제어로봇시스템학회:학술대회논문집
- 1997.10a
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- Pages.629-632
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- 1997
A self tuning controller using genetic algorithms
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Abstract
This paper presents the design method of controller which is combined Genetic Algorithms with the Generalized minimum variance self tuning controller. It is shown that the controllers adapts to changes in the system parameters with time delays and noises. The self tuning effect is achieved through the recursive least square algorithm at the parameter estimation stage and also through the Robbins-Monro algorithm at the stage of optimizing a polynomial parameters. The computer simulation results are presented to illustrate the procedure and to show the performance of the control system.
Keywords
- generalized minimum variance control;
- weighting polynomial;
- Robbins-Monro algorithm;
- genetic algorithm