An experimental neural controller implementing a VSC for a DC/DC PWM converter with power factor corrector

An experimental neural controller implementing a variable structure control (VSC) algorithm is proposed for a power factor corrector. VSC control laws yield fast response and a robust behavior against large parameters variations. A multilayer perceptron learns through backpropagation to approximate the desired control function. An simple analog electronic realization of this neural network using discrete operational amplifiers is proposed. This implementation possesses all the good properties of sliding mode while avoiding the unnecessary discontinuities of the control input and thus eliminating chattering. A simple analog electronic implementation of this controller is proposed. Experimental results are summarized confirming the validity of the neural network approach.