In view of the characteristics of strong coupling, non-linearity and natural instability of the balancing car and the defects of the conventional PID control, the balance is difficult and the reliability is low. This paper analyses the conventional PID control and single neuron control, the combination of value through balancing the car unit of input error, according to the rules of self learning, adjust each parameter and control links in proportion, integral and differential control, again by self-tuning fuzzy controller on the gain coefficient, thus improve the adaptive ability of the system. Finally, through MATLAB simulation, the controller proposed is compared with the conventional PID controller, which verifies the superiority of the proposed method. And the improved single neuron PID controller has better tracking performance and anti-interference capability.