Constrained receding horizon predictive control for nonlinear systems

Author

Lee, Y.I. ; Kouvaritakis, B. ; Cannon, M.

Author_Institution

Div. of Electr. & Electron. Eng, Gyeongsang Nat.Univ., Jinju Gyeong-Nam, South Korea

Volume

4

fYear

1999

fDate

6/21/1905 12:00:00 AM

Firstpage

3370

Abstract

This paper represents a receding horizon predictive control algorithm for constrained nonlinear systems which, unlike earlier works, can be solved by linear programming methods. Use is made of a terminal inequality constraint in conjunction with a cost penalizing an upper bound on the tracking error over a finite control horizon. The optimization procedure is based on predictions made by linearized incremental models at points of a given seed trajectory and the effects of linearization error are taken into account to give a bound on the predicted tracking error. The proposed algorithm is posed in the form of LP and its asymptotic stability can be guaranteed by proper selection of the terminal weights of the cost index

Keywords

asymptotic stability; linear programming; model reference adaptive control systems; nonlinear control systems; predictive control; stability criteria; LP; asymptotic stability; constrained nonlinear systems; constrained receding horizon predictive control; cost index terminal weights; finite control horizon; linear programming; linearization error effects; linearized incremental models; predicted tracking error; terminal inequality constraint; tracking error; upper bound; Asymptotic stability; Costs; Error correction; Linear programming; Nonlinear systems; Prediction algorithms; Predictive control; Predictive models; Trajectory; Upper bound;

fLanguage

English

Publisher

ieee

Conference_Titel

Decision and Control, 1999. Proceedings of the 38th IEEE Conference on

Conference_Location

Phoenix, AZ

ISSN

0191-2216

Print_ISBN

0-7803-5250-5

Type

conf

DOI

10.1109/CDC.1999.827793

Filename

827793