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Article Navigation >  IEEE/CAA Journal of Automatica Sinica  > 2025  > In Press, Accepted Manuscript
I. Hussain, X. Ruan, C. Liu, and B. Li, “Data-driven adaptive p-type iterative learning control for linear discrete time singular systems,” IEEE/CAA J. Autom. Sinica, 2025. doi: 10.1109/JAS.2024.125040
Citation: I. Hussain, X. Ruan, C. Liu, and B. Li, “Data-driven adaptive p-type iterative learning control for linear discrete time singular systems,” IEEE/CAA J. Autom. Sinica, 2025. doi: 10.1109/JAS.2024.125040
shu

Data-Driven Adaptive P-type Iterative Learning Control for Linear Discrete Time Singular Systems

doi: 10.1109/JAS.2024.125040
Funds:  This work was supported by National Natural Science Foundation of China (619733380
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    Abstract
  • Aiming at the pulse response sequence of a kind of repetitive linear discrete-time singular systems unavailable, the paper explores a data-driven adaptive iterative learning control (DDAILC) strategy that interacts with the pulse response iterative correction(PRIC). The mechanism is to formulate the correction performance index as a linear summation of the quadratic correction error of the pulse response and the quadratic tracking error. The correction algorithm of the pulse response arrives and the correction error goes down in a monotonic way. It also discusses the conditional relationship between the declining rate of the correction error and the correction ratio. A DDAILC algorithm is designed by means of substituting the exact pulse response of the GOILC with its approximated one updated in the correction algorithm. The convergences regarding tracking error and correction error are obtained monotonically. Finally, numerical simulation verifies the validity and effectiveness.

     

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