Event‐based asynchronous communication and sampled control for synchronization of multiagent networks with input saturation

Abstract

This paper investigates the problem of event-based synchronization of linear dynamical networks subject to input saturation. The asynchronous neighboring information transmission is triggered by distributed events. The sampled control technique is utilized to exclude both the internal Zeno behavior of each agent and the network Zeno behavior attributed to neighboring agents. Allowing the input saturation to be attained, an event-based global synchronization algorithm is proposed for multiagent networks with neutrally stable dynamics. For general linear networks, an event-triggered control protocol is designed using the modified algebraic Riccati equation, with a low-gain cooperative control law proposed to achieve semiglobal synchronization. A numerical example is presented to illustrate the theoretical results.

Gain margin and Lyapunov analysis of discrete‐time network synchronization via Riccati design

“…Then, the design approach in Theorem 3 can be applied to Lyapunov analysis for discrete‐time networks with switching topologies 36 If time delay is considered in agent dynamics and network information transmission, the Lyapunov analysis approach works well for networks with undirected graphs in References 8,9. For problem with digraphs, the error between the current states $$$ {x}_i(t) $$$ and the delayed states $$$ {x}_i\left(t-\tau \right) $$$ may be taken into account in the Lyapunov analysis, and the delay‐dependent synchronizing conditions need to be analyzed, which will be studied in detail in the future.…”

“…The MARE plays a fundamental role in synchronization of discrete-time networks. [1][2][3][4][5] The effective Lyapunov analysis approach can be used for event-triggered control of multi-agent networks with undirected fixed graphs [6][7][8][9] and sampled control of multi-agent networks with undirected switching graphs. 10 However, there is a lack of knowledge about the Lyapunov analysis of discrete-time networks with directed graphs and general linear dynamics.…”

Steady‐State Analysis and Output Voltage Minimization Based Control Strategy for Electric Springs in the Smart Grid with Multiple Renewable Energy Sources

“…For this reason, a PR controller is introduced to regulate the PCC voltage (V ) to its reference level by driving the difference between reference voltage V − and measured voltage V to zero. In addition to PR control, many other control methods, such as sliding-mode control [28,29], robust control [30], model predictive control [31,32], and event-triggered control [33] can also be considered in future studies based on the control strategy mentioned above.…”