An event-triggered neural critic technique for nonzero-sum game design with control constraints

DOI10.1080/00207721.2022.2111238zbMath1520.93311OpenAlexW4292833573MaRDI QIDQ6111183

Unnamed Author, Ding Wang, Lingzhi Hu, Jin Ren, Jun-Fei Qiao

Publication date: 6 July 2023

Published in: International Journal of Systems Science (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00207721.2022.2111238

zbMATH Keywords

nonzero-sum gamesoptimal controlneural networksconstrained controlevent-triggered controlnonaffine systemsadaptive critic technique

Mathematics Subject Classification ID

Discrete-time games (91A50) Discrete event control/observation systems (93C65) Existence theories for optimal control problems involving partial differential equations (49J20)

Related Items (1)

Decentralised tracking control based on critic learning for nonlinear disturbed interconnected systems

Cites Work

• Model-based adaptive event-triggered control of nonlinear continuous-time systems
• Event-triggered constrained control with DHP implementation for nonaffine discrete-time systems
• Optimal nonlinear, but continuous, feedback control of systems with saturating actuators
• Control of linear systems with saturating actuators
• A data-based neural policy learning strategy towards robust tracking control design for uncertain dynamic systems
• Non-fragile l₂-l_∞ state estimation for time-delayed artificial neural networks: an adaptive event-triggered approach
• Self-Learning Optimal Regulation for Discrete-Time Nonlinear Systems Under Event-Driven Formulation
• Neural-network-based discounted optimal control via an integrated value iteration with accuracy guarantee

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