三自由度并联机器人加载控制的自抗扰算法研究

IF 0.7 Q4 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Journal of Advanced Computational Intelligence and Intelligent Informatics Pub Date : 2023-09-20 DOI:10.20965/jaciii.2023.p0923
Yu Liu, Yumeng Chen, Yu Gong, Guoxin Zhao
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引用次数: 0

摘要

设计了一种基于气动3-universal- prismuniversal (UPU)并联机械手的三维加载装置(三条链各有UPU接头),用于对目标施加时变多维载荷。首先,根据矢量叠加原理和Newton-Raphson方法,分析了加载装置的运动学逆解和正解;其次,基于螺旋理论,推导了动平台与作动机构之间的静态映射关系。第三,建立了基于比例流量阀和金属密封气缸的气动3-UPU并联机构的二阶数学模型。在建模过程中为控制算法提供了一个可参考的不精确模型。第四,基于自抗扰控制(ADRC)技术,提出了一种三维加载控制算法,实现了动态加载控制。实验结果表明,该算法对扰动具有良好的鲁棒性,稳态控制精度小于2 N,动态跟踪(0.2 Hz正弦跟踪)均方误差小于10.5 N。
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Research on Active Disturbance Rejection Algorithm for Loading Control of 3-DOF Parallel Robot
A three-dimensional (3D) loading device based on a pneumatic 3-universal-prismatic-universal (UPU) parallel manipulator (three chains with UPU joint each) is designed to apply time-varying multi-dimensional loads to a target. First, according to the principle of vector superposition and Newton–Raphson method, the inverse and forward kinematics of the loading device are analyzed. Second, based on the screw theory, the static mapping between the dynamic platform and actuations is derived. Third, a second-order mathematical model is established for pneumatic 3-UPU parallel mechanism based on proportional flow valve and a metal seal pneumatic cylinder. A referential inaccurate model is provided for the control algorithm during modeling. Fourth, based on active disturbance rejection control (ADRC) technique, a 3D loading control algorithm is proposed and dynamic loading control is realized. Experimental results show that the ADRC algorithm has good robustness against disturbances, the steady-state control accuracy is less than 2 N, and the mean square error in dynamic tracking (sinusoidal tracking at 0.2 Hz) is less than 10.5 N.
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来源期刊
CiteScore
1.50
自引率
14.30%
发文量
89
期刊介绍: JACIII focuses on advanced computational intelligence and intelligent informatics. The topics include, but are not limited to; Fuzzy logic, Fuzzy control, Neural Networks, GA and Evolutionary Computation, Hybrid Systems, Adaptation and Learning Systems, Distributed Intelligent Systems, Network systems, Multi-media, Human interface, Biologically inspired evolutionary systems, Artificial life, Chaos, Complex systems, Fractals, Robotics, Medical applications, Pattern recognition, Virtual reality, Wavelet analysis, Scientific applications, Industrial applications, and Artistic applications.
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