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Motivated by the demand of intelligent control that applicable to real industrial systems, this brief develops an innovative neuro controller for remotely operated robotic manipulators. First, the leader-following robotic devices and their communication are introduced. The remotely operated robot can either be controlled by pre-designed controller or human-computer interaction. Then, a neuro network algorithm is utilized to update PID control gains adaptively. To minimize training time, adaptive moment estimation algorithm is integrated to the neuro PID controller to form a novel control strategy which can be implemented in closed loop. As a result, intelligent algorithms and control methodology can be combined to solve industrial problem. Furthermore, the proposed intelligent controllers are implemented to two cases of remotely operated robot: 1. pre-designed motion driven for comparison; 2. Human-computer interaction. Real experimental results can successfully validate the effectiveness of the presented techniques.
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Ren et al. (2022) studied this question.
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