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Volume 7 Issue 3
Apr.  2020

IEEE/CAA Journal of Automatica Sinica

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Jianxiang Zhang, Baotong Cui, Xisheng Dai and Zhengxian Jiang, "Iterative Learning Control for Distributed Parameter Systems Based on Non-Collocated Sensors and Actuators," IEEE/CAA J. Autom. Sinica, vol. 7, no. 3, pp. 865-871, May 2020. doi: 10.1109/JAS.2019.1911663
Citation: Jianxiang Zhang, Baotong Cui, Xisheng Dai and Zhengxian Jiang, "Iterative Learning Control for Distributed Parameter Systems Based on Non-Collocated Sensors and Actuators," IEEE/CAA J. Autom. Sinica, vol. 7, no. 3, pp. 865-871, May 2020. doi: 10.1109/JAS.2019.1911663

Iterative Learning Control for Distributed Parameter Systems Based on Non-Collocated Sensors and Actuators

doi: 10.1109/JAS.2019.1911663
Funds:  This work was supported by National Natural Science Foundation of China (61807016) and Postgraduate Research and Practice Innovation Program of Jiangsu Province (KYCX18-1859)
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  • In this paper, an open-loop PD-type iterative learning control (ILC) scheme is first proposed for two kinds of distributed parameter systems (DPSs) which are described by parabolic partial differential equations using non-collocated sensors and actuators. Then, a closed-loop PD-type ILC algorithm is extended to a class of distributed parameter systems with a non-collocated single sensor and m actuators when the initial states of the system exist some errors. Under some given assumptions, the convergence conditions of output errors for the systems can be obtained. Finally, one numerical example for a distributed parameter system with a single sensor and two actuators is presented to illustrate the effectiveness of the proposed ILC schemes.

     

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    Highlights

    • We first propose the open-loop PD-type ILC scheme for a class of parabolic distributed parameter system with non-collocated sensors and actuators.
    • Then, we present a closed-loop PD-type ILC algorithm for the distributed parameter system using single sensor and multiple actuators when some errors are identified in the initial states of the system.
    • This study enhances the performance of parabolic distributed parameter system using non-collocated sensors and actuators.
    • The simulation results demonstrate the effectiveness of the proposed schemes.

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