基于模糊类神经网络的双轴伺服电机运动控制

Motion Control of Dual Axis Servo Motor Based on Fuzzy Neural Network

为了消除双轴线性伺服电机同步运动的相对速度误差,提出模糊类神经网络控制器,以取代传统的比例-积分-微分交叉耦合控制器。首先对双轴线性伺服电机系统进行建模,其次采用2个模糊类神经网络速度控制器提供需要的控制动作,以保持双轴线性伺服电机同步运动且追随速度命令。仿真结果证明,该控制方法在无载和有载时分别在0.4 s和0.5 s后两电机速度相对误差几乎为零,可适应的速度范围宽且对负载干扰具有高鲁棒性。

To eliminate the relative velocity error of the synchronous motion for the dual axis linear servo motor, the fuzzy neural network controller was proposed to replace the traditional cross coupling controller of proportionalintegral- differential. Firstly,the dual axis linear servo motor system was built. Then two fuzzy neural network speed controllers were used to provide the required control action,which kept synchronous motion and tracked speed command of a dual axis linear servo motor. The simulation shows that the relative speed error of the two motors is almost zero after 0.4 s and 0.5 s under unloaded and loaded condition by the proposed control method,respectively. In addition,the adaptable speed range is wide and the load interference is highly robust for the proposed method.