Periodic event-triggered adaptive tracking control design for nonlinear discrete-time systems via reinforcement learning

DOI10.1016/j.neunet.2022.06.039zbMath1525.93256WikidataQ114950051 ScholiaQ114950051MaRDI QIDQ6052405

Fanghua Tang, Xudong Zhao, Guangdeng Zong, Ning Xu, Ben Niu

Publication date: 17 October 2023

Published in: Neural Networks (Search for Journal in Brave)

zbMATH Keywords

discrete-time systemsneural networks (NNs)reinforcement learning (RL)periodic event-triggered mechanism

Mathematics Subject Classification ID

Artificial neural networks and deep learning (68T07) Nonlinear systems in control theory (93C10) Adaptive control/observation systems (93C40) Discrete-time control/observation systems (93C55) Discrete event control/observation systems (93C65)

Related Items (10)

Event-triggered fault-tolerant control for input-constrained nonlinear systems with mismatched disturbances via adaptive dynamic programming ⋮ Adaptive optimized consensus control for a class of nonlinear multi-agent systems with asymmetric input saturation constraints and hybrid faults ⋮ Distributed consensus of heterogeneous switched nonlinear multiagent systems with input quantization and DoS attacks ⋮ Event-triggered tracking control for nonlinear time-varying delay systems with full state constraints and unknown control coefficients ⋮ Sliding-mode surface-based approximate optimal control for nonlinear multiplayer Stackelberg-Nash games via adaptive dynamic programming ⋮ Event-triggered-based online integral reinforcement learning for optimal control of unknown constrained nonlinear systems ⋮ Active disturbance rejection‐based event‐triggered bipartite consensus control for nonaffine nonlinear multiagent systems ⋮ Event-triggered adaptive decentralised control of interconnected nonlinear systems with Bouc-Wen hysteresis input ⋮ Dynamic event-triggered control for discrete-time nonlinear Markov jump systems using policy iteration-based adaptive dynamic programming ⋮ Event-based adaptive fuzzy tracking control for nonlinear systems with input magnitude and rate saturations

Cites Work

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