New Control Method of Adaptive Fuzzy-Neural Networks for Brushless D\^C\^ Motor

This control method was based on combining fuzzy control with adaptive and bang-bang control. Fuzzy controller and mechanism are realized by neural networks. In double closed loop system the current regulator consists of proportional and integral controller, the speed regulator consists of bang-bang controller and fuzzy controller combining with adaptive mechanism. Fuzzy controller is realized by three layers of neural networks, which learns off the line. Improved BP algorism is used to learn. Adaptive mechanism is realized by an artificial neuron, which dynamically learns on the line during the operation of the system. The superintendence Hebb algorism is used to learn. Operation stage of the motor resolves which controller to work. It-s shown by the results of digital simulation that the system has good dynamic and static performance, it also has excellent adaptive performance.