Paper Info
Title
Stable model predictive control for a nonlinear system
Abstract
In this paper, a stable model predictive control approach is proposed for constrained highly nonlinear systems. The technique is a modification of the multistep Newton-type control strategy, which was introduced by Li and Biegler. The proposed control technique is applied on a constrained highly nonlinear aerodynamic test bed, the twin rotor MIMO system (TRMS) to show the efficacy of the control technique. Since the accuracy of the plant model is vital in MPC techniques, the nonlinear state space equations of the system are derived considering all possible effective components. The nonlinear model is adaptively linearized during the prediction horizon. The linearized models of the system are employed to form a linear quadratic objective function subject to a set of inequality constraints due to the system input/output limits. The stability of the control system is guaranteed using the terminal equality constraints technique. The satisfactory performance of the proposed control algorithm on the TRMS validates the effectiveness and the reliability of the approach.
Year
DOI
Venue
2011
10.1016/j.jfranklin.2011.05.015
Journal of the Franklin Institute
Keywords
Field
DocType
nonlinear system,input output,objective function,state space,predictive control,test bed,linear model,control system
Mathematical optimization,Nonlinear system,Nonlinear control,Control theory,State-space representation,Model predictive control,MIMO,Rotor (electric),Control system,Mathematics,Sliding mode control
Journal
Volume
Issue
ISSN
348
8
0016-0032
Citations 
PageRank 
References 
6
0.59
21
Authors
2
Name
Order
Citations
PageRank
A. Rahideh1293.92
M. Hasan Shaheed2283.01