Zhen-Yu Huo, Zhu Yang and Yan-Jun Pang. Set-point-related Indirect Iterative Learning Control for Multi-input Multi-output Systems. International Journal of Automation and Computing, vol. 9, no. 3, pp. 266-273, 2012. DOI: 10.1007/s11633-012-0643-3
Citation: Zhen-Yu Huo, Zhu Yang and Yan-Jun Pang. Set-point-related Indirect Iterative Learning Control for Multi-input Multi-output Systems. International Journal of Automation and Computing, vol. 9, no. 3, pp. 266-273, 2012. DOI: 10.1007/s11633-012-0643-3

Set-point-related Indirect Iterative Learning Control for Multi-input Multi-output Systems

  • A form of iterative learning control (ILC) is used to update the set-point for the local controller. It is referred to as set-point-related (SPR) indirect ILC. SPR indirect ILC has shown excellent performance: as a supervision module for the local controller, ILC can improve the tracking performance of the closed-loop system along the batch direction. In this study, an ILC-based P-type controller is proposed for multi-input multi-output (MIMO) linear batch processes, where a P-type controller is used to design the control signal directly and an ILC module is used to update the set-point for the P-type controller. Under the proposed ILC-based P-type controller, the closed-loop system can be transformed to a 2-dimensional (2D) Roesser's system. Based on the 2D system framework, a sufficient condition for asymptotic stability of the closed-loop system is derived in this paper. In terms of the average tracking error (ATE), the closed-loop control performance under the proposed algorithm can be improved from batch to batch, even though there are repetitive disturbances. A numerical example is used to validate the proposed results.
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