Tube-based Stochastic Nonlinear Model Predictive Control: A Comparative Study on Constraint Tightening

被引:7
|
作者
Bonzanini, Angelo D. [1 ]
Santos, Tito L. M. [2 ]
Mesbah, Ali [1 ]
机构
[1] Univ Calif Berkeley, Dept Chem & Biomol Engn, Berkeley, CA 94720 USA
[2] Univ Fed Bahia, Dept Elect Engn, BR-40210630 Salvador, BA, Brazil
来源
IFAC PAPERSONLINE | 2019年 / 52卷 / 01期
关键词
Tube-based MPC; chance constraints; constraint tightening; incremental stabilizability; SYSTEMS; MPC;
D O I
10.1016/j.ifacol.2019.06.128
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This paper presents a comparative study between two constraint-tightening approaches for tube-based stochastic nonlinear model predictive control (SNMPC) with and without terminal constraints. A simple constraint-tightening method based on the exponential decay rate of a (5-Lyapunov function is extended to the stochastic setting. This method uses the notion of incremental stabilizability to alleviate the need for offline, but involved computation of terminal constraints. The proposed method is compared to a SNMPC formulation that employs terminal constraints and Lipschitz constant-based constraint tightening. A comparative analysis is presented on a benchmark continuous stirred-tank reactor problem. Practical approximations for computing terminal sets are discussed in the context of this comparison. (C) 2019, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.
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页码:598 / 603
页数:6
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