Stable Adaptive Control of A Class of Nonlinear Dynamic Systems Using RBF Networks

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Original languageEnglish
Pages (from-to)15-26
Journal / PublicationIntelligent Automation and Soft Computing
Issue number1
Publication statusPublished - 1996
Externally publishedYes


Based on Radial Basis Function neural networks, a stable adaptive control scheme is proposed for a class of unknown nonlinear dynamic systems. It is shown that the scheme is stable and convergent in the sense that all the signal in the loop remain bounded, and in the ideal case, output tracking error will converge to zero and in the non-ideal case, the error will converge to a residue which is proportional to the modelling error bound. Simulation results are also provided to demonstrate performance of the scheme. 

Research Area(s)

  • Adaptive control, Neural networks, Nonlinear systems, Radial basis functions, Stability