ELM-based adaptive backstepping neural control for a class of uncertain MIMO nonlinear systems with predefined tracking accuracy

DOI10.1080/00207179.2013.865277zbMath1291.93161OpenAlexW2039435931MaRDI QIDQ5494518

Weisheng Chen, Yasser Elkoteshy, Li-Cheng Jiao

Publication date: 28 July 2014

Published in: International Journal of Control (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00207179.2013.865277

zbMATH Keywords

adaptive backstepping designBarbalat's lemmaMIMO nonlinear systemELM-based SLFNN

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Neural networks for/in biological studies, artificial life and related topics (92B20) Nonlinear systems in control theory (93C10) Multivariable systems, multidimensional control systems (93C35) Adaptive control/observation systems (93C40) Stability of control systems (93D99)

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Cites Work

• Approximation-based control of nonlinear MIMO time-delay systems
• An ISS-modular approach for adaptive neural control of pure-feedback systems
• Novel adaptive neural control design for nonlinear MIMO time-delay systems
• Adaptive dynamic surface control of nonlinear systems with unknown dead zone in pure feedback form
• Adaptive neural control of MIMO nonlinear state time-varying delay systems with unknown dead-zones and gain signs
• Adaptive control of a class of discrete-time MIMO nonlinear systems with uncertain couplings
• Systematic design of adaptive controllers for feedback linearizable systems
• Stable adaptive control for nonlinear multivariable systems with a triangular control structure
• Direct Adaptive Control for a Class of MIMO Nonlinear Systems Using Neural Networks
• Adaptive Output Control of Nonlinear Systems With Uncertain Dead-Zone Nonlinearity

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