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Performance of hybrid learning control with input shaping for input tracking and vibration suppression of a flexible manipulator

机译:具有输入整形的混合学习控制的性能,用于柔性机械臂的输入跟踪和振动抑制

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摘要

The Objective Of The Work Reported In This Paper Is To Investigate The Performance Of An Intelligent Hybrid Iterative Learning Control Scheme With Input Shaping For Input Tracking And End-Point Vibration Suppression Of A Flexible Manipulator. The Dynamic Model Of The System Is Derived Using Finite Element Method. Initially, A Collocated Proportional-Derivative (PD) Controller Utilizing Hub-Angle And Hub-Velocity Feedback Is Developed For Control Of Rigid-Body Motion Of The System. This Is Then Extended To Incorporate Iterative Learning Control With Genetic Algorithm (GA) To Optimize The Learning Parameters And A Feedforward Controller Based On Input Shaping Techniques For Control Of Vibration (Flexible Motion) Of The System. Simulation Results Of The Response Of The Manipulator With The Controllers Are Presented In Time And Frequency Domains. The Performance Of Hybrid Learning Control With Input Shaping Scheme Is Assessed In Terms Of Input Tracking And Level Of Vibration Reduction. The Effectiveness Of The Control Schemes In Handling Various Payloads Is Also Studied.
机译:本文所报告工作的目的是研究一种具有输入整形功能的智能混合迭代学习控制方案的性能,该方案用于柔性机械手的输入跟踪和端点振动抑制。系统的动力学模型是用有限元方法推导的。最初,开发了一种利用轮毂角和轮毂速度反馈的并置比例微分(PD)控制器,用于控制系统的刚体运动。然后将其扩展为将迭代学习控制与遗传算法(GA)结合在一起,以优化学习参数,并基于输入整形技术的前馈控制器来控制系统的振动(柔性运动)。在时域和频域中给出了带有控制器的机械手响应的仿真结果。根据输入跟踪和减振水平来评估具有输入整形方案的混合学习控制的性能。还研究了控制方案在处理各种有效载荷方面的有效性。

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