Control of a Sun Tracking Robot Based on Adaptive Sliding Mode Control with Kalman Filtering and Model Predictive Control

This paper proposes an adaptive Sliding Mode Control (SMC) strategy using a Model Predictive Control (MPC) for a two rotational joints robot to be used in a tracking problem. The considered tracking problem is the sensorless orientation of a photovoltaic panel with respect to the solar position. The estimated velocity of the sun is obtained by drawing the solar Azimuth and Elevation angle from the Application Programming Interface (API) of a German Metereological Service (meteomatics), providing real time data. The measured data are processed by an Kalman Filter (KF) to estimate the position, velocity and acceleration of the angles of the joints of the robot. The estimated and reference angles and their derivatives are used in the SMC law. Exemplary tracking results are presented at the end.