Abstract
This paper aims to improve the steel liquid level control quality via iterative learning control (ILC) with extended error information. The ILC is one kind of type P iterative learning control, and besides the forgetting factor and the on-off switching action, error information was further extended on account of introduction of the just past and the second past cycles error signals. Results demonstrated that, the control quality can still be improved even under the model uncertainties, periodic bulging disturbances, the measuring noises, as well as the input signal error, the state error and the output error can be guaranteed to be ultimately bounded. Simulation results were provided to clarify the suggested idea further.
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Acknowledgments
The author would like to express his appreciation for his graduate student Xu Zhao, for his laborious work towards this paper. This work is also supported in part by National Science Foundation of China (61340041 and 61374079), and The Project-sponsored by SRF for ROCS, SEM to Yunzhong Song.
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Song, Y. (2016). Steel Liquid Level Tracking Via Iterative Learning with Extended Error Information. In: Jia, Y., Du, J., Li, H., Zhang, W. (eds) Proceedings of the 2015 Chinese Intelligent Systems Conference. Lecture Notes in Electrical Engineering. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-48365-7_26
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DOI: https://doi.org/10.1007/978-3-662-48365-7_26
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