Robust model predictive control under redundant channel transmission with applications in networked DC motor systems

Summary In networked systems, intermittent failures in data transmission are usually inevitable due to the limited bandwidth of the communication channel, and an effective countermeasure is to add redundance so as to improve the reliability of the communication service. This paper is concerned with the model predictive control (MPC) problem by using static output feedback for a class of polytopic uncertain systems with redundant channels under both input and output constraints. By utilizing the min–max control approach combined with stochastic analysis, sufficient conditions are established to guarantee the feasibility of the designed MPC scheme that ensures the robust stability of the closed-loop system. In terms of the solution to an auxiliary optimization problem, an easy-to-implement MPC algorithm is proposed to obtain the desired sub-optimal control sequence as well as the upper bound of the quadratic cost function. Finally, to illustrate its effectiveness, the proposed design method is applied to control a networked direct current motor system. Copyright © 2016 John Wiley & Sons, Ltd.

[1]  Hongye Su,et al.  Stability analysis and controller synthesis for discrete linear time-delay systems with state saturation nonlinearities , 2011, Int. J. Syst. Sci..

[2]  Mohamed-Slim Alouini,et al.  Spectral Efficiency Enhancement in Multi-Channel Systems Using Redundant Transmission and Diversity Reception , 2008, IEEE Transactions on Wireless Communications.

[3]  Massimo Canale,et al.  Nonlinear model predictive control from data: a set membership approach , 2014 .

[4]  João Pedro Hespanha,et al.  Redundant data transmission in control/estimation over lossy networks , 2012, Autom..

[5]  Huiping Li,et al.  Event-triggered robust model predictive control of continuous-time nonlinear systems , 2014, Autom..

[6]  Huiping Li,et al.  Robust Distributed Model Predictive Control of Constrained Continuous-Time Nonlinear Systems: A Robustness Constraint Approach , 2014, IEEE Transactions on Automatic Control.

[7]  Dimos V. Dimarogonas,et al.  Event-triggered control for discrete-time systems , 2010, Proceedings of the 2010 American Control Conference.

[8]  Nicola Elia,et al.  Model Predictive Control-Based Real-Time Power System Protection Schemes , 2010, IEEE Transactions on Power Systems.

[9]  David Q. Mayne,et al.  Model predictive control: Recent developments and future promise , 2014, Autom..

[10]  M. Zima,et al.  Model Predictive Control Employing Trajectory Sensitivities for Power Systems Applications , 2005, Proceedings of the 44th IEEE Conference on Decision and Control.

[11]  Zidong Wang,et al.  $H_{\infty}$ State Estimation for Discrete-Time Complex Networks With Randomly Occurring Sensor Saturations and Randomly Varying Sensor Delays , 2012, IEEE Transactions on Neural Networks and Learning Systems.

[12]  Dewei Li,et al.  Synthesis of dynamic output feedback RMPC with saturated inputs , 2013, Autom..

[13]  Zidong Wang,et al.  Recent advances on distributed filtering for stochastic systems over sensor networks , 2014, Int. J. Gen. Syst..

[14]  B. Ding,et al.  Constrained robust model predictive control via parameter-dependent dynamic output feedback , 2010, Autom..

[15]  Derui Ding,et al.  Event-triggered consensus control for discrete-time stochastic multi-agent systems: The input-to-state stability in probability , 2015, Autom..

[16]  Dewei Li,et al.  Constrained model predictive control synthesis for uncertain discrete-time Markovian jump linear systems , 2013 .

[17]  Daniel W. C. Ho,et al.  Robust ${\cal H}_{\infty}$ Finite-Horizon Control for a Class of Stochastic Nonlinear Time-Varying Systems Subject to Sensor and Actuator Saturations , 2010, IEEE Transactions on Automatic Control.

[18]  Xiang Li,et al.  Nonlinear model predictive control for path following problems , 2015 .

[19]  Robert S. Balog,et al.  Model Predictive Control of PV Sources in a Smart DC Distribution System: Maximum Power Point Tracking and Droop Control , 2014, IEEE Transactions on Energy Conversion.

[20]  Fuad E. Alsaadi,et al.  Event-triggered robust distributed state estimation for sensor networks with state-dependent noises , 2015, Int. J. Gen. Syst..

[21]  Zilong Zou,et al.  An Approach of Reliable Data Transmission With Random Redundancy for Wireless Sensors in Structural Health Monitoring , 2015, IEEE Sensors Journal.

[22]  Guo-Ping Liu,et al.  Predictive Output Feedback Control for Networked Control Systems , 2014, IEEE Transactions on Industrial Electronics.

[23]  Vijay Vittal,et al.  Wide-Area Control Resiliency Using Redundant Communication Paths , 2014, IEEE Transactions on Power Systems.

[24]  Li-Sheng Hu,et al.  Robust digital model predictive control for linear uncertain systems with saturations , 2004, IEEE Transactions on Automatic Control.

[25]  Fuwen Yang,et al.  H∞ control for networked systems with random communication delays , 2006, IEEE Trans. Autom. Control..

[26]  Chuang Li,et al.  Distributed model predictive control for polytopic uncertain systems subject to actuator saturation , 2013 .

[27]  Fuad E. Alsaadi,et al.  Receding horizon filtering for a class of discrete time-varying nonlinear systems with multiple missing measurements , 2015, Int. J. Gen. Syst..

[28]  M. Larrson,et al.  Coordinated System Protection Scheme against Voltage Collapse Using Heuristic Search and Predictive Control , 2002, IEEE Power Engineering Review.

[29]  Mo-Yuen Chow,et al.  Gain adaptation of networked DC motor controllers based on QoS variations , 2003, IEEE Trans. Ind. Electron..

[30]  Manfred Morari,et al.  Robust constrained model predictive control using linear matrix inequalities , 1994, Proceedings of 1994 American Control Conference - ACC '94.