Simulation of hydraulic transplanting robot control system based on fuzzy PID controller. (November 2020) - Jin, Xin; Chen, Kaikang; Zhao, Yang; Ji, Jiangtao; Jing, Pang
Highlights: Intelligent transplanting machine hydraulic control system is designed to transplant seedlings. Operation parameters can be adjusted in real time through fuzzy PID control system. The intelligent control system can improve the dynamic response speed of the hydraulic system. Abstract: At present, there is a problem that the output accuracy of the transplanting manipulator is low due to interference from external factors. To solve the problem of low output accuracy of the transplanting manipulator caused by the interference of external factors to the displacement tracking of the hydraulic seedling picking-up system, a control method of the transplanting manipulator based on the fuzzy PID control strategy is proposed. First of all, the hydraulic seedling taking system was modeled and analyzed, and the total output displacement of hydraulic cylinder piston when the valve core input displacement and external load force were acted on simultaneously was given. Then the PID control method of the hydraulic seedling picking-up system was designed, and by combining the fuzzy control theory with PID control theory, a fuzzy PID controller was designed, which was capable of on-line adjusting the PID parameters. MATLAB/Simulink was used to simulate the control system, and the control effects of conventional PID control and fuzzy PID control on the hydraulic seedling picking-up system were compared. The results showed that when k p value took 4, k i value took 10 and k d value took 0.001, the output response curve of the traditional PID control reaches a stable state in 5 s, while the fuzzy PID control only takes 2.2 s under the same conditions, successfully increasing the step response signal time of the system by 56%. The results showed that fuzzy PID control introduced helped the hydraulic seedling picking-up system to overcome its disadvantages of non-linearity and low control accuracy, and improved the stability and dynamic performance of the system.