As a complex system with multiple variables, nonlinearity, and strong coupling, the BLDCM (Brushless Direct Current Motor) has many problems, such as bad parameter tuning, poor adaptability, low control accuracy, and weak anti-interference ability by using the double closed loop traditional PI (Proportional Integral) control algorithm. In order to obtain good control performance, a fuzzy parameter adaptive PI algorithm based on speed loop was designed by combining fuzzy control with traditional PI control. This paper analyzes the mathematical model and operating characteristics of the BLDCM and designs a fuzzy system that takes the deviation e and deviation change rate ec of the reference speed and feedback speed as input and takes the corresponding PI adjustment parameters as output. The step response of the BLDCM at different reference speeds is analyzed. The variable speed response with the initial speed of 4000 r/min under different control algorithms and the changes in the three-phase current, back electromotive force, and electromagnetic torque in this state are compared. The results show that the designed fuzzy parameter adaptive PI algorithm based on the speed loop can make the motor have a faster response time, a smaller overshoot, and a steady-state error when the motor achieves the stable operation. The proposed algorithm also has better control effect, robustness, and stable operation under variable speed conditions.

Because of its simple structure, high efficiency, low noise, and high reliability, the brushless direct current motor (BLDCM) has an irreplaceable role compared with other types of motors in many aspects. The traditional proportional integral derivative (PID) control algorithm has been widely used in practical engineering because of its simple structure and convenient adjustment, but it has many shortcomings in control accuracy and other aspects. Therefore, in this paper, a fuzzy single neuron neural network (FSNNN) PID algorithm based on an automatic speed regulator (ASR) is designed and applied to a BLDCM control system. This paper introduces a BLDCM mathematical model and its control system and designs an FSNNN PID algorithm that takes speed deviation e at different sampling times as inputs of a neural network to adjust the PID parameters, and then it uses a fuzzy system to adjust gain K of the neural network. In addition, the frequency domain stability of a double closed loop PID control system is analyzed, and the control effect of traditional PID, fuzzy PID, and FSNNN PID algorithms are compared by setting different reference speeds, as well as the change rules of three-phase current, back electromotive force (EMF), electromagnetic torque, and rotor angle position. Finally, results show that a motor controlled by the FSNNN PID algorithm has certain superiority compared with traditional PID and fuzzy PID algorithms and also has better control effects.

In order to meet the needs of modern high-performance aircraft, the fuzzy PID control strategy was used to design the electromechanical actuator control system. This control strategy combines the advantages of fuzzy control and PID control, and has better adaptability to time-varying complex systems. The electromechanical actuator control system adopted the three-loop structure, and current loop, speed loop and position loop were built on the platform of MATLAB / Simulink. Considering that the discrete universe fuzzy PID control algorithm has good real-time performance with small online computation, the fuzzy PID controller in discrete universe was designed in the position loop and the system was simulated. The simulation results show that the dynamic and steady performance of discrete universe fuzzy PID control is better than that of traditional PID control, and it is more suitable for electromechanical actuator system.

Brushless direct current motor (BLDCM) is a complicated system with multivariable, nonlinear and strong coupled. The present work devotes to design a fuzzy adaptive PID algorithm based on the speed loop so that it could crack the traditional PID problems which include bad parameter setting, poor adaptability, imprecise control and weak anti-interference so on. In this paper, the mathematical model and operating characteristics of BLDCM are analyzed. Then, the simulation platform is built by MATLAB/Simulink. Finally, the control effects of PI, PID and fuzzy adaptive PID are compared and analyzed. The results indicate that the fuzzy adaptive PID is better robustness, faster response, smaller overshoot and more stable operation than others.

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