Dynamic output feedback robust MPC for LPV systems subject to input saturation and bounded disturbance

For linear parameter varying (LPV) systems with unknown scheduling parameters and bounded disturbance, a synthesis approach of dynamic output feedback robust model predictive control (OFRMPC) with input saturation is investigated. By pre-specifying partial controller parameters, a main optimization problem is solved by convex optimization to reduce the on-line computational burden. The main optimization problem guarantees that the estimated state and estimation error converge within the corresponding invariant sets such that recursive feasibility and robust stability are guaranteed. The consideration of input saturation in the main optimization problem improves the control performance. Two numerical examples are given to illustrate the effectiveness of the approach.

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

[2]  PooGyeon Park,et al.  State‐feedback disturbance attenuation for polytopic LPV systems with input saturation , 2009 .

[3]  R. Braatz,et al.  A tutorial on linear and bilinear matrix inequalities , 2000 .

[4]  Michael Nikolaou,et al.  MPC: Current practice and challenges , 2009 .

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

[6]  Pornchai Bumroongsri,et al.  Tube-based robust MPC for linear time-varying systems with bounded disturbances , 2015 .

[7]  Zongli Lin,et al.  Output Feedback Stabilization of Linear Systems With Actuator Saturation , 2007, IEEE Transactions on Automatic Control.

[8]  Giorgio Battistelli,et al.  Design of state estimators for uncertain linear systems using quadratic boundedness , 2006, Autom..

[9]  Arkadi Nemirovski,et al.  Lmi Control Toolbox For Use With Matlab , 2014 .

[10]  Fen Wu,et al.  Output feedback control of saturated discrete-time linear systems using parameter-dependent Lyapunov functions , 2008, Syst. Control. Lett..

[11]  Baocang Ding,et al.  A synthesis approach for output feedback robust constrained model predictive control , 2008, Autom..

[12]  S. Joe Qin,et al.  A survey of industrial model predictive control technology , 2003 .

[13]  Mayuresh V. Kothare,et al.  Robust output feedback model predictive control using off-line linear matrix inequalities , 2002 .

[14]  Ping Xu,et al.  Dynamic Output Feedback Robust Model Predictive Control Based on Ellipsoidal Estimation Error Bound , 2014 .

[15]  Zongli Lin,et al.  Min-max MPC algorithm for LPV systems subject to input saturation , 2005 .

[16]  O. Toker,et al.  On the NP-hardness of solving bilinear matrix inequalities and simultaneous stabilization with static output feedback , 1995, Proceedings of 1995 American Control Conference - ACC'95.

[17]  He Huang,et al.  An improved robust model predictive control design in the presence of actuator saturation , 2011, Autom..

[18]  David Q. Mayne,et al.  Constrained model predictive control: Stability and optimality , 2000, Autom..

[19]  Michel Verhaegen,et al.  Robust output-feedback controller design via local BMI optimization , 2004, Autom..

[20]  Baocang Ding,et al.  On dynamic output feedback robust MPC for constrained quasi-LPV systems , 2013, Int. J. Control.

[21]  Baocang Ding,et al.  Output Feedback Predictive Control With One Free Control Move for Nonlinear Systems Represented by a Takagi–Sugeno Model , 2014, IEEE Transactions on Fuzzy Systems.

[22]  Tingshu Hu,et al.  Analysis and design for discrete-time linear systems subject to actuator saturation , 2002, Syst. Control. Lett..

[23]  L. Ghaoui,et al.  A cone complementarity linearization algorithm for static output-feedback and related problems , 1997, IEEE Trans. Autom. Control..

[24]  Antonio Sala,et al.  Asymptotically necessary and sufficient conditions for stability and performance in fuzzy control: Applications of Polya's theorem , 2007, Fuzzy Sets Syst..

[25]  Baocang Ding,et al.  Dynamic output feedback MPC for LPV systems via near-optimal solutions , 2011, Proceedings of the 30th Chinese Control Conference.

[26]  Giorgio Battistelli,et al.  On estimation error bounds for receding-horizon filters using quadratic boundedness , 2004, IEEE Transactions on Automatic Control.

[27]  Baocang Ding,et al.  Dynamic Output Feedback Predictive Control for Nonlinear Systems Represented by a Takagi–Sugeno Model , 2011, IEEE Transactions on Fuzzy Systems.