气动轨迹自适应s型摩擦补偿性能评价

K. N. Kamaludin, L. Abdullah, S. Salim, Z. Jamaludin, T. H. Chiew, M. N. Kamarudin, M. Aras, M. F. Rahmat
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引用次数: 0

摘要

轨迹跟踪是一项具有挑战性的任务,在气动由于分类的执行器作为一个非线性系统。除了上述因素外,系统内部还存在非线性扰动,如阀死区、空气可压缩性、空气密度、阀内部和执行器摩擦等。执行机构的内摩擦是最关键的扰动之一。针对执行机构的近零速度运动,许多学者设计并改进了动态摩擦模型,用于建模和摩擦补偿。然而,使用动态模型进行补偿是复杂的,并且在实时情况下计算是彻底的。基于这一因素,本文提出了一种改进的自适应摩擦估计器和补偿器。设计了自适应s型摩擦(FASF)函数来补偿摩擦力的预滑动和滑动状态。该函数与非线性双曲PID (NPID+FASF)控制器耦合。基于最大跟踪误差(MTE)、均方根误差(RMSE)和快速傅立叶变换(FFT)误差对补偿器的性能进行了评价。观察到所提出的NPID+FASF策略可以减少所有错误。MTE对基本PID的改善达45.75%,RMSE为27.88%,FFTE为38.91%。为了进一步提高弹道跟踪性能,“跟踪微分器”被证明可以提高弹道跟踪和精确定位的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Performance Evaluation of an Adaptive Sigmoid Friction Compensation for Pneumatic Trajectory
Trajectory tracking is a challenging task in pneumatics due to the classification of the actuator as a nonlinear system. In addition to the said factor, nonlinear disturbances occur within the system, such as valve-dead zone, air compressibility, air density, internal valve and actuator friction. Actuators' internal friction is one of the most critical disturbances. For a near-zero velocity motion of an actuator, many scholars have designed and improved dynamic friction models for modeling and friction compensation. However, compensation using the dynamic model is complex and computationally exhaustive in real-time. Owing to this factor, a modified adaptive friction estimator and compensator are presented in this research. The adaptive sigmoid friction (FASF) function is designed to compensate both the pre-sliding and sliding regimes of the friction force. The function is coupled with a nonlinear hyperbolic PID (NPID+FASF) controller. The performance of the compensator was evaluated based on maximum tracking error (MTE), root mean square error (RMSE) and fast Fourier transform (FFT) error. The proposed NPID+FASF is observed to reduce all errors strategically. The improvement of MTE to the basic PID is up to 45.75%, RMSE of 27.88% and FFTE of 38.91%. To further improve the trajectory tracking performance, a ‘tracking differentiator’ has been proven to increase the performance of trajectory tracking and precise positioning.
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