Piezoelectrics & Acoustooptics, Volume. 47, Issue 1, 157(2025)
MPC-KAN Control Method for Piezoelectric Actuators Based on GRU-NN Prediction Model
[1] [1] CHEN Gaohua, YAN Xianguo, CAI Jianghui, et al. Hysteresis nonlinear modeling and compensation of piezoelectric ceramic sensors in micro measurement systems[J]. Measurement Science and Technology, 2018, 29(9): 095102.
[2] [2] JUNG H J, ESHGHI A T, LEE S. Structural failure detection using wireless transmission rate from piezoelectric energy harvesters[J]. IEEE/ASME Transactions on Mechatronics, 2021, 26(4): 1708-1718.
[3] [3] GUO Weiping, LIU Diantong, WANG Wei. Neural network hysteresis modeling with an improved Preisach model for piezoelectric actuators[J]. Engineering Computations, 2012, 29(3): 248-259.
[4] [4] XIE S L, ZHANG Y H, CHEN C H, et al. Identification of nonlinear hysteretic systems by artificial neural network[J]. Mechanical Systems and Signal Processing, 2013, 34(1/2): 76-87.
[5] [5] CAO Kairui, HAO Guanglu, LIU Qingfeng, et al. Hysteresis modeling and compensation of fast steering mirrors with hysteresis operator based back propagation neural networks[J]. Micromachines, 2021, 12(7): 732.
[6] [6] LI Jiangang, HUANG Youhua, LI Qijie, et al. Closed-LSTM neural network based reference modification for trajectory tracking of piezoelectric actuator[J]. Neurocomputing, 2022, 467: 379-391.
[7] [7] YAN Jingyang, DIMEO P, SUN Lu, et al. LSTM-based model predictive control of piezoelectric motion stages for high-speed autofocus[J]. IEEE Transactions on Industrial Electronics, 2022, 70(6): 6209-6218.
[10] [10] LIU Ziming, WANG Yixuan, VAIDYA S, et al. KAN: Kolmogorov-Arnold networks[EB/OL]. (2024-04-30)[2024-09-30]. https: ∥arxiv.org/abs/2404.19756v4.
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GUO Chenxing, LI Zicheng, XU Ruirui. MPC-KAN Control Method for Piezoelectric Actuators Based on GRU-NN Prediction Model[J]. Piezoelectrics & Acoustooptics, 2025, 47(1): 157
Received: Oct. 22, 2024
Accepted: Apr. 17, 2025
Published Online: Apr. 17, 2025
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