TY - JOUR
T1 - Adaptive neural approximated inverse control for photovoltaic power generation servo systems with all states constrained
AU - Zhang, Xiuyu
AU - Gao, Yiming
AU - Liu, Yong
AU - Zhaowu, Bowen
AU - Zhang, Yanhui
AU - Zhang, Ye
AU - Zhu, Guoqiang
AU - Chen, Xinkai
N1 - Publisher Copyright:
© 2023 Elsevier Ltd
PY - 2023/12
Y1 - 2023/12
N2 - For PV power generation servo systems with motor hysteresis, an all-state constrained decentralized adaptive approximation inversion control strategy is suggested in order to further increase the tracking precision of photovoltaic (PV) panels to the sun and the efficiency of solar energy utilization. Firstly, the hysteresis phenomenon in the servo motors of photovoltaic panels is considered, and the hysteresis-approximate inverse compensator is first studied in the servo motors of photovoltaic panels. Secondly, to deal with the constrained states such as rotor angle, angular velocity, and stator current in practical servo motors, and to ensure all states are strictly confined within each set of constraints with pre-set tracking performance, the asymmetric barrier Lyapunov functions and the error transformed functions are designed. Finally, to test the effectiveness of the proposed control strategy, a hardware-in-the-loop simulation platform and a photovoltaic servo system for PV power generation are built.
AB - For PV power generation servo systems with motor hysteresis, an all-state constrained decentralized adaptive approximation inversion control strategy is suggested in order to further increase the tracking precision of photovoltaic (PV) panels to the sun and the efficiency of solar energy utilization. Firstly, the hysteresis phenomenon in the servo motors of photovoltaic panels is considered, and the hysteresis-approximate inverse compensator is first studied in the servo motors of photovoltaic panels. Secondly, to deal with the constrained states such as rotor angle, angular velocity, and stator current in practical servo motors, and to ensure all states are strictly confined within each set of constraints with pre-set tracking performance, the asymmetric barrier Lyapunov functions and the error transformed functions are designed. Finally, to test the effectiveness of the proposed control strategy, a hardware-in-the-loop simulation platform and a photovoltaic servo system for PV power generation are built.
KW - All state constrained
KW - Dynamic surface approximated inverse control
KW - Motor hysteresis
KW - Photovoltaic power generation
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U2 - 10.1016/j.conengprac.2023.105734
DO - 10.1016/j.conengprac.2023.105734
M3 - Article
AN - SCOPUS:85173261588
SN - 0967-0661
VL - 141
JO - Control Engineering Practice
JF - Control Engineering Practice
M1 - 105734
ER -