自适应伸缩因子的变论域模糊控制的AGV纠偏

AGV deviation correction of variable universe fuzzy control with adaptive expansion factor

针对自动导航车(Automated Guided Vehicle, AGV)纠偏控制响应较慢这一问题,提出了一种自适应伸缩因子的变论域模糊纠偏控制方法。建立了AGV的运动学方程,以车体位置、角度偏差为输入量,以车体转向角度为输出量,在设计模糊纠偏控制器的基础上,引入了基于函数模型的参数自适应伸缩因子,将系统误差作为输入,将伸缩因子参数作为输出,实现了伸缩因子基于函数模型的参数实时自适应调整,使模糊变论域跟随误差变化而调整,避免因变论域不恰当导致控制效果变差的问题。最后通过MATLAB环境下的Simulink仿真研究,将该控制器的纠偏控制效果与传统模糊控制、传统变论域模糊控制的纠偏控制效果进行仿真对比,验证了该控制器的纠偏控制响应更快。

Aiming at the slow response of Automated Guided Vehicle(AGV) deviation correction control, a variable universe fuzzy deviation correction control method with adaptive expansion factor was proposed.The kinematic equation of AGV was established. Taking the vehicle body position and angle deviation as the input and the vehicle body steering angle as the output, based on the design of fuzzy deviation correction controller, the parameter adaptive expansion factor based on function model was introduced.The system error was taken as the input and the parameter of expansion factor was taken as the output to realize the real-time adaptive adjustment of the parameter of expansion factor based on function model, which make the fuzzy variable universe adjust with the change of error, so as to avoid the problem of low control effect caused by improper variable universe.Finally, through the Simulink simulation in MATLAB environment, the deviation correction control effect of the controller was simulated and compared with the deviation correction control effect of traditional fuzzy control and traditional variable universe fuzzy control.It is verified that the deviation correction control response of the controller is faster.