Weighting Matrix Selection Method for LQR Design Based on a Multi-Objective Evolutionary Algorithm

Abstract:

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This paper introduces an application of Multi-Objective Evolution Algorithm (MOEA) to design Q and R weighting matrices in Linear Quadratic regulators (LQR). Considering the difficulty of designing weighting matrices for a linear quadratic regulator, a multi-objective evolutionary algorithm based approach is proposed. The LQR weighting matrices, state feedback control rate and consequently the optimal controller are obtained by means of establishing the multi-objective optimization model of LQR weighting matrices and applying MOEA to it, which makes control system meet multiple performance indexes simultaneously. Controller of double inverted pendulum system is designed using the proposed approach. Simulation results show that it has shorter adjusting time and smaller amplitude value deviating from steady-state than a Non-dominated Sorting Genetic Algorithm LQR ( NSGA- LQR )weighting matrices design approach.

Info:

Periodical:

Advanced Materials Research (Volumes 383-390)

Edited by:

Wu Fan

Pages:

1047-1054

DOI:

10.4028/www.scientific.net/AMR.383-390.1047

Citation:

M. A. Nekoui and H. H. J. Bozorgi, "Weighting Matrix Selection Method for LQR Design Based on a Multi-Objective Evolutionary Algorithm", Advanced Materials Research, Vols. 383-390, pp. 1047-1054, 2012

Online since:

November 2011

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Price:

$35.00

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