Data driven- adaptive single neuron predictive controller based on Lyapunov approach

Please use this identifier to cite or link to this item: https://doi.org/10.1109/WCICA.2011.5970724

Title:	Data driven- adaptive single neuron predictive controller based on Lyapunov approach
Authors:	Jia, L. Cao, L. Chiu, M.
Keywords:	Lyapunov approach neuron predictive controller PID controller
Issue Date:	2011
Citation:	Jia, L.,Cao, L.,Chiu, M. (2011). Data driven- adaptive single neuron predictive controller based on Lyapunov approach. Proceedings of the World Congress on Intelligent Control and Automation (WCICA) : 7-12. ScholarBank@NUS Repository. https://doi.org/10.1109/WCICA.2011.5970724
Abstract:	In this paper, a novel data driven-adaptive single neuron predictive controller is proposed. The self-tuning algorithm for the single neuron predictive controller is derived by a rigorous analysis based on the Lyapunov method such that the predicted tracking error convergences asymptotically. Simulation results are presented to illustrate the proposed adaptive predictive controller and a comparison with its conventional counterparts is made. © 2011 IEEE.
Source Title:	Proceedings of the World Congress on Intelligent Control and Automation (WCICA)
URI:	http://scholarbank.nus.edu.sg/handle/10635/74530
ISBN:	9781612847009
DOI:	10.1109/WCICA.2011.5970724
Appears in Collections:	Staff Publications

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