A Fuzzy Neural Network Direct Adaptive Iterative Learning Controller for Robot Manipulators
نویسنده
چکیده
This paper studies the iterative learning control of robotic systems with repetitive tasks. A fuzzy neural network is applied to design a direct adaptive iterative learning controller. The fuzzy neural network is introduced for compensation of the unknown certainty equivalent controller. A new adaptive law using mixed time-domain and iteration-domain adaptation is developed. It is shown that the finiteness of control parameters and control input can be guaranteed for all the time interval during each iteration without using parameter projection.
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