Every Continuous Nonlinear Control System Can be Obtained by Parametric Convex Programming

Author

Baes, Michel ; Diehl, Moritz ; Necoara, Ion

Author_Institution

Electr. Eng. Dept., Katholieke Univ. Leuven, Leuven

Volume

53

Issue

8

fYear

2008

Firstpage

1963

Lastpage

1967

Abstract

In this short note, we define parametric convex programming (PCP) in a slightly different manner than it is usually done by extending convexity not only to variables but also to the parameters, and we show that the widely applied model predictive control (MPC) technique is a particular case of PCP. The main result of the note is an answer to the inverse question of PCP: which feedback laws can be generated by PCP? By employing results of convex analysis, we provide a constructive proof-yet not computational-that allows us to conclude that every continuous feedback law can be obtained by PCP.

Keywords

continuous systems; convex programming; feedback; nonlinear control systems; predictive control; continuous feedback law; continuous nonlinear control system; model predictive control; parametric convex programming; Circuit stability; Feedback; Hypercubes; Iterative methods; Linear matrix inequalities; Linear systems; Nonlinear control systems; Predictive control; Predictive models; Transmission line matrix methods; Continuous feedback laws; model predictive control (MPC); parametric convex programming (PCP);

fLanguage

English

Journal_Title

Automatic Control, IEEE Transactions on

Publisher

ieee

ISSN

0018-9286

Type

jour

DOI

10.1109/TAC.2008.928131

Filename

4631508