气动肌肉执行器的遗传算法优化T-S模糊控制

Cheng Chen, Jian Huang, Dongrui Wu, Zhikang Song
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引用次数: 4

摘要

基于气动肌肉执行器(PMA)的三要素模型,提出了一种基于遗传算法优化的T-S模糊逻辑控制,实现了PMA的轨迹跟踪控制。为了保证控制系统的稳定性,采用了Lyapunov直接方法。利用Matlab的线性矩阵不等式工具箱求解线性矩阵不等式,计算状态反馈增益。最后,实验结果表明,采用遗传算法优化的T-S模糊逻辑控制能够达到理想的控制性能,克服了轨迹跟踪的抖振,有效地减小了跟踪误差,提高了控制精度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
T-S Fuzzy Logic Control with Genetic Algorithm Optimization for Pneumatic Muscle Actuator
Based on the three elements model of pneumatic muscle actuators(PMA), this paper proposed a T-S fuzzy logic control with genetic algorithm optimization and achieved the trajectory tracking control of PMA. To guarantee the stability of control system, the Lyapunov direct method was used. And the LMI Toolbox of Matlab was used in this paper to solve linear matrix inequalities(LMls) and calculate the state feedback gains. Finally, the results of experiment demonstrated that, T-S fuzzy logic control with genetic algorithm optimization can achieve desired control performance, which overcome the chattering of trajectory tracking, reduced tracking error effectively and improved the accuracy of control.
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