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Robot manipulator control based on the inner-learning mechanism

机译:基于内部学习机制的机器人机械手控制

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This paper deals with the control problem of a class of multi-tasking and varying-load robot systems, presents an effective control architecture based on inner-learning mechanism. The novelty of the controller designed by the new architecture is in the fact that the sub-controllers can learn from each other and change information from each other; it can also avoid the failures of the sub-controllers. The good performance and the feasibility of this approach are shown through the experimental results.
机译:针对一类多任务变负荷机器人系统的控制问题,提出了一种基于内部学习机制的有效控制体系结构。通过新架构设计的控制器的新颖性在于,子控制器可以彼此学习,并且可以彼此更改信息。它也可以避免子控制器的故障。实验结果表明了该方法的良好性能和可行性。

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