Single neuron adaptive controller for brushless DC motor control system

To overcome the effects of nonlinearity and varying parameters, the adaptive PID controller with single neuron suited to the control system of the brushless DC motor was studied. The learning algorithm was presented and the adaptive function was implemented by adjustment of the weighting values. The comparisons of both linear and nonlinear single neuron PID controllers were performed. The analysis and simulation results have shown that the linear controller is superior to the nonlinear controller in response speed, robustness, adaptation and real time control.