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首页> 外文期刊>International journal of humanoid robotics >Extended State Observer Fuzzy-Approximation-Based Active Disturbances Rejection Control Method for Humanoid Robot with Trajectory Tracking
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Extended State Observer Fuzzy-Approximation-Based Active Disturbances Rejection Control Method for Humanoid Robot with Trajectory Tracking

机译：基于状态观测器模糊逼近的主动扰动，具有轨迹跟踪的人形机器人的抑制控制方法

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摘要

This study aimed to propose an extended state observer fuzzy-approximation-based active disturbances rejection control (FAADRC) method for a dual-arm humanoid robotic system. The purpose of this control system was to provide disturbance estimation and compensation to enable the humanoid robots to track any continuous desired trajectory, even in the presence of environmental disturbances and parametric uncertainties. The proposed active disturbances rejection controller was analyzed using mathematical modeling, and the robot dual-arm motion information of a number of cases when they simulated the trajectory was examined to verify the model. The extended state observer adaptive fuzzy-approximation control strategy was designed combining the synthesis of the robust design, active disturbances rejection control, and Lyapunov function method so that the proposed FAADRC did not need to know the arms model of the humanoid robot precisely. In the control system proposed in this study, once the desired trajectories of the robot's dual-arm positions were given, the FAADRC system was closed to any unknown functions and to the derivative of the virtual control law of the humanoid robot system. In this case, a robust controller based on an extended state observer was designed to realize the disturbance estimation and compensation. Using the proposed trajectory tracking, not only were the coordinate motions of a humanoid robot's two arms generated, but the arms could also be controlled to move to the desired positions. The proposed closed-loop system under the FAADRC design was effective, and the asymptotic stability was successfully achieved. The numerical simulation showed the tracking error comparison and the estimated errors of the extended state observer. Two experimental tests were carried out to prove the performance of the algorithm presented in this study. The experimental results showed that the proposed FAADRC exhibited a better performance than the regular proportional integral derivative controller.
机译：本研究旨在提出扩展的基于状态观察者模糊近似的主动扰动抑制控制（FAADRC）方法，用于双臂人形机器机机器人系统。该控制系统的目的是提供干扰估计和补偿，以使人形机器人能够跟踪任何连续的期望轨迹，即使在存在环境干扰和参数的不确定性。使用数学建模分析所提出的主动干扰抑制控制器，以及当检查它们模拟轨迹时的多个情况的机器人双臂运动信息以验证模型。设计了扩展的状态观察者自适应模糊逼近控制策略，结合了鲁棒设计，主动干扰抑制控制和Lyapunov功能方法的合成，使得提出的FAADRC不需要精确地了解人形机器人的臂模型。在本研究中提出的控制系统中，一旦给出了机器人的双臂位置的所需轨迹，FAADRC系统被关闭到任何未知的功能和人形机器人系统虚拟控制定律的衍生物。在这种情况下，设计了一种基于扩展状态观察者的鲁棒控制器，用于实现干扰估计和补偿。使用所提出的轨迹跟踪，不仅是生成的人形机器人的两个臂的坐标运动，而且还可以控制臂移动到所需位置。在FAADRC设计下提出的闭环系统有效，成功实现了渐近稳定性。数值模拟显示跟踪误差比较和扩展状态观察者的估计误差。进行了两次实验测试以证明本研究中呈现的算法的性能。实验结果表明，拟议的FAADRC表现出比常规比例整体衍生控制器更好的性能。

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