A fuzzy control algorithm reducing steady-state position errors of robotic manipulators

C. Kang, Hee-Sung Kwak
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引用次数: 3

Abstract

Conventional fuzzy controllers for the motion tracking of robotic manipulators utilize two input variables, position errors and velocity errors, to deal with highly nonlinear and time-varying dynamics associated with robot motion, and position errors usually remain at steady state conditions. In order to eliminate the steady state position errors, a new fuzzy control algorithm is proposed using three input variables of the fuzzy controller: position error, velocity error, and integral of position errors. Simulation and experiment studies show that the position errors at steady state are decreased more than 90% compared to those of conventional fuzzy control when the proposed fuzzy control is applied to the 2-axis direct-drive SCARA robot.
一种减少机械臂稳态位置误差的模糊控制算法
传统的机器人运动跟踪模糊控制器利用位置误差和速度误差两个输入变量来处理与机器人运动相关的高度非线性和时变动力学,并且位置误差通常保持在稳态条件下。为了消除稳态位置误差,提出了一种新的模糊控制算法,该算法使用模糊控制器的三个输入变量:位置误差、速度误差和位置误差积分。仿真和实验研究表明,将所提出的模糊控制应用于2轴直驱SCARA机器人的稳态位置误差比传统模糊控制方法降低了90%以上。
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