Investigate Model Reference Controller for Sun-Seeker Tracking System Based on Neural Network

Abstract

Neural network are appropriate for the modeling and control of multifaceted physical systems because of their capability to manage multifaceted input-output charting without thorough mathematical model of the systems. Demonstrating a non-linear active charting, Model Reference Controller Neural Network (MRCNN) is appropriate to manage active non-linear complications. In this paper, a MRCNN have employed in a sun-seeker tracking system. First, the MRCNN will be used as identifier to recognize the opposite model of the system to be controlled through supervised, and then the MRCNN is used such as a feed forward controller, to create control voltage to power the sun-seeker to track pre-selected routes of location.