Nussbaum gain based iterative learning control for a class of multi-input multi-output nonlinear systems.
|dc.identifier.citation||Jiang, P. and Chen, H. (2005). Nussbaum gain based iterative learning control for a class of multi-input multi-output nonlinear systems. In: Proceedings of the 44th IEEE Conference on Decision and Control, and the European Control Conference 2005, Seville, Spain, December 12-15, 2005. pp. 2439- 2444.||en|
|dc.description.abstract||An adaptive iterative learning control(ILC) approach is proposed for a class of multi-input multi-output (MIMO) uncertain nonlinear systems without prior knowledge about system control gain matrices. The Nussbaum-type gain and the positive definite discrete matrix kernel are proposed for dealing with selection of the unknown control gain and learning of the repeatable uncertainties, respectively. Asymptotic convergence for a trajectory tracking within a finite time interval is achieved through repetitive tracking. Simulations are carried out to show the validity of the proposed control method.||en|
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|dc.subject||Iterative learning control (ILC)||en|
|dc.subject||Multi-input multi-output (MIMO)||en|
|dc.title||Nussbaum gain based iterative learning control for a class of multi-input multi-output nonlinear systems.||en|
|dc.type.version||published version paper||en|