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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  [2969 journals]
  • Control-oriented modeling and analysis of direct energy balance in
           coal-fired boiler-turbine unit
    • Abstract: Publication date: October 2016
      Source:Control Engineering Practice, Volume 55
      Author(s): Li Sun, Donghai Li, Kwang Y. Lee, Yali Xue
      Direct energy balance (DEB) coordinated control scheme is widely used by field engineers in coal-fired power plants while attracting little attention in the academic community. This paper aims to derive a mathematical model that is suitable for DEB research. To balance the model’s fidelity and simplicity, the power plant is divided into three transformation modules and, using conservation laws, a dynamic model is developed to describe each module. Within reasonable assumptions, numerous module equations are combined to yield a 6th-order nonlinear model. Time constants of the model are identified based on Pareto optimization. Model accuracy is confirmed using field measurements from a 300 MW coal-fired power plant. Based on the linearized model, the merits of the DEB control structure are analyzed. It is confirmed that the DEB control is sufficient to fulfill the fundamental goals of power plant regulation. An illustration of performance improvement is given by introducing gain scheduling techniques to the DEB structure. The proposed model can provide groundwork for future development of advanced control algorithms under the DEB structure.


      PubDate: 2016-07-18T07:51:24Z
       
  • Multi-objective voltage and frequency regulation in autonomous microgrids
           using Pareto-based Big Bang-Big Crunch algorithm
    • Abstract: Publication date: October 2016
      Source:Control Engineering Practice, Volume 55
      Author(s): Amir Eisapour Moarref, Mostafa Sedighizadeh, Masoud Esmaili
      Voltage and frequency regulation is one of the most vital issues in autonomous microgrids to ensure an acceptable electric power quality supply to customers. In this paper, a real-time control structure including power, voltage, and current control loops is proposed for microgrid inverters to restore voltage and frequency of the system after the initiation and load changes. The Proportional-Integral (PI) gains of the voltage controller are optimized in a real-time basis after a perturbation in the microgrid to have a fast and smooth response and a more stable system. The current controller produces Space Vector Pulse Width Modulation command signals to be fed into the three-leg inverter. The multi-objective optimization problem has objective functions of voltage overshoot/undershoot, rise time, settling time, and Integral Time Absolute Error (ITAE). The modified Multi-Objective Hybrid Big Bang-Bing Crunch (MOHBB-BC) algorithm is employed as one of efficient evolutionary algorithms in order to solve the optimization problem. The MOHBB-BC method obtains a set of Pareto optimal solutions; a fuzzy decision maker is used to pick up the most preferred Pareto solution as the final solution of the problem. Results from testing the control strategy on a case study are discussed and compared with previous works; according to them, the proposed method is able to obtain dynamic PI regulator gains to have a more appropriate response.


      PubDate: 2016-07-18T07:51:24Z
       
  • Nonlinear robust observer design using an invariant manifold approach
    • Abstract: Publication date: October 2016
      Source:Control Engineering Practice, Volume 55
      Author(s): Irfan Ullah Khan, David Wagg, Neil D. Sims
      This paper presents a method to design a reduced order observer using an invariant manifold approach. The main advantages of this method are that it enables a systematic design approach, and (unlike most nonlinear observer design methods), it can be generalized over a larger class of nonlinear systems. The method uses specific mapping functions in a way that minimizes the error dynamics close to zero. Another important aspect is the robustness property which is due to the manifold attractivity: an important feature when an observer is used in a closed loop control system. A two degree-of-freedom system is used as an example. The observer design is validated using numerical simulation. Then experimental validation is carried out using hardware-in-the-loop testing. The proposed observer is then compared with a very well known nonlinear observer based on the off-line solution of the Riccati equation for systems with Lipschitz type nonlinearity. In all cases, the performance of the proposed observer is shown to be very high.


