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Decentralized robust control of a hydraulic driven parallel manipulator based on disturbance estimation

机译:基于干扰估计的液压驱动并行机械手分散鲁棒控制

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Since the parallel robot manipulator is a nonlinear, coupling and time-varying dynamic system, it is difficult to synthesize a controller based on the dynamic model by using a centralized control method. Considering each driving unit as a subsystem and treating the coupling interconnection terms between the joints as a time-varying external disturbance of the driving unit, this paper presents a decentralized robust controller with extended state observer (ESO) in joint-space to implement the high-precision trajectory tracking of the robot manipulator. By constructing two extended state observers, not only matched uncertainties but also unmatched uncertainties can be estimated and then compensated in a feed-forward way. Consequently, high-gain feedback is avoided. In addition, the feedback robust laws ensure the global robustness of the proposed controller. Furthermore, the stability of the system is verified by constructing the Lyapunov function. The simulation results show that the proposed controller can estimate both matched and unmatched uncertainties of the driving unit accurately, and the system possesses high trajectory tracking performance and strong robustness.
机译:由于并行机器人机器人是非线性,耦合和时变动态系统,因此难以使用集中控制方法基于动态模型来合成控制器。考虑到每个驱动单元作为子系统,并将关节之间的耦合互连术语视为驱动单元的时变外部干扰,本文介绍了一个分散的鲁棒控制器,其中在关节空间中具有扩展状态观察者(ESO)以实现高电平 - 机器人操纵器的轨迹跟踪。通过构造两个延伸状态观察者,不仅可以匹配不确定性,而且可以估计未比不确定性,然后以前馈方式补偿。因此,避免了高增益反馈。此外,反馈强大的法律确保了所提出的控制器的全球鲁棒性。此外,通过构建Lyapunov函数来验证系统的稳定性。仿真结果表明,所提出的控制器可以准确估计驱动单元的匹配和无与伦比的不确定性,并且该系统具有高轨迹跟踪性能和强大的鲁棒性。

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