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Journal Articles Robotica Year : 2022

Mechatronic design of dynamically decoupled manipulators based on the control performance improvement

Abstract

Abstract The control of industrial robot manipulators presents a difficult problem for control engineers due to the complexity of their nonlinear dynamics models. Nonlinear controls based on feedback linearization are developed to meet control requirements. Model-based nonlinear control is highly sensitive to parameter errors and leads to problems of robustness for tracking trajectories at high speeds, and there is the additional problem of a heavy computational burden to consider in the design of nonlinear controllers. In this paper, a mechatronic design approach is proposed, which aims to facilitate controller design by redesigning the mechanical structure. The problem is approached in two steps: first, the dynamic decoupling conditions of manipulators are described and discussed, involving redistribution of the moving mass, which leads to the decoupling of motion equations. A classical linear control law is then used to track the desired efficient bang-bang profile trajectory. Then, in the presence of parameter uncertainty and external disturbances, the nonlinear controls with simple structures are adopted to stabilize the decoupled system asymptotically. An analysis of the results from a simulation of this approach demonstrates its effectiveness in controller design. The proposed improvement in control performance is illustrated via two spatial manipulators.

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Dates and versions

hal-03831729 , version 1 (27-10-2022)

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Yaodong Lu, Yannick Aoustin, Vigen Arakelian. Mechatronic design of dynamically decoupled manipulators based on the control performance improvement. Robotica, 2022, pp.1-23. ⟨10.1017/S0263574722001485⟩. ⟨hal-03831729⟩
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