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In this paper, an adaptive control of a parallel robot is proposed for trajectory tracking problems. This approach is based on adaptive multi-layer perceptron (MLP) neural network and sliding mode technique. The aim of this study is to design a robust controller with respect to external disturbances in order to improve the trajectory tracking. In fact, an adaptive MLP neural network is developed to...
In this paper, a neural adaptive force control of a parallel robot is proposed to solve the trajectory tracking problems. Assuming that the dynamic model of the system is a black box one, we use an a priori learning for its neural identification. And then, we use this results to design and adaptive control law. All adaptation laws of neural parameters are based on the stability of the closed loop...
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