Performance‐guaranteed containment control for pure‐feedback multi agent systems via reinforcement learning algorithm

DOI10.1002/RNC.6349zbMath1529.93030OpenAlexW4296480453MaRDI QIDQ6180531

Unnamed Author, Deyin Yao, Wenbin Xiao, Qi Zhou, Xiao-Meng Li

Publication date: 19 December 2023

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

Full work available at URL: https://doi.org/10.1002/rnc.6349

zbMATH Keywords

backsteppingcontainment controlreinforcement learning (RL)unmeasurable statesperformance-guaranteed

Mathematics Subject Classification ID

Feedback control (93B52) Lyapunov and other classical stabilities (Lagrange, Poisson, (L^p, l^p), etc.) in control theory (93D05) Multi-agent systems (93A16) Observers (93B53)

Cites Work

• Online actor-critic algorithm to solve the continuous-time infinite horizon optimal control problem
• Adaptive control with guaranteed transient and steady state tracking error bounds for strict feedback systems
• Asymptotic Tracking Control of Uncertain Nonlinear Systems With Unknown Actuator Nonlinearity
• Distributed containment control for nonlinear multiagent systems in pure‐feedback form
• Fuzzy adaptive optimal control for nonlinear switched systems with actuator hysteresis
• Distributed Robust Global Containment Control of Second-Order Multiagent Systems With Input Saturation
• Containment control of stochastic multiagent systems with semi‐Markovian switching topologies
• Reinforcement learning for adaptive optimal control of unknown continuous-time nonlinear systems with input constraints

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