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Observer-based control for time-varying delay neural networks with nonlinear observation
journal contribution
posted on 2014-01-01, 00:00 authored by V Phat, T Fernando, Hieu TrinhHieu TrinhThis paper studies the problem of designing observer-based controllers for a class of delayed neural networks with nonlinear observation. The system under consideration is subject to nonlinear observation and an interval time-varying delay. The nonlinear observation output is any nonlinear Lipschitzian function and the time-varying delay is not required to be differentiable nor its lower bound be zero. By constructing a set of appropriate Lyapunov-Krasovskii functionals and utilizing the Newton-Leibniz formula, some delay-dependent stabilizability conditions which are expressed in terms of Linear Matrix Inequalities (LMIs) are derived. The derived conditions allow simultaneous computation of two bounds that characterize the exponential stability rate of the closed-loop system. The unknown observer gain and the state feedback observer-based controller are directly obtained upon the feasibility of the derived LMIs stabilizability conditions. A simulation example is presented to verify the effectiveness of the proposed result.
History
Journal
Neural computing and applicationsVolume
24Issue
7-8Pagination
1639 - 1645Publisher
SpringerLocation
Berlin, GermanyPublisher DOI
ISSN
0941-0643eISSN
1433-3058Language
engPublication classification
C1 Refereed article in a scholarly journal; C Journal articleUsage metrics
Keywords
interval time-varying delaylinear matrix inequalitiesLyapunov-Krasovskii functionalsneural networksnonlinear observationobserver-based controlScience & TechnologyTechnologyComputer Science, Artificial IntelligenceComputer ScienceObserver based controlASYMPTOTIC STABILITYSYSTEMSDESIGNArtificial Intelligence and Image Processing
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