Báo Cáo Using a modified genetic algorithm for multiobjective modelling and optimisation of tagakisugeno fuz

ABSTRACT
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This paper is concerned with using a modified genetic algorithm (MGA) for generating the Tagaki-Sugeno type fuzzy model. By using such a MGA, we process the input-output data and optimize the fuzzy model. This is referred to perform fuzzy identification by which we generate automatically the appropriate fuzzy if-then rules to characterize the plant.

We know that in conventional identification techniques, difficulties such as poor knowledge of the process, inaccurate process parameters determining and complexity of the resulting model, all which limit their usefulness during dealing with dynamic industrial processes. Fuzzy model identification is a rather new area in control system design as well as the field of MGA optimisation of such T-S type fuzzy model is still in its early stage.

Keywords : Tagaki-Sugeno fuzzy model, identification model, optimal control, modified genetic algorithm.