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Neural Dynamics for Cooperative Control of Redundant Robot Manipulators

机译:神经动力学用于冗余机器人机械手的协同控制

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摘要

In this paper, a neural-dynamic distributed scheme is proposed for the cooperative control of multiple redundant manipulators with limited communications. It is guaranteed that, with the communication network being connected, all manipulators can jointly reach the same desired motion. The proposed distributed scheme is rearranged as a time-varying quadratic program and solved online by a Zhang neural network. Then, theoretical analyses show that, without noise, the proposed distributed scheme is able to execute a given task with exponentially convergent position errors. Moreover, an explicit bound relationship between the control input noise and the end-effector position error is analytically derived. Furthermore, numerical comparisons substantiate the superiority, effectiveness, and accuracy of the proposed distributed scheme.
机译:本文提出了一种神经动力学分布式方案,用于受限通信的多个冗余机械手的协同控制。确保在连接通信网络的情况下,所有机械手可以共同达到相同的期望运动。所提出的分布式方案被重新布置为随时间变化的二次程序,并通过张神经网络在线求解。然后,理论分析表明,在没有噪声的情况下,所提出的分布式方案能够执行具有指数收敛位置误差的给定任务。此外,通过分析得出控制输入噪声与末端执行器位置误差之间的明确界限关系。此外,数值比较证实了所提出的分布式方案的优越性,有效性和准确性。

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