Model Predictive Control of Linear Parameter Varying Systems Based on a Recurrent Neural Network

This paper presents a model predictive control approach to discrete-time linear parameter varying systems based on a recurrent neural network. The model predictive control problem is formulated as a sequential convex optimization, and it is solved by using a recurrent neural network in real time. The essence of the proposed approach lies in its real-time computational capability with extended applicability. Simulation results are provided to substantiate the effectiveness of the proposed model predictive control approach.

[1]  Yaman Arkun,et al.  Quasi-Min-Max MPC algorithms for LPV systems , 2000, Autom..

[2]  Thomas Parisini,et al.  A receding-horizon regulator for nonlinear systems and a neural approximation , 1995, Autom..

[3]  Soorathep Kheawhom,et al.  An ellipsoidal off-line model predictive control strategy for linear parameter varying systems with applications in chemical processes , 2012, Syst. Control. Lett..

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

[5]  Zheng Yan,et al.  Model Predictive Control for Tracking of Underactuated Vessels Based on Recurrent Neural Networks , 2012, IEEE Journal of Oceanic Engineering.

[6]  Derong Liu.  Editorial: The Blossoming of the IEEE Transactions on Neural Networks , 2011, IEEE Trans. Neural Networks.

[7]  Long Cheng,et al.  Constrained multi-variable generalized predictive control using a dual neural network , 2007, Neural Computing and Applications.

[8]  Bassam Bamieh,et al.  Identification of linear parameter varying models , 2002 .

[9]  Ricardo C. L. F. Oliveira,et al.  MPC for LPV systems with bounded parameter variations , 2011, Int. J. Control.

[10]  Stephen Piche,et al.  Nonlinear model predictive control using neural networks , 2000 .

[11]  Zheng Yan,et al.  Robust Model Predictive Control of Nonlinear Systems With Unmodeled Dynamics and Bounded Uncertainties Based on Neural Networks , 2014, IEEE Transactions on Neural Networks and Learning Systems.

[12]  Sangchul Won,et al.  Robust model predictive control for LPV systems using relaxation matrices , 2007 .

[13]  Hong Chen,et al.  Model predictive control of constrained LPV systems , 2012, Int. J. Control.

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

[15]  F. L. Lewis,et al.  Neural-network predictive control for nonlinear dynamic systems with time-delay , 2003, IEEE Trans. Neural Networks.

[16]  Qingshan Liu,et al.  A One-Layer Recurrent Neural Network for Pseudoconvex Optimization Subject to Linear Equality Constraints , 2011, IEEE Transactions on Neural Networks.

[17]  Lingjie Chen,et al.  Stability and Stabilization of a Class of Multimode Linear Discrete-Time Systems With Polytopic Uncertainties , 2009, IEEE Transactions on Industrial Electronics.

[18]  Qingshan Liu,et al.  A One-Layer Recurrent Neural Network With a Discontinuous Hard-Limiting Activation Function for Quadratic Programming , 2008, IEEE Transactions on Neural Networks.

[19]  Jun Wang,et al.  Model Predictive Control of Nonlinear Systems With Unmodeled Dynamics Based on Feedforward and Recurrent Neural Networks , 2012, IEEE Transactions on Industrial Informatics.

[20]  Qingshan Liu,et al.  A one-layer recurrent neural network for constrained pseudoconvex optimization and its application for dynamic portfolio optimization , 2012, Neural Networks.

[21]  Jun Wang,et al.  A Novel Recurrent Neural Network for Solving Nonlinear Optimization Problems With Inequality Constraints , 2008, IEEE Transactions on Neural Networks.

[22]  Hannu T. Toivonen,et al.  A neural network model predictive controller , 2006 .

[23]  Michael Athans,et al.  Guaranteed properties of gain scheduled control for linear parameter-varying plants , 1991, Autom..

[24]  Emanuele Garone,et al.  Receding Horizon Control Strategies for Constrained LPV Systems Based on a Class of Nonlinearly Parameterized Lyapunov Functions , 2012, IEEE Transactions on Automatic Control.

[25]  Xiaolin Hu,et al.  An Improved Dual Neural Network for Solving a Class of Quadratic Programming Problems and Its $k$-Winners-Take-All Application , 2008, IEEE Transactions on Neural Networks.

[26]  Wilson J. Rugh,et al.  Research on gain scheduling , 2000, Autom..

[27]  Jun Wang,et al.  Model Predictive Control of Unknown Nonlinear Dynamical Systems Based on Recurrent Neural Networks , 2012, IEEE Transactions on Industrial Electronics.

[28]  Reza Olfati-Saber.  Global configuration stabilization for the VTOL aircraft with strong input coupling , 2002, IEEE Trans. Autom. Control..

[29]  G. Balas,et al.  Development of linear-parameter-varying models for aircraft , 2004 .

[30]  Jun Wang,et al.  A One-Layer Recurrent Neural Network for Constrained Nonsmooth Optimization , 2011, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).