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融合光纤感知的气动执行器夹持力控制策略研究

Clamping Force Control Strategy of a Pneumatic Actuator Based on Fiber Sensing
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摘要 为了降低气动执行器夹持力/气压迟滞的影响,提高夹持力跟踪控制精度,提出一种基于Prandtl-Ishlinskii(P-I)逆模型的前馈补偿结合模糊PID的控制策略。分析气动执行器的夹持力/气压迟滞特性,通过初载曲线法辨识迟滞模型参数,建立P-I逆模型;设计融合FBG力感知的模糊PID控制算法,基于自制的FBG传感器实现夹持力反馈,通过标定实验验证传感器的静态特性。在Simulink中构建前馈补偿和融合FBG力感知的模糊PID相结合的复合控制器,完成与传统PID以及模糊PID控制器的夹持力控制仿真对比。仿真结果显示:前馈补偿可以降低稳态误差,提高控制精度。最后,在气动执行器夹持力控实验平台上开展动态跟踪实验,验证了所设计复合控制器的有效性。 A control algorithm combining feedforward hysteresis compensation based on Prandtl-Ishlinskii(P-I)inverse model and fuzzy PID was proposed to reduce the influence of clamping force/pressure hysteresis on a pneumatic actuator and improve the clamping force tracking control accuracy.The clamping force/pressure hysteresis characteristics of the pneumatic actuator were analyzed.The hysteresis model parameters were identified by the initial load curve method to establish P-I inverse model.A fuzzy PID control al⁃gorithm based on FBG force sensing was designed.The clamping force feedback was realized based on the self-made FBG sensor.The static characteristics of the sensors were verified by calibration experiment.Furthermore,a compound controller combined with feedfor⁃ward compensation and fuzzy PID fused with FBG force sensing was constructed to complete the simulation comparison with the tradi⁃tional PID and fuzzy PID controller of clamping force control in Simulink.Simulation results show that feedforward hysteresis compensa⁃tion can reduce steady-state error and improve control accuracy.Finally,the dynamic tracking experiment was carried out on the pneu⁃matic actuator clamping force control experimental platform.The effectiveness of the designed composite controller was verified.
作者 李天梁 王量 裴青峰 LI Tianliang;WANG Liang;PEI Qingfeng(School of Mechanical and Electronic Engineering,Wuhan University of Technology,Wuhan Hubei 430070,China)
出处 《机床与液压》 北大核心 2024年第4期13-18,26,共7页 Machine Tool & Hydraulics
基金 湖北省重点研发计划(2022BAA066) 国家自然科学基金青年科学基金项目(51905398)。
关键词 气动执行器 迟滞补偿 模糊PID控制 FBG力感知 pneumatic actuator hysteresis compensation fuzzy PID control FBG force sensing
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