Dynamic output feedback RBF neural network sliding mode control for robust tracking and model following

DOI10.1007/S11071-014-1720-7zbMath1345.93063OpenAlexW2070884781MaRDI QIDQ493935

Ming-Chang Pai

Publication date: 7 September 2015

Published in: Nonlinear Dynamics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s11071-014-1720-7

zbMATH Keywords

output feedbacksliding mode control (SMC)radial basis function (RBF)tracking and modeling followingzero-tracking error

Mathematics Subject Classification ID

Feedback control (93B52) Control/observation systems governed by functional-differential equations (93C23) Robust stability (93D09) Stochastic functional-differential equations (34K50) Control problems for functional-differential equations (34K35) Analytic circuit theory (94C05) Qualitative investigation and simulation of models involving functional-differential equations (34K60)

Related Items (5)

A new adaptive control strategy for a class of nonlinear system using RBF neuro-sliding-mode technique: application to SEIG wind turbine control system ⋮ An LMI approach to adaptive robust tracker design for uncertain nonlinear systems with time-delays and input nonlinearities ⋮ Quasi-output feedback global sliding mode tracker for uncertain systems with input nonlinearity ⋮ Robust output feedback sliding mode control for uncertain discrete time systems ⋮ Robust discrete-time sliding mode control for tracking and model following of uncertain nonlinear systems

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