Discrete Modelling of Continuous-Time Systems Having Interval Uncertainties Using Genetic Algorithms

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概要

• 論文の詳細を見る

• In this paper, an evolutionary approach is proposed to obtain a discrete-time state-space interval model for uncertain continuous-time systems having interval uncertainties. Based on a worst-case analysis, the problem to derive the discrete interval model is first formulated as multiple mono-objective optimization problems for matrix-value functions associated with the discrete system matrices, and subsequently optimized via a proposed genetic algorithm (GA) to obtain the lower and upper bounds of the entries in the system matrices. To show the effectiveness of the proposed approach, roots clustering of the characteristic equation of the obtained discrete interval model is illustrated for comparison with those obtained via existing methods.

• （社）電子情報通信学会の論文
• 2008-01-01

著者

• Lu Tsung-chi

  Department Of Electronic Engineering St. John's University

• Chen Heng-chou

  Department Of Computer And Communication Engineering Chienkuo Technology University

• Hsu Chen-chien

  Department Of Electrical Engineering Tamkang University

関連論文

• Multiobjective Evolutionary Approach to the Design of Optimal Controllers for Interval Plants via Parallel Computation(Systems and Control)
• Population Fitness Probability for Effectively Terminating Evolution Operations of a Genetic Algorithm(Biocybernetics, Neurocomputing)
• Discrete Modelling of Continuous-Time Systems Having Interval Uncertainties Using Genetic Algorithms

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