基于神经滑模和高阶滑模观测器的输出反馈跟踪控制

A. Vo, Hee-Jun Kang, V. Nguyen
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引用次数: 21

摘要

针对机器人的不确定性,提出了一种基于神经滑模的无关节速度测量输出反馈跟踪控制方案和高阶滑模观测器。设计了两个二阶滑模观测器分别用于估计机器人的关节速度和动态不确定性。利用一二阶滑模观测器在有限时间内估计状态向量,不进行滤波。为了在不滤波的情况下估计不确定性,设计了二阶滑模非线性观测器。通过对两个观测器进行积分,得到的观测器理论上可以得到关节速度和动态不确定性的精确估计。利用它们设计了一种基于神经滑模控制器的输出反馈跟踪控制方案。该控制方案能够有效地减少抖振,提高跟踪性能。最后,以一个二自由度机械臂为例进行了仿真,验证了该控制策略的有效性。
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An output feedback tracking control based on neural sliding mode and high order sliding mode observer
In this paper, a novel output feedback tracking control scheme based on neural sliding mode without joint velocity measurement and the high order sliding mode observer for the uncertainty of robot manipulators are presented. Two second-order sliding mode observers are designed to estimate joint velocities and dynamic uncertainties of the robot manipulator, respectively. The first-second order sliding mode observer is used to estimate the state vector in a finite time without filtration. To estimate the uncertainties without filtration, the second second-order sliding mode nonlinear observer is designed. By integrating two observers, the resulting observer can theoretically obtain exact estimations of both joint velocities and dynamic uncertainties. They are used to design an output feedback tracking control scheme based on neural sliding mode controller. This proposed control scheme can reduce chattering and improves tracking performances. Finally, the simulation for a 2-DOF robot manipulator is given to show the effectiveness of this control strategy.
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