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A scheme on the force and motion control of manipulator robots based on a neural network

机译:基于神经网络的机器人机器人力量和运动控制方法

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In this paper, a computed-torque control scheme based on the BP algorithm is proposed. The control scheme is an efficient combination of a computed-torque control and a neural network as a compensation structure, which enhances the adaptability of the controller. Based on the Lyapunov stability theorem, it is shown that the new scheme can guarantee tracking performance of the robotic manipulator. Furthermore, the scheme showed a good performance when it was applied to the force control. The results of the simulations and experiments verified the effectiveness of the proposed scheme.
机译:本文提出了一种基于BP算法的计算扭矩控制方案。控制方案是计算 - 扭矩控制和神经网络作为补偿结构的有效组合,其增强了控制器的适应性。基于Lyapunov稳定性定理,表明新方案可以保证跟踪机器人操纵器的性能。此外,该方案在将其应用于力控制时显示出良好的性能。模拟和实验结果验证了拟议方案的有效性。

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