Development of Neuro Controller for Negative Output Self-Lift Luo Converter

The present work deals with the application of neuro control theory for the closed loop operation of negative output self-lift Luo converter, which is a newly developed DC-DC converter. Due to the time-varying and switching nature of the power electronic converters, their dynamic behavior becomes highly non-linear. Conventional controllers are incapable of providing good dynamic performance and hence neural network can be utilized as a feedforward controller for controlling power electronic converters. The neuro controller presented in this work is off-line trained using quasi-Newton backpropagation algorithm. The performances of the chosen Luo converter with neuro control are evaluated in this paper (using MATLAB coding) under load and line disturbances. The simulation results are presented. They validate the neuro control developed