Stochastic output-feedback model predictive control for systems with multiplicative and additive uncertainty

被引:0
|
作者
Li Jiwei [1 ]
Li Dewei [1 ]
Xi Yugeng [1 ]
Zheng Pengyuan [2 ]
机构
[1] Shanghai Jiao Tong Univ, Dept Automat, Minist Educ, Key Lab Syst Control & Informat Proc, Shanghai 200240, Peoples R China
[2] Shanghai Univ Elect Power, Coll Automat Engn, Shanghai 200090, Peoples R China
关键词
model predictive control; output feedback; probabilistic constraints; stochastic uncertainty; CONSTRAINED LINEAR-SYSTEMS; STATE; DESIGN; MPC; IMPLEMENTATION;
D O I
暂无
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 designs output-feedback model predictive control for discrete-time stochastic linear systems. An augmented system of both estimated state and estimation error is formulated. A series of polyhedrons is designed for uncertainty propagation of the augmented system and handling probabilistic constraints. In particular, the polyhedron of estimation error is maintained over the repeated optimization such that the real system state is properly estimated. The resultant optimization problem of the controller is quadratic programming and is solved efficiently. A numerical example is given to illustrate performance of the controller.
引用
收藏
页码:4179 / 4184
页数:6
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