Cascaded predictive Speed Control Optimization Method based on Fuzzy Controller

In a high-performance motor drive system, the motor is required to have fast dynamic response and stable steady-state performance. In the traditional predictive current control, the outer loop still uses the PI controller. Its speed dynamic response is slower than the predictive speed control. Model predictive speed control can improve the dynamic performance of speed, but its steady-state performance is poor and requires high accuracy of motor parameters. At the same time, it is necessary to design a torque observer. This paper proposes an optimization method for predictive speed control based on fuzzy control. The current inner loop of this method uses the continuous control set predictive current control method. The speed outer loop uses both the PI control method and the predictive control method. The fuzzy controller is used to judge the running state of the motor, adjust the output weight of PI control and predictive control, thereby improving the control performance of the motor. The simulation and experimental results prove that the control method proposed in this paper can effectively improve the steady-state performance and robustness of predictive speed control. At the same time, there is no need to design a torque observer.