HARDWARE IMPLEMENTATION OF A NEURALNETWORK CONTROLER WITH AN MCU AND AN FPGA FOR A NONLINEAR SYSTEM

Abstract

This paper presents the hardware implementation of a neural network controller for a nonlinear system. As a learning algorithm for a neural network, the reference compensation technique has been implemented on a low cost micro-controller unit (MCU), while PID controllers with counters and PWM generators are implemented on an FPGA chip. Interface between an MCU and a field programmable gate array (FPGA) chip has been developed to complete hardware implementation of a neural controller. The neural controller has been tested for controlling the inverted pendulum as a nonlinear system. Reference compensation technique