Abstract
A novel integrated learning control system is presented in this paper. It systematically integrates discrete-time (batch-axis) information and continuous-time (time-axis) information into one uniform frame. More specifically, the iterative learning controller is designed in the domain of batch-axis, while an adaptive single neuron predictive controller (SNPC) in the domain of time-axis. In addition, the convergence and tracking performance of the proposed integrated learning control system are firstly given rigorous description and proof. Lastly, to verify the effectiveness of the proposed integrated control system, it is applied to a benchmark batch process, in comparison with ILC recently developed.
Keywords
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Jia, L., Cao, L., Chiu, M. (2013). Analysis on Data-Based Integrated Learning Control for Batch Processes. In: Li, K., Li, S., Li, D., Niu, Q. (eds) Intelligent Computing for Sustainable Energy and Environment. ICSEE 2012. Communications in Computer and Information Science, vol 355. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37105-9_15
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DOI: https://doi.org/10.1007/978-3-642-37105-9_15
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