      PubDate: 2016-07-18T07:51:24Z
       
  • Robust tuning for machine-directional predictive control of MIMO
           paper-making processes
    • Abstract: Publication date: October 2016
      Source:Control Engineering Practice, Volume 55
      Author(s): Ning He, Dawei Shi, Michael Forbes, Johan Backström, Tongwen Chen
      This paper solves the controller tuning problem of machine-directional predictive control for multiple-input–multiple-output (MIMO) paper-making processes represented as superposition of first-order-plus-dead-time (FOPDT) components with uncertain model parameters. A user-friendly multi-variable tuning problem is formulated based on user-specified time domain specifications and then simplified based on the structure of the closed-loop system. Based on the simplified tuning problem and a proposed performance evaluation technique, a fast multi-variable tuning technique is developed by ignoring the constraints of the MPC. In addition, a technique to predict the computation time of the tuning algorithm is proposed. The efficiency of the proposed method is verified through Honeywell real time simulator platform with a MIMO paper-making process obtained from real data from an industrial site.


      PubDate: 2016-07-13T20:33:11Z
       
  • An experimental investigation of additional actuators on a submarine
           diesel generator
    • Abstract: Publication date: October 2016
      Source:Control Engineering Practice, Volume 55
      Author(s): Timothy Broomhead, Chris Manzie, Peter Hield, Michael Brear
      Additional actuators and active generator load control have been suggested to improve performance on submarine diesel generators. Until recently, a lack of systematic control design has limited the ability to thoroughly investigate their potential. In this paper, model predictive control is used to produce near-optimal actuator commands for an experimental diesel generator on a test bed capable of producing representative submarine operating conditions. The performance with different actuator subsets is compared against an existing speed governor control architecture over a range of operating conditions. It is demonstrated that a minimum of two actuators may substantially improve generator performance. The study also investigates how model predictive control, when combined with additional actuators, can be used to enforce appropriate operational constraints that may lead to better longevity of the generator.


      PubDate: 2016-07-13T20:33:11Z
       
  • Regulation of lactic acid concentration in its bioproduction from wheat
           flour
    • Abstract: Publication date: September 2016
      Source:Control Engineering Practice, Volume 54
      Author(s): Karen Gonzalez, Sihem Tebbani, Filipa Lopes, Aurore Thorigné, Sébastien Givry, Didier Dumur, Dominique Pareau
      Lactic acid is an important molecule for biopolymer production that can be obtained by biological processes. This work deals with the control of the lactic acid concentration in its production bioprocess using wheat flour as substrate. An adaptive control strategy for the simultaneous saccharification, proteins hydrolysis and fermentation (SSPHF) continuous process of lactic acid production is proposed in order to regulate the lactic acid concentration to the target value. The latter is determined so that the lactic acid productivity is maximized. The control strategy effectiveness and robustness are illustrated by means of experimental results.


      PubDate: 2016-07-13T20:33:11Z
       
  • A local alignment approach to similarity analysis of industrial alarm
           flood sequences
    • Abstract: Publication date: October 2016
      Source:Control Engineering Practice, Volume 55
      Author(s): Wenkai Hu, Jiandong Wang, Tongwen Chen
      Similar alarm sequence alignment algorithms have been used to find similar alarm floods in the historical database for the prediction and prevention of alarm floods. However, the existing modified Smith–Waterman (SW) algorithm has a high computation complexity, preventing its online applications within a tolerable computation time period. This paper proposes a new local alignment algorithm, based on the basic local alignment search tool (BLAST). The novelty of the proposed algorithm is three-fold. First, a priority-based similarity scoring strategy makes the proposed algorithm more sensitive to alarms having higher alarm priorities. Second, a set-based pre-matching mechanism avoids unnecessary computations by excluding all irrelevant alarm floods and alarm tags. Third, the seeding and extending steps of the conventional BLAST are adapted for alarm floods, which reduce the searching space significantly. Owing to the novelties, the proposed algorithm is much faster in computation and provides a higher alignment accuracy than the SW algorithm. The efficiency of the proposed algorithm is demonstrated by industrial case studies based on the historical alarm floods from an oil conversion plant.


      PubDate: 2016-07-13T20:33:11Z
       
  • Integrated stability and traction control for electric vehicles using
           model predictive control
    • Abstract: Publication date: September 2016
      Source:Control Engineering Practice, Volume 54
      Author(s): Milad Jalali, Amir Khajepour, Shih-ken Chen, Bakhtiar Litkouhi
      In this paper, an integrated vehicle and wheel stability control is developed and experimentally evaluated. The integrated structure provides a more accurate solution as the output of the stability controller is not altered by a separate unit, therefore its optimality is not compromised. Model predictive control is used to find the optimal control actions. The proposed control scheme can be applied to a wide variety of vehicle driveline and actuation configurations such as: four, front and rear wheel drive systems. Computer simulations as well as experiments are provided to show the effectiveness of the proposed control algorithm.


