Min-max feedback model predictive control with state estimation

被引：5

作者：

Jia, D ^{[1
]}

Krogh, B ^{[1
]}

机构：

[1] Carnegie Mellon Univ, Dept Elect & Comp Engn, Pittsburgh, PA 15213 USA

来源：

ACC: PROCEEDINGS OF THE 2005 AMERICAN CONTROL CONFERENCE, VOLS 1-7 | 2005年

关键词：

D O I：

10.1109/ACC.2005.1469943

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 proposes a state estimation scheme for output feedback min-max model predictive control (MPC). A set-membership state estimator bounds the current states of the physical system. A standard state estimator provides state feedback for the state feedback control law in MPC optimization over the prediction horizon. The paper presents a recursive method for the set-membership state estimation and conditions for bounded stability of the closed-loop system. The approach is illustrated with an example.

引用

页码：262 / 267

页数：6

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