Research On The Intelligent Optimization Control Of BLDC

The brushless DC motors (BLDCM) have small sizes, low weight, and large power to volume ratio, and receive much attention in every field. For its time-varying, nonlinear and strong coupling features, The high-performance speed control method has become an important research direction, especially the control methods based on neural network. With its control technology has become more and more mature, The high cost has become one of the main obstacles in limiting its popularization and application. Without affecting the performance of the premise, reducing costs as much as possible become another hot issue of its research.According to the basic structure of brushless DC motor, operation principle and its mathematical description, established the control system modeling simulation of BLDC based on MATLAB and fuzzy PID speed control simulation model.For its time-varying, nonlinear and strong coupling features, Research on the neural network control of Brushless DC motor. To solve the deficiency of neural network, such as decision of structure and adjustment of parameters in hidden-unit, Research on an adaptive speed control approach based on genetic algorithm optimizing Radial Basis Function (RBF) neural network controller for brushless DC motor. In this approach, the RBF neural network whose structure and parameters of hidden-unit have been trained by genetic algorithm off-line constitutes a speed loop controller. The controller tunes parameters of neural network adaptively via the self-modifiability of network on-line, while the motor is running. At the same time, the current loop controller traces the change of given current rapidly, so that the system can adapt to variational environment. Improved its speed performance.Finally, studied the research on Intelligent optimization control of four-switch three-phase brushless DC Motor, simplify the conventional six switch inverter topology. using single-neuron PID current controller, speed up the system response capacity, four-switch inverter achieved a three-phase brushless DC motor of the energy transfer, the inverter topology to simplify and reduce system cost.