Identification of Continuous-time Systems from Sampled Data via Genetic Algorithm

K. Inoue, G. Chen, H. Shibata, and T. Fujinaka (Japan)


system identification, continuous-time system, genetic algorithm


This paper proposes a system identification method of a continuous-time system from sampled input and output data using a genetic algorithm(GA). A gene-coding based on a pole-zero parameterization is adopted for a plant to be identified. It is shown that a GA is able to directly identify poles and zeros. It is obvious that an ordering difficulty arise from the pole-zero parameterization. To avoid the difficulty, we introduce a certain ordering procedure be fore crossover. Finally, an illustrative numerical example is given.

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