Soft constrained finite horizon model predictive control

Authors

M Askaria, University of Malaya
Mahmoud Moghavvemi, University of Malaya
Haider A. F Almurib, University of Nottingham
Ahmed M. Haidar, University of WollongongFollow

RIS ID

105509

Publication Details

M. Askaria, M. Moghavvemi, H. A. F. Almurib & A. Haidar, "Soft constrained finite horizon model predictive control," in IEEE Industry Application Society - 51st Annual Meeting, IAS 2015, Conference Record, 2015, pp. 1-8.

Abstract

This article addresses tuning of the finite prediction horizon of soft-constrained model predictive control. The findings presented in this paper prove that there exists a finite horizon such that the infinite horizon soft-constrained model predictive control problem can be solved as a finite horizon soft-constrained model predictive control problem. Algorithms are proposed to compute the upper-bound of the prediction horizon in online and offline modes. The effectiveness of the proposed algorithm is verified by illustrative example.