Based On Fnn Brushless Dc Motor Control Devices And Speed Stabilization Technology

With the rapid development of micro-electronics and electromotor technology, Brushless DC motor as a new type motor is becoming more and more popular in recent years. By means of power electronics circuit to control over commutation instead of traditional mechanical methods, Brushless DC motor which not only has the merits of the AC induction motor of reliable operation, simple structure and easy upholding but also has the merit of the DC motor high running efficiency, good timing performance, nice control characteristic and without wasting excitation, has applied widely in many scopes. To overcome a lot of disadvantages generated by the sensor and expand the application range of Brushless DC motor further, sensorless control has draw lots of attention of control technique for Brushless DC motor.Because of Brushless DC motor has the features of time-varying, strong coupling and linearity, although traditional control methods are of fast performance and precise control, it is difficult to meet the needs of static state and dynamic performance when the model of control subjects is uncertain. Fuzzy neural network control does not depend on exact match models and can restrain the impact of time varying and parameter disturbance etc. In order to solve the problems above, this thesis designs a algorithm which is for modifying the fuzzy control demand table on line by single neuron at the base of easy fuzzy control algorithm.Begin with the dissertation introducing the base elements, working principle, operating characteristic and transfer function of the Brushless DC motor, then it presents the disadvantages of sensor control. For detail, the principle and methods of sensorless control technology. On the base of these, the dissertation analyses the matter of speed ripple and compare with various detection technologies of sensorless position, then it chooses Back EMF zero-detecting to design the system of sensorless Brushless DC motor control using the AT89C2051 chip. In addition, according to the factual require, the dissertation discusses in detail the questions of how to start, exchange phase and keep speed steadily running at the condition of sensorless. Then it designs the system of hardware, software correspondingly.However, during the course of design, there are some problems on the structure and learning arithmetic of fuzzy neural network. The thesis offers some proving methods and theory deduction in detail as well as the Contrastive simulation results to demonstrate its control feature. After the simulation of MATLAB, it is evident that the fuzzy neural network control which is using the speed control of sensorless Brushless DC motor can make the control system having good static state and dynamic performance, and meet the need of speed stability to some degree. In the course of comparing with the wave form experimental detection, the results achieve its aim and require, and can satisfy us.