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IEEE/CAA Journal of Automatica Sinica

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T. Mu, H. Guo, C. Bai, and Z.-H. Pang, “Data-driven adaptive PID tracking control of a class of nonlinear systems,” IEEE/CAA J. Autom. Sinica, vol. 12, no. 6, pp. 1–3, Feb. 2025.
Citation: T. Mu, H. Guo, C. Bai, and Z.-H. Pang, “Data-driven adaptive PID tracking control of a class of nonlinear systems,” IEEE/CAA J. Autom. Sinica, vol. 12, no. 6, pp. 1–3, Feb. 2025.

Data-Driven Adaptive PID Tracking Control of a Class of Nonlinear Systems

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  • [1]
    J. Sun, Y. Zhang, Y. Chang, T. Shen, and S. Ding, “Fixed-time composite learning fuzzy control with disturbance rejection for uncertain engineering systems toward Industry 5.0,” IEEE Trans. Syst. Man Cybern.: Syst., vol. 54, no. 7, pp. 4077–4088, Jul. 2024. doi: 10.1109/TSMC.2024.3373471
    [2]
    Z. Hou and S. Xiong, “On model-free adaptive control and its stability analysis,” IEEE Trans. Autom. Control, vol. 64, no. 11, pp. 4555–4569, Nov. 2019. doi: 10.1109/TAC.2019.2894586
    [3]
    Z. Hou, and Y. Zhu, “Controller-dynamic-linearization-based model free adaptive control for discrete-time nonlinear systems,” IEEE Trans. Ind. Inf., vol. 9, no. 4, pp. 2301–2309, Nov. 2013. doi: 10.1109/TII.2013.2257806
    [4]
    Z.-H. Pang, B. Ma, G.-P. Liu, and Q.-L. Han, “Data-driven adaptive control: An incremental triangular dynamic linearization approach,” IEEE Trans. Circuits Syst. II Express Briefs, vol. 69, no. 12, pp. 4949–4953, Dec. 2022.
    [5]
    C. Zhao and L. Guo, “Towards a theoretical foundation of PID control for uncertain nonlinear systems,” Automatica, vol. 142, p. 110360, Aug. 2022. doi: 10.1016/j.automatica.2022.110360
    [6]
    H. Yu, Z. Guan, T. Chen, and T. Yamamoto, “Design of data-driven PID controllers with adaptive updating rules,” Automatica, vol. 121, p. 109185, Nov. 2020. doi: 10.1016/j.automatica.2020.109185
    [7]
    Q. Yang, F. Zhang, and C. Wang, “Deterministic learning-based neural PID control for nonlinear robotic systems,” IEEE/CAA J. Autom. Sinica, vol. 11, no. 5, pp. 1227–1238, May 2024. doi: 10.1109/JAS.2024.124224
    [8]
    C. Wang, X. Huo, K. Ma, and R. Ji, “PID-Like model free adaptive control with discrete extended state observer and its application on an unmanned helicopter,” IEEE Trans. Ind. Inf., vol. 19, no. 11, pp. 11265–11274, Nov. 2023. doi: 10.1109/TII.2023.3245223
    [9]
    Y. Cao and Y.-D. Song, “Adaptive PID-like fault-tolerant control for robot manipulators with given performance specifications,” Int. J. Control, vol. 93, no. 3, pp. 377–386, May 2018.
    [10]
    Z.-H. Pang, L.-Z. Fan, H. Guo, Y. Shi, R. Chai, J. Sun, and G.-P. Liu, “Security of networked control systems subject to deception attacks: A survey,” Int. J. Syst. Sci., vol. 53, no. 16, pp. 3577–3598, Nov. 2022. doi: 10.1080/00207721.2022.2143735
    [11]
    Z.-H. Pang, T. Du, S. Gao, Q.-L. Han, and G.-P. Liu, “Cooperative tracking control of networked multiagent systems: A dual-prediction plus correction approach,” IEEE Trans. Ind. Inf., vol. 21, no. 1, pp. 146–155, Jan. 2025. doi: 10.1109/TII.2024.3441648

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