Robust model predictive control for discrete uncertain nonlinear systems with time-delay via fuzzy model

2006 ◽  
Vol 7 (10) ◽  
pp. 1723-1732 ◽  
Author(s):  
Cheng-li Su ◽  
Shu-qing Wang
Keyword(s):  
Time Delay ◽  
Nonlinear Systems ◽  
Model Predictive Control ◽  
Predictive Control ◽  
Fuzzy Model ◽  
Uncertain Nonlinear Systems ◽  
Robust Model Predictive Control ◽  
Robust Model

Observer-based robust model predictive control of switched nonlinear systems with time delay and parametric uncertainties

2020 ◽  
pp. 107754632095052 ◽  
Author(s):  
Amin Taghieh ◽  
Mohammad Hossein Shafiei
Keyword(s):  
Time Delay ◽  
Nonlinear Systems ◽  
Model Predictive Control ◽  
Cost Function ◽  
Predictive Control ◽  
Lipschitz Constant ◽  
Parametric Uncertainties ◽  
Switched Nonlinear Systems ◽  
Robust Model Predictive Control ◽  
Robust Model

In this study, an observer-based robust model predictive control scheme is proposed to control a class of switched nonlinear systems in the presence of time delay and parametric uncertainties under arbitrary switching. Constructing an appropriate Lyapunov–Krasovskii functional in conjunction with an infinite horizon cost function, sufficient conditions are obtained to guarantee the asymptotic stability of the closed-loop switched system in terms of linear matrix inequalities depending on the time delay, the upper bounds of uncertain parameters, and the Lipschitz constant of subsystems. To model the uncertainty of the system, the parametric uncertainty is used to reduce the computational burden and the conservatism of the method. In the proposed method, a predictive state observer and an observer-based controller are synthesized via an online optimization problem to minimize the upper bound of the cost function, while handling the constraints. Finally, the obtained results are validated using practical and numerical simulations.

scholarly journals Nonfragile Robust Model Predictive Control for Uncertain Constrained Systems with Time-Delay Compensation

2016 ◽  
Vol 2016 ◽  
pp. 1-14 ◽  
Author(s):  
Wei Jiang ◽  
Hong-li Wang ◽  
Jing-hui Lu ◽  
Wei-wei Qin ◽  
Guang-bin Cai
Keyword(s):  
Time Delay ◽  
Model Predictive Control ◽  
Predictive Control ◽  
Optimization Problems ◽  
Sufficient Conditions ◽  
Constrained Systems ◽  
Delay Compensation ◽  
Robust Model Predictive Control ◽  
Robust Model ◽  
Time Delay Compensation

This study investigates the problem of asymptotic stabilization for a class of discrete-time linear uncertain time-delayed systems with input constraints. Parametric uncertainty is assumed to be structured, and delay is assumed to be known. In Lyapunov stability theory framework, two synthesis schemes of designing nonfragile robust model predictive control (RMPC) with time-delay compensation are put forward, where the additive and the multiplicative gain perturbations are, respectively, considered. First, by designing appropriate Lyapunov-Krasovskii (L-K) functions, the robust performance index is defined as optimization problems that minimize upper bounds of infinite horizon cost function. Then, to guarantee closed-loop stability, the sufficient conditions for the existence of desired nonfragile RMPC are obtained in terms of linear matrix inequalities (LMIs). Finally, two numerical examples are provided to illustrate the effectiveness of the proposed approaches.

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