Command Filtered Backstepping Control of a Two-Link Flexible Joint Manipulator with Uncertainties Based on Reduced-Order ESO

Xiangyin Fei, Changzhong Pan, Lan Zhou, Peiyin Xiong, Meiliu Li
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Abstract

The motion control of flexible joint manipulators (FJMs) is a hot topic in the field of robot control, and the uncertainties including parameter perturbations and disturbances are the key challenges in the development of control strategies for FJMs. In this paper, we take a two-link FJM with complex uncertainties as the object, and present a command filtered backstepping control approach based on reduced-order extended state observer (RESO) for the trajectory tracking control of the two-link FJM with high precision. To enhance the robustness of the control system, an RESO which takes parameter perturbations, friction term and external disturbances as the lumped disturbances is constructed to estimate and compensate for the disturbances. The second-order command filter technique is introduced to eliminate the “explosion of complexity” problem of the conventional backstepping method, and an error compensation dynamic system is developed to reduce the potential filtering errors. All signals of the closed-loop system are proved to be uniformly ultimately bounded by Lyapunov theorem. Simulation reaults are shown to demonstrate the effectiveness and efficiency of the proposed control method.
基于降阶ESO的不确定双连杆柔性关节机械臂命令滤波反演控制
柔性关节机械臂的运动控制是机器人控制领域的一个热点问题,其中包括参数摄动和扰动在内的不确定性是柔性关节机械臂控制策略开发中的关键挑战。本文以具有复杂不确定性的两连杆飞振机为研究对象,提出了一种基于降阶扩展状态观测器(RESO)的命令滤波反步控制方法,用于高精度的两连杆飞振机轨迹跟踪控制。为了提高控制系统的鲁棒性,构造了以参数扰动、摩擦项和外部扰动为集总扰动的RESO来估计和补偿扰动。引入二阶命令滤波技术,消除了传统反演方法的“复杂度爆炸”问题,并设计了误差补偿动态系统,减小了潜在的滤波误差。证明了闭环系统的所有信号最终一致地由李雅普诺夫定理有界。仿真结果验证了所提控制方法的有效性和高效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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