Performance-constrained fault-tolerant DSC based on reinforcement learning for nonlinear systems with uncertain parameters

DOI10.1016/J.AMC.2022.127759OpenAlexW4311771087MaRDI QIDQ2700398

Jiuxiang Dong, Dongdong Li

Publication date: 21 April 2023

Published in: Applied Mathematics and Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.amc.2022.127759

zbMATH Keywords

neural networkreinforcement learningfault-tolerant controlprescribed performance control (PPC)adaptive dynamic programming (ADP)

Mathematics Subject Classification ID

Model systems in control theory (93Cxx) Controllability, observability, and system structure (93Bxx) Systems theory; control (93-XX)

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Output-feedback optimized consensus for directed graph multi-agent systems based on reinforcement learning and subsystem error derivatives

Cites Work

• Funnel control for nonlinear systems with known strict relative degree
• Tracking control of uncertain nonlinear systems with deferred asymmetric time-varying full state constraints
• Global output feedback tracking control for switched nonlinear systems with deferred prescribed performance
• Finite time command filtered adaptive fault tolerant control for a class of uncertain nonlinear systems
• Robust Adaptive Control of Feedback Linearizable MIMO Nonlinear Systems With Prescribed Performance
• Prescribed Performance Adaptive Control for Multi-Input Multi-Output Affine in the Control Nonlinear Systems
• Adaptive Asymptotic Tracking With Global Performance for Nonlinear Systems With Unknown Control Directions

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