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Multiobjective Evolutionary Approach to the Design of Optimal Controllers for Interval Plants via Parallel Computation
ChenChien James HSU ChihYung YU ShihChi CHANG
Publication
IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences
Vol.E89A
No.9
pp.23632373 Publication Date: 2006/09/01 Online ISSN: 17451337
DOI: 10.1093/ietfec/e89a.9.2363 Print ISSN: 09168508 Type of Manuscript: PAPER Category: Systems and Control Keyword: genetic algorithms, multiobjective genetic algorithms, interval systems, robust controllers, minimax optimization, parallel computation,
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Summary:
Design of optimal controllers satisfying performance criteria of minimum tracking error and disturbance level for an interval system using a multiobjective evolutionary approach is proposed in this paper. Based on a worstcase design philosophy, the design problem is formulated as a minimax optimization problem, subsequently solved by a proposed twophase multiobjective genetic algorithm (MOGA). By using two sets of interactive genetic algorithms where the first one determines the maximum (worstcase) cost function values for a given set of controller parameters while the other one minimizes the maximum cost function values passed from the first genetic algorithm, the proposed approach evolutionarily derives the optimal controllers for the interval system. To suitably assess chromosomes for their fitness in a population, root locations of the 32 generalized Kharitonov polynomials will be used to establish a constraints handling mechanism, based on which a fitness function can be constructed for effective evaluation of the chromosomes. Because of the timeconsuming process that genetic algorithms generally exhibit, particularly the problem nature of minimax optimization, a parallel computation scheme for the evolutionary approach in the MATLABbased working environment is also proposed to accelerate the design process.

