基于模型参考自适应的AGV运动控制系统设计

为了消除自动导航车（AGV）麦克纳姆驱动轮间负载不均衡引起的控制系统不确定性问题，提出基于模型参考自适应控制（MRAC）的伺服控制方法. 建立驱动轮伺服电机的数学模型，根据李雅普诺夫稳定理论求解MRAC控制律和自适应律，并确定自适应律算法的正定矩阵. 根据AGV实际运行过程中伺服电机的频率特性，引入低通滤波器. 综合AGV定位精度和MRAC系统稳定性，确定二阶巴特沃兹低通滤波器的截止频率. 在保证控制系统稳态精度的同时，有效抑制高频振荡. 实验结果表明：基于MRAC的AGV在复杂工况下的控制性能保持了较高的稳定性，每个电机的速度波动不超过3%，定位精度误差小于3.6 mm.

Design of AGV motion control system based on model reference adaptive method

A servo control method based on model reference adaptive control (MRAC) was proposed, to eliminate the control system uncertainty which was caused by the unbalanced load between the Mecanum wheels of the automated guided vehicle (AGV) system. The mathematical model of the driving wheel servo motor was established. The control law and adaptive law of MRAC were acquired by Lyapunov method, and the positive definite matrix of the adaptive law was determined. According to the frequency characteristics of the servo motor during the operation of the AGV, a low-pass filter was introduced. The cut-off frequency of the second-order Butterworth low-pass filter was determined by the positioning accuracy of the AGV and the stability of the MRAC system. The high frequency oscillation of the control system was effectively suppressed and the high steady-state accuracy was achieved. Experimental results show that the control performance of the AGV based on MRAC achieves a high stability under complex working conditions. The speed error of each motor is controlled within 3%, and the positioning accuracy error is less than 3.6 mm.