Abstract: In order to implement high precision position tracking controlling for the brushless DC motor(BLDCM)， a CFNNC (compensation fuzzy neural network controller) algorithm was proposed based on the multivariable， nonlinearity， strong coupling， time-variable characteristics of position servo system. The compensative fuzzy logic and neural network were combined in the proposed algorithm， which could not only adjust the input and output of fuzzy membership functions， but also optimize the fuzzy inference dynamically by using the logic compensation algorithm. The fault tolerance， stability and working speed of the network were improved greatly due to the introduction of fuzzy neuron. The simulation and experiment results of DSP-based control system illustrated that this method has rapid response， high precision and robustness， and its dynamic characteristic was much better than that of traditional PID controller.

Key words: BLDCM(brushless DC motor), CFNNC (compensation fuzzy neural network controller), position servo system, mathematical model, DSP control system