ISA Trans. 2026 Jul 21:S0019-0578(26)00382-4. doi: 10.1016/j.isatra.2026.07.016. Online ahead of print.
ABSTRACT
This paper investigates the distributed resource allocation problem in second-order nonlinear multi-agent systems (MASs) and proposes an integrated adaptive dynamic programming (ADP) framework with a dynamic event-triggered mechanism. A coupled performance index based on resource allocation errors is first formulated, embedding a positive-definite quadratic form to transform the resource allocation control problem into the design of optimal control policies for all agents. Within this framework, a fixed-time single-critic learning law is developed to approximate the Hamilton-Jacobi-Bellman (HJB) equation online. The dynamic event-triggered mechanism updates the control input only when the adaptive triggering condition is violated. Theoretical analysis guarantees the uniform ultimate boundedness of all closed-loop signals. Numerical simulations verify the effectiveness of the proposed framework in achieving accurate resource allocation while balancing allocation errors and control efforts.
PMID:42502010 | DOI:10.1016/j.isatra.2026.07.016
