Designing a Novel Adaptive Regulator for Nonlinear Converters

In this paper, a new adaptive self tuning PID output voltage regulator based on Fuzzy Wavelet Neural Network (FWNN) model is proposed for the DC-to-DC Cuk converter with nonlinear dynamic. The auto regulator is made by a combination of static fuzzy wavelet neural network structure and a PID controller. Tuning rule is accomplished based on gradient descent method for minimizing a compound of control error and identification error. This tuning rule is arranged such as to increase the precision of output voltage regulation. Beside of very well control results, the simple proposed regulator is capable of being robust with disturbances or some kinds of uncertainty. To investigate the performance of proposed method some numerical results are presented on a DC-to-DC Cuk converter with unknown structures. The simulation studies show that the designed controller has good capability to solve the output voltage regulation problem for the DC-to-DC Cuk converter.

Keywords:

Fuzzy wavelet neural network , Self tuning PID controller , Gradient descent , DC-to-DC Cuk converter