摘要
针对气动肌肉执行器(PMA)在控制中易受到模型参数不确定性影响,提出了一种基于遗传算法的T-S模糊逻辑控制器。以PMA的三元素模型为基础,建立了T-S模糊逻辑控制器;利用遗传算法在实验过程中调整和优化控制器中使用的PMA参数,从而克服了PMA参数不确定性的影响;将传统的模糊逻辑控制(FLC)、T-S模糊逻辑控制和经过遗传算法(GA)优化后的T-S模糊逻辑控制进行了对比实验。实验结果表明:采用遗传算法优化的T-S模糊逻辑控制误差范围为-2.1^+2.05 mm,优化后的T-S模糊逻辑控制克服了轨迹跟踪抖动,有效降低了跟踪误差,提高了控制精度。
Aiming at the influence of model parameters uncertainty in the control of pneumatic muscle actuator(PMA),a T-S fuzzy logic controller based on genetic algorithm is proposed.Based on the three-element model of PMA,the TS fuzzy logic controller is established.The genetic algorithm is used to adjust and optimize the PMA parameters used in the controller to overcome the influence of PMA parameter uncertainty.The traditional fuzzy logic control(FLC),TS fuzzy logic control and GA-optimized TS fuzzy logic control were compared.The experimental results show that the T-S fuzzy logic control error range optimized by genetic algorithm is-2.1^+2.05 mm.The optimized T-S fuzzy logic control overcomes the trajectory tracking jitter,effectively reduces the tracking error and improves the control precision.
作者
陈志
秦展田
韩兴国
CHEN Zhi;QIN Zhan-tian;HAN Xing-guo(School of Mechanical Engineering,Guilin University of Aerospace Technology,Guilin,Guangxi 541000)
出处
《液压与气动》
北大核心
2020年第4期47-52,共6页
Chinese Hydraulics & Pneumatics
基金
国家自然科学基金(51965014)
广西自然科学基金(2018JJA160218)。
