Adaptive neural control of MIMO stochastic systems with unknown high-frequency gains

DOI10.1016/j.ins.2017.08.027zbMath1447.93164OpenAlexW2744475817MaRDI QIDQ780938

Yun Zhang, Zhi Liu, Kan Xie, Ci Chen, C. L. Philip Chen

Publication date: 16 July 2020

Published in: Information Sciences (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.ins.2017.08.027

zbMATH Keywords

adaptive neural controlunknown control direction\textit{MIMO} stochastic systemhigh-frequency gains

Mathematics Subject Classification ID

Nonlinear systems in control theory (93C10) Multivariable systems, multidimensional control systems (93C35) Adaptive control/observation systems (93C40) Stochastic systems in control theory (general) (93E03)

Related Items (1)

Control with prescribed performance tracking for input quantized nonlinear systems using self-scrambling gain feedback

Cites Work

• Unnamed Item
• Global adaptive neural control for strict-feedback time-delay systems with predefined output accuracy
• Adaptive fuzzy control for a class of unknown nonlinear dynamical systems
• Fuzzy adaptive high-gain-based observer backstepping control for SISO nonlinear systems
• Remarks on adaptive stabilization of first order nonlinear systems
• Some remarks on a conjecture in parameter adaptive control
• Design of a fuzzy adaptive controller for MIMO nonlinear time-delay systems with unknown actuator nonlinearities and unknown control direction
• Barrier Lyapunov functions-based adaptive control for a class of nonlinear pure-feedback systems with full state constraints
• Observer-based adaptive fuzzy decentralized control for stochastic large-scale nonlinear systems with unknown dead-zones
• Decentralized adaptive fuzzy output feedback control of stochastic nonlinear large-scale systems with dynamic uncertainties
• Containment control of networked autonomous underwater vehicles with model uncertainty and ocean disturbances guided by multiple leaders
• Hybrid adaptive fuzzy control for uncertain MIMO nonlinear systems with unknown dead-zones
• Adaptive consensus output regulation of a class of nonlinear systems with unknown high-frequency gain
• Adaptive fuzzy control of uncertain stochastic nonlinear systems with unknown dead zone using small-gain approach
• Adaptive neural tracking control for stochastic nonlinear strict-feedback systems with unknown input saturation
• Adaptive backstepping control design for systems with unknown high-frequency gain
• Razumikhin-Nussbaum-lemma-based adaptive neural control for uncertain stochastic pure-feedback nonlinear systems with time-varying delays
• Adaptive Consensus of Multi-Agent Systems With Unknown Identical Control Directions Based on A Novel Nussbaum-Type Function
• A nonlinear universal servomechanism
• Adaptive nonlinear design without a priori knowledge of control directions
• Adaptive control of non-linear systems with unknown virtual control coefficients
• Stabilization of stochastic nonlinear systems driven by noise of unknown covariance
• Robust adaptive tracking for time-varying uncertain nonlinear systems with unknown control coefficients

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