On-line tuning strategy for model predictive controllers

This paper presents an intuitive on-line tuning strategy for linear model p redictive control (MPC) algorithms. The tuning strategy is based on the lin ear approximation between the closed-loop predicted output and the MPC tuni ng parameters. By direct utilization of the sensitivity expressions for the closed-loop response with respect to the MPC tuning parameters, new values of the tuning parameters can be found to steer the MPC feedback response i nside predefined time-domain performance specifications. Hence, the algorit hm is cast as a simple constrained least squares optimization problem which has a straightforward solution. The simplicity of this strategy makes it m ore practical for on-line implementation. Effectiveness of the proposed str ategy is tested on two simulated examples. One is a linear model for a thre e-product distillation column and the second is a non-linear model for a CS TR. The effectiveness of the proposed tuning method is compared to an exiti ng offline tuning method and showed superior performance. (C) 2001 Elsevier Science Ltd. All rights reserved.