the position tracking error is minimized for a stable and robust position regime. Simulations and experimental results are given to discuss the feasibility of the proposed scheme.


      PubDate: 2016-05-14T12:24:30Z
       
  • Model predictive control of reactive distillation for benzene
           hydrogenation
    • Abstract: Publication date: July 2016
      Source:Control Engineering Practice, Volume 52
      Author(s): Vishal Mahindrakar, Juergen Hahn
      Benzene hydrogenation via reactive distillation is a process that has been widely adopted in the process industry. However, studies in the open literature on control of this process are rare and seem to indicate that conventional decentralized PI control results in sluggish responses when the reactive distillation column is subjected to disturbances in the feed concentration. In order to overcome this performance limitation, this work investigates model predictive control (MPC) strategies of a reactive distillation column model, which has been implemented in gPROMS. Several MPCs based upon different sets of manipulated and controlled variables are investigated where the remaining variables remain under regular feedback control. Further, MPC controllers with output disturbance correction and, separately, with input disturbance correction have been investigated. The results show that the settling time of the column can be reduced and the closed loop dynamics significantly improved for the system under MPC control compared to a decentralized PI control structure.


      PubDate: 2016-05-08T14:19:06Z
       
  • Hybrid approach to casual analysis on a complex industrial system based on
           transfer entropy in conjunction with process connectivity information
    • Abstract: Publication date: August 2016
      Source:Control Engineering Practice, Volume 53
      Author(s): R. Landman, S.-L. Jämsä-Jounela
      Industrial processes often encounter disturbances that propagate through the process units and their control elements, leading to poor process performance and massive economic losses. Thus, one major concern in the chemical industry is the detection of disturbances and identification of their propagation path. Causal analysis based on process data is frequently applied to identify causal dependencies among process measurements and thereby obtain the propagation path of disturbances. One significant challenge in data-based causal analysis is investigating industrial systems with a high degree of connectivity due to multiple causal pathways. This paper proposes a new hybrid approach for detecting causality based on the transfer entropy (TE) method by incorporating process connectivity information using an explicit search algorithm. Based on the hybrid approach, initially, the TE is only calculated for pathways that are considered as direct pathways based on the process topology. Then, the direct transfer entropy (DTE) is employed to discriminate spurious and/or indirect pathways obtained by the initial TE results. To facilitate the DTE calculation, the search algorithm is invoked once again to extract the intermediate pathways. This concept is demonstrated on an industrial board machine. In particular, the propagation path of an oscillation due to valve stiction within multiple control loops in the drying section of the machine is studied. Finally, the results are discussed and evaluated.


      PubDate: 2016-05-03T14:14:10Z
       
  • 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
       
  • 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
       
  • 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
       
  • 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
       
 
 
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