Lyapunov-based model predictive control of stochastic nonlinear systems

被引：46
|
作者：
Mahmood, Maaz [1 ]
Mhaskar, Prashant [1 ]
机构：
[1] McMaster Univ, Dept Chem Engn, Hamilton, ON L8S 4L7, Canada
来源：
AUTOMATICA | 2012年 / 48卷 / 09期
基金：
加拿大自然科学与工程研究理事会;
关键词：
Stochastic systems; Predictive control; RECEDING HORIZON CONTROL; OUTPUT-FEEDBACK; STABILIZATION; STABILITY; DRIVEN; STATE; NOISE;
D O I：
10.1016/j.automatica.2012.06.033
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
In this work, we design a Lyapunov-based model predictive controller (LMPC) for nonlinear systems subject to stochastic uncertainty. The LMPC design provides an explicitly characterized region from where stability can be probabilistically obtained. The key idea is to use stochastic Lyapunov-based feedback controllers, with well characterized stabilization in probability, to design constraints in the LMPC that allow the inheritance of the stability properties by the LMPC. The application of the proposed LMPC method is illustrated using a nonlinear chemical process system example. (C) 2012 Elsevier Ltd. All rights reserved.
引用
收藏
页码：2271 / 2276
页数：6
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