System identification via a virtual higher-resolution fuzzy model
Intelligent Automation & Soft Computing（2000）
摘要
A fuzzy identification algorithm with an inherent knowledge generalization mechanism is reported in this paper. In the proposed identification algorithm, a low-resolution fuzzy model is used to mimic the effect of a virtual higher-resolution model. The gradient descent optimization method is then applied to update the rule-base by using the difference between the actual system output and the model output. Simulation studies are included to demonstrate the performance of the algorithm
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关键词
fuzzy logic,fuzzy systems,generalisation (artificial intelligence),gradient methods,identification,optimisation,truth maintenance,algorithm performance,fuzzy identification algorithm,gradient descent optimization method,knowledge generalization mechanism,low-resolution fuzzy model,model output,rule-base updating,simulation,system identification,system output,virtual higher-resolution fuzzy model,gradient descent method
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