Title :
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
fDate :
6/21/1905 12:00:00 AM
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;
Conference_Titel :
Decision and Control, 1999. Proceedings of the 38th IEEE Conference on
Conference_Location :
Phoenix, AZ
Print_ISBN :
0-7803-5250-5
DOI :
10.1109/CDC.1999.827793
