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Robust Control for Nonlinear Delta Parallel Robot With Uncertainty: An Online Estimation Approach

Ruiying Zhao, Linlin Wu, Ye‐Hwa Chen

发表年份
2020
引用次数
31
访问权限
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摘要

A series of fractional robust trajectory tracking controls are proposed for the Delta parallel robot with uncertainty. For the high speed and heavy load, the Delta parallel robot could not ignore the influences of the high nonlinearity (by the dynamics of the multiple closed-loops mechanism and the nonlinear joints friction) and the various kinds of uncertainties (i.e., the unknown dynamic parameters and external disturbances caused by the residual vibration). By formulating the motion equation of the Delta parallel robot, the nonlinearity is settled by a norm model based control design. The uncertainty considered in the paper is time-varying but unknown. An online estimation with an exponential type leakage term and dead-zone is construct to investigate the realtime information of the uncertainty. In virtue of the estimated information, two fractional robust trajectory tracking controls with the joints friction compensation are designed. Under the proposed controls, the system performance of the Delta parallel robot can be deterministically guaranteed (which includes uniform boundedness and uniform ultimate boundedness).

关键词

Control theory (sociology)Nonlinear systemRobotTrajectoryComputer scienceRobust controlRobustness (evolution)Motion controlNorm (philosophy)Artificial intelligence

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