Force control for press machines using an online smart tuning fuzzy PID based on a robust extended Kalman filter

Electro-hydraulic actuators (EHAs) have a wide range of applications where force or position control with high accuracy is exceedingly necessary. Among them, press machines applied hybrid EHAs are more and more used in the heavy industry. This paper presents an online smart tuning fuzzy PID (OSTFPID) approach based on a robust extended Kalman filter (REKF) for the development of high force control precision in the press machines. Here, the main control unit employs the fuzzy PID structure of which membership function (MF) optimization is considered as a system identification problem. A smart selection procedure (SSP) is implemented to pick out only fuzzy input and output MFs activated at each running step, and then the REKF algorithm is used to tune the active MFs automatically during the operation process to minimize the control error. Consequently, the active MFs are trained about their shapes and positions to adapt to the working conditions. As the result, the control performance is significantly improved, while the optimizing time and number of the controller calculations are remarkably reduced. In order to verify the ability of the proposed controller applied to the press machines using EHAs, a test press bench system called electro-hydraulic test machine (EHTM) is also suggested and setup to use in this study. Real-time experiments on the EHTM are carried out to evaluate the control method in a large variation of working environments. Considerable improvement in the performance generated by the designed controller is compared with the traditional PID and fuzzy PID controllers.