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

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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.

Original languageEnglish
Title of host publicationIECON 2021 - 47th Annual Conference of the IEEE Industrial Electronics Society
Number of pages6
Place of PublicationPiscataway
PublisherIEEE - Institute of Electrical and Electronics Engineers Inc.
Publication date13.10.2021
ISBN (Print)978-1-6654-0256-9
ISBN (Electronic)978-1-6654-3554-3
Publication statusPublished - 13.10.2021
Event47th Annual Conference of the IEEE Industrial Electronics Society - virtuell, Toronto, Canada
Duration: 13.10.202116.10.2021
Conference number: 47

    Research areas

  • Kalman filter, Lyapunov, Model predictive control, Robot, Sliding Mode Control, Sun Tracking
  • Engineering