Distributed Feedback Optimization of High-Order Integrators Based on Dynamic Event-Triggered Mechanisms
Xinyi Liu, Adiya Bao, Xiaoming Su, Jingwei Xu, Zhanxiu Wang · 2025
This paper investigates the distributed feedback optimization problem of high-order integrators based on dynamic event-triggered mechanisms, where the ultimate goal of distributed feedback optimization is to drive the outputs of all agents to achieve consensus and reach the optimal solution of the global cost function. To address this problem, a hierarchical control structure including distributed optimizer with time delays and dynamic event-triggered mechanisms and reference-tracking controller is employed. The relationship between the equilibrium point of the distributed optimizer and the optimal solution of the optimization problem is analyzed, using the Lyapunov-Krasovskii method, it is proven that the distributed optimizer generates an optimal signal that asymptotically converges to the optimal solution. Furthermore, it is also proven that Zeno behavior will not occur. Finally, a reference tracking controller is designed using the leader-following method, ensuring that the agents' outputs follow the optimal signal, and the stability theory of cascade systems is used to prove that the hierarchical control structure can achieve distributed feedback optimization for high-order multi-agent systems.