An optimal approach to output-feedback robust model predictive control of LPV systems with disturbances

被引：50

作者：

Yang, Weilin ^{[1
]}

Gao, Jianwei ^{[1
]}

Feng, Gang ^{[2
]}

Zhang, TieJun ^{[1
]}

机构：

[1] Masdar Inst Sci & Technol, Dept Mech & Mat Engn, POB 54224, Abu Dhabi, U Arab Emirates

[2] City Univ Hong Kong, Dept Mech & Biomed Engn, Kowloon, Hong Kong, Peoples R China

来源：

INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL | 2016年 / 26卷 / 15期

基金：

新加坡国家研究基金会;

关键词：

model predictive control; LPV systems; output feedback; robust control; TO-STATE STABILITY; MPC;

D O I：

10.1002/rnc.3505

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

An observer-based output feedback predictive control approach is proposed for linear parameter varying systems with norm-bounded external disturbances. Sufficient and necessary robust positively invariant set conditions of the state estimation error are developed to determine the minimal ellipsoidal robust positively invariant set and observer gain through offline computation. The quadratic upper bound of state estimation error is updated and included in an H-type cost function of predictive control to optimize transient output feedback control performance. Recursive feasibility of the dynamic convex optimization problem is guaranteed in the proposed predictive control strategy. With the input-to-state stable observer, the closed-loop control system states are steered into a bounded set. Simulation results are given to demonstrate the effectiveness of the proposed control strategy. Copyright (c) 2016 John Wiley & Sons, Ltd.

引用

页码：3253 / 3273

页数：21

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