Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/72436
Title: A composite energy function based sub-optimal learning control approach for nonlinear systems with time-varying parametric uncertainties
Authors: Ying, T.
Xu, J. 
Issue Date: 2000
Source: Ying, T.,Xu, J. (2000). A composite energy function based sub-optimal learning control approach for nonlinear systems with time-varying parametric uncertainties. Proceedings of the IEEE Conference on Decision and Control 4 : 3837-3842. ScholarBank@NUS Repository.
Abstract: In this paper, a novel composite energy function (CEF) is introduced to provide a general framework for incorporating system information along both time and learning repetition horizon. Based on the CEF, learning control is integrated with nonlinear sub-optimal control to enhance control performance for a class of nonlinear system with time-varying parametric uncertainties. Sub-optimal control strategy based on control Lyapunov function (CLF) and Sontag's formula provides a sub-optimal performance as well as stability along time horizon for the nominal part of the nonlinear dynamic system. Learning mechanism tries to learn unknown time-varying parametric uncertainties so as to eliminate uncertain effects. The proposed control scheme achieves asymptotical convergence along learning repetition horizon. At the same time, the boundedness and pointwise convergence of the tracking error along time horizon are also ensured.
Source Title: Proceedings of the IEEE Conference on Decision and Control
URI: http://scholarbank.nus.edu.sg/handle/10635/72436
ISSN: 01912216
Appears in Collections:Staff Publications

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