基于图像视觉伺服的模糊比例积分微分控制系统

Fuzzy-proportion integration differentiation control system based on image visual servo

针对传统比例积分微分(PID)参数难整定、控制性能不理想等问题,将模糊控制理论与PID控制器相结合,构成模糊PID控制器。采用Eye-to-Hand视觉模型,引入图像视觉伺服机制,通过图像获取误差信号来实现对PID控制器三个参数Kp、Ti和Td的实时在线自适应调整。最后在以PC机、CompactRIO、NI-9401、互补金属氧化物半导体(CMOS)摄像头、电机驱动器及无刷直流(DC)电机组成的打孔机视觉伺服运动控制系统上完成了实验。结果表明,基于图像的视觉伺服模糊PID控制器相对于传统PID控制器响应速度提高了60%,超调量降低了80%,鲁棒性也更好;不仅能提高孔的定位精度,还能边加工边检测。

In view of the hard parameter tuning and unsatisfactory control performance, a fuzzy-Proportion Integration Differentiation（ fuzzy-PID） controller which combined Proportion Integration Differentiation（ PID） controller with the fuzzy control theory was proposed. The control system applied Eye-to-Hand visual model, introduced visual servo mechanism, and realized real-time, online and adaptive adjustment for three parameters Kp, Tiand Tdof the PID controller by getting errors in image. The experiment was performed on punching machine visual servo motion control system which composes of PC,compactRIO, NI-9401, Complementary Metal Oxide Semiconductor（ CMOS） camera, motor driver and brushless Direct Current（ DC） motor. The results show that, compared with traditional PID controller, the speed of response of the fuzzy-PID controller based on image visual servo is increased by 60%, the overshoot is reduced by 80%, and it has better robustness. It can not only improve the positioning accuracy of hole, but also process and detect holes nearly at the same time.