Creator:
Aicha, Faten Ben ; Bouani, Faouzi ; Ksouri, Mekki
Contributor:
Korbicz, Józef - red. ; Uciński, Dariusz - red.
Title:
A multivariable multiobjective predictive controller
Group publication title:
Subject and Keywords:
closed loop performance ; coupled multivariable system ; generalized predictive control ; multiobjective optimization ; weighted sum method ; NSGA-II
Abstract:
Predictive control of MIMO processes is a challenging problem which requires the specification of a large number of tuning parameters (the prediction horizon, the control horizon and the cost weighting factor). In this context, the present paper compares two strategies to design a supervisor of the Multivariable Generalized Predictive Controller (MGPC), based on multiobjective optimization. Thus, the purpose of this work is the automatic adjustment of the MGPC synthesis by simultaneously minimizing a set of closed loop performances (the overshoot and the settling time for each output of the MIMO system). ; First, we adopt the Weighted Sum Method (WSM), which is an aggregative method combined with a Genetic Algorithm (GA) used to minimize a single criterion generated by the WSM. Second, we use the Non- Dominated Sorting Genetic Algorithm II (NSGA-II) as a Pareto method and we compare the results of both the methods. The performance of the two strategies in the adjustment of multivariable predictive control is illustrated by a simulation example. The simulation results confirm that a multiobjective, Pareto-based GA search yields a better performance than a single objective GA.
Publisher:
Zielona Góra: Uniwersytet Zielonogórski
Date:
Resource Type:
DOI:
Pages:
Source:
AMCS, volume 23, number 1 (2013) ; click here to follow the link