Model predictive control for constrained systems with serially correlated stochastic parameters and portfolio optimization

Automatica ◽  
2015 ◽  
Vol 54 ◽  
pp. 325-331 ◽  
Author(s):  
Vladimir Dombrovskii ◽  
Tatyana Obyedko
Keyword(s):  
Model Predictive Control ◽  
Portfolio Optimization ◽  
Predictive Control ◽  
Constrained Systems ◽  
Stochastic Parameters

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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