Explicit Approximate Approach to Feedback Min-Max Model Predictive Control of Constrained Nonlinear Systems

Author

Grancharova, Alexandra ; Johansen, Tor A.

Author_Institution

Inst. of Control & Syst. Res., Bulgarian Acad. of Sci., Sofia

fYear

2006

fDate

13-15 Dec. 2006

Firstpage

4848

Lastpage

4853

Abstract

This paper presents an approximate multi-parametric nonlinear programming (mp-NLP) approach to explicit solution of feedback min-max model predictive control problems for constrained nonlinear systems in the presence of bounded disturbances. It is based on an orthogonal search tree structure of the state space partition and consists in constructing a feasible piecewise nonlinear (PWNL) approximation to the optimal sequence of feedback control policies. The proposed approach is applied to design an explicit feedback min-max nonlinear model predictive controller for a cart moving on a plane and attached to the wall via a spring

Keywords

control system synthesis; feedback; minimax techniques; nonlinear control systems; nonlinear programming; predictive control; state-space methods; tree searching; bounded disturbances; constrained nonlinear systems; feedback control policy; feedback min-max model predictive control; multiparametric nonlinear programming; orthogonal search tree structure; piecewise nonlinear approximation; state space partition; Feedback control; Nonlinear systems; Optimal control; Piecewise linear approximation; Predictive control; Predictive models; Robustness; State-space methods; Tree data structures; Uncertainty;

fLanguage

English

Publisher

ieee

Conference_Titel

Decision and Control, 2006 45th IEEE Conference on

Conference_Location

San Diego, CA

Print_ISBN

1-4244-0171-2

Type

conf

DOI

10.1109/CDC.2006.377772

Filename

4177241