ファジィ推論による制御対象の同定とオートチューニングへの応用

概要

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This paper presents a new identification method which utilizes fuzzy inference in parameter identification. The proposed system has an additional control loop where a real plant is replaced by a plant model. At first, an input signal, such as a step signal, is given to both control loops. Then the parameters in the plant model are modified such that the output signal features, such as magnitude of an overshoot, of the two loops become closer. Fuzzy rules describe the relationship between comparison results of the features and magnitudes of modification in the model parameter values. This method is effective in auto-tuning because the response of the closed loop is verified. The proposed method is tested both in simulations for several plants with first-order lags and dead-times, and in experiments for motor control. The results show that the proposed method is effective in practical use.
社団法人日本機械学会の論文
1992-10-25