      PubDate: 2016-07-13T20:33:11Z
       
  • Hierarchical control for microalgae biomass production in
           photobiorreactors
    • Abstract: Publication date: September 2016
      Source:Control Engineering Practice, Volume 54
      Author(s): I. Fernández, M. Berenguel, J.L. Guzmán, F.G. Acién, G.A. de Andrade, D.J. Pagano
      This paper addresses the development of a hierarchical control strategy for microalgal production in a tubular photobioreactor. The proposed control scheme is composed of two layers. On one hand, a lower layer is in charge of tracking a pH set-point by a PI controller plus feedforward compensator, which was used due to its recognized efficiency in industrial control processes. On the other hand, the upper layer calculates optimal pH set-points based on an economic model predictive control approach. The main aim of this control scheme is to maximize profits, computed as the difference between the incomes obtained from the final production sale and the associated production costs (including the environmental impact of the exhausted CO2 losses). For this purpose, two types of models have been used depending on the requirements of each layer. Simulated and experimental results of the proposed hierarchical control architecture are presented, as well as a comparison with a single-layer architecture with constant reference implemented by the controller used in the lower layer of the hierarchical structure.


      PubDate: 2016-07-13T20:33:11Z
       
  • Asymmetric relay autotuning – Practical features for industrial use
    • Abstract: Publication date: September 2016
      Source:Control Engineering Practice, Volume 54
      Author(s): Josefin Berner, Tore Hägglund, Karl Johan Åström
      The relay autotuner provides a simple way of finding PID controller parameters. Even though relay autotuning is much investigated in the literature, the practical aspects are not that well-documented. In this paper an asymmetric relay autotuner with features such as a startup procedure and adaptive relay amplitudes is proposed. Parameter choices and handling of noise, disturbances, start in non-steady state and other possible error sources are discussed. The autotuner is implemented and tested on an industrial air handling unit to show its use in practice. The experiments show good results, and prove that the proposed simple autotuner is well-suited for industrial use. But the experiments also enlighten possible error sources and remaining problems.


      PubDate: 2016-07-13T20:33:11Z
       
  • OWave control chart for monitoring the process mean
    • Abstract: Publication date: September 2016
      Source:Control Engineering Practice, Volume 54
      Author(s): Achraf Cohen, Teodor Tiplica, Abdessamad Kobi
      In this paper a control chart for monitoring the process mean, called OWave (Orthogonal Wavelets), is proposed. The statistic that is plotted in the proposed control chart is based on weighted wavelets coefficients, which are provided through the Discrete Wavelets Transform using Daubechies db 2 wavelets family. The statistical behavior of the wavelets coefficients when the mean shifts are occurring is presented, and the distribution of wavelets coefficients in the case of normality and independence assumptions is provided. The on-line algorithm of implementing the proposed method is also provided. The detection performance is based on simulation studies, and the comparison result shows that OWave control chart performs slightly better than Fixed Sample Size and Sampling Intervals control charts ( X ¯ , EWMA, CUSUM) in terms of Average Run Length. In addition, illustrative examples of the new control chart are presented, and an application to Tennessee Eastman Process is also proposed.


      PubDate: 2016-07-13T20:33:11Z
       
  • A systematic approach for robust repetitive controller design
    • Abstract: Publication date: September 2016
      Source:Control Engineering Practice, Volume 54
      Author(s): Jeferson V. Flores, Luis Fernando A. Pereira, Guilherme Bonan, Daniel F. Coutinho, João Manoel Gomes da Silva
      In this paper, a methodology for the synthesis of repetitive controllers to ensure periodic reference tracking and harmonic disturbance rejection is cast in a robust control framework. Specifically, the Lyapunov–Krasovskii theory is applied to derive LMI-based conditions for designing a state feedback control law with guaranteed stability and performance properties for system parameter variations. Practical experiments in commercial uninterruptible power supplies – UPS are considered to illustrate and discuss some practical implementation aspects of the proposed method.


      PubDate: 2016-07-13T20:33:11Z
       
  • 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
       
  • 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
       
  • 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
       
  • 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
       
  • 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
       
  • 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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