Control of a Sun Tracking Robot Based on Adaptive Sliding Mode Control with Kalman Filtering and Model Predictive Control
Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review
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IECON 2021 - 47th Annual Conference of the IEEE Industrial Electronics Society. Piscataway: IEEE - Institute of Electrical and Electronics Engineers Inc., 2021. (IECON Proceedings (Industrial Electronics Conference); Vol. 2021-October).
Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review
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TY - CHAP
T1 - Control of a Sun Tracking Robot Based on Adaptive Sliding Mode Control with Kalman Filtering and Model Predictive Control
AU - Rehbein, Jan Philip
AU - Haus, Benedikt
AU - Mercorelli, Paolo
N1 - Conference code: 47
PY - 2021/10/13
Y1 - 2021/10/13
N2 - 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.
AB - 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.
KW - Kalman filter
KW - Lyapunov
KW - Model predictive control
KW - Robot
KW - Sliding Mode Control
KW - Sun Tracking
KW - Engineering
UR - http://www.scopus.com/inward/record.url?scp=85119505003&partnerID=8YFLogxK
UR - https://www.mendeley.com/catalogue/841f091e-33bc-3a02-a209-b222e7b8c85c/
U2 - 10.1109/IECON48115.2021.9589081
DO - 10.1109/IECON48115.2021.9589081
M3 - Article in conference proceedings
AN - SCOPUS:85119505003
SN - 978-1-6654-0256-9
T3 - IECON Proceedings (Industrial Electronics Conference)
BT - IECON 2021 - 47th Annual Conference of the IEEE Industrial Electronics Society
PB - IEEE - Institute of Electrical and Electronics Engineers Inc.
CY - Piscataway
T2 - 47th Annual Conference of the IEEE Industrial Electronics Society
Y2 - 13 October 2021 through 16 October 2021
ER -