基于辨识自适应NARX模型的单连杆柔性机械臂迭代学习控制

Dinesh Mute, Subhojit Ghosh, B. Subudhi
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引用次数: 1

摘要

针对单连杆柔性机械臂的辨识模型,设计了一种迭代学习控制器。由于系统具有非线性和时变特性,为满足控制系统设计的需要,利用输入输出实验数据,建立了一种具有外生输入的自适应非线性自回归模型。采用最小二乘法对ILC控制器进行整定。仿真结果表明,基于NARX模型的ILC控制器能够有效地抑制单连杆柔性机械臂的振动,实现精确的旋转跟踪。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Iterative learning control of a single-link flexible manipulator based on an identified adaptive NARX model
In this paper an iterative learning controller (ILC) is designed based on the identified model of a single-link flexible manipulator (SLFM). As the system is nonlinear and time-varying so to meet the demands of the control system design, an adaptive nonlinear autoregressive with exogenous input (NARX) model is identified using the input/output experimental data. Tuning of the ILC controller is carried out using least square method. Simulation results demonstrate the potential of the NARX model based ILC controller for precise rotation tracking of a single-link flexible manipulator with suppressing link vibration.
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