基于傅立叶级数展开的机械臂无模型鲁棒阻抗控制

M. Fard, S. Khorashadizadeh
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引用次数: 11

摘要

阻抗控制是机械臂与环境接触时最常用的控制方法。机器人系统响应环境的动力学行为用阻抗模型来描述。该模型是确定的、线性的,而机械臂是不确定的、非线性的。因此,主要的挑战是克服不确定性和非线性来控制所需的阻抗模型。提出了一种基于变结构模型逼近控制(VSMRC)和函数逼近技术(FAT)的鲁棒阻抗控制策略。FAT是基于傅里叶级数近似。与其他现有方法相比,所提出的方法包括两个重要性质。首先,由于傅里叶级数近似的收敛速度加快,它对不确定性的快速变化具有鲁棒性。其次,它不要求不确定性一定是已知的。该方案在工业选择性柔性装配机械臂(SCARA)上进行了仿真。仿真结果验证了理论的正确性和所提技术的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Model free robust impedance control of robot manipulators using fourier series expansion
Impedance control is the most favorite control of robot manipulators in contact with environment. The dynamic behavior of robotic system in response to environment is prescribed by an impedance model. This model is certain and linear while the robot manipulator is uncertain and nonlinear. So the major challenge is overcoming uncertainty and nonlinearity to dominate the desired impedance model. This paper presents a robust impedance control strategy based on Variable Structure Model Reaching Control (VSMRC) and Function Approximation Techniques (FAT). FAT is based on Fourier series approximation. In contrast to other existing methods, the proposed approach includes two important properties. Firstly, it is robust against fast changes in uncertainty due to increased speed of convergence in Fourier series approximation. Secondly, it does not require uncertainties bound to be known. This scheme is simulated on an industrial selective compliance assembly robot arm (SCARA). Simulation results verify the theory and confirm the effectiveness of presented technique.
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