Event-Triggered Discrete-Time Distributed Consensus Optimization over Time-Varying Graphs

Abstract

This paper focuses on a class of event-triggered discrete-time distributed consensus optimization algorithms, with a set of agents whose communication topology is depicted by a sequence of time-varying networks. The communication process is steered by independent trigger conditions observed by agents and is decentralized and just rests with each agent's own state. At each time, each agent only has access to its privately local Lipschitz convex objective function. At the next time step, every agent updates its state by applying its own objective function and the information sent from its neighboring agents. Under the assumption that the network topology is uniformly strongly connected and weight-balanced, the novel event-triggered distributed subgradient algorithm is capable of steering the whole network of agents asymptotically converging to an optimal solution of the convex optimization problem. Finally, a simulation example is given to validate effectiveness of the introduced algorithm and demonstrate feasibility of the theoretical analysis.

Distributed Event-Triggered Subgradient Method for Convex Optimization With General Step-Size

“…The general time-triggered subgradient methods are studied in [4]- [30], however, they consume a great number of resources for the agent needs to communicate with its neighbors at every communication moment. In order to reduces the burden of communication network, event-triggered control [31]- [34], [36]- [39] has be widely studied in recent few years. The key to the event-triggered mechanism is to reduce the unnecessary information transmission among agents which can effectively improve the running speed and reduce the communication burden.…”

“…Then, the threshold function of the trigger condition is changed to independent with the step-size [33]. The event-based distributed consensus of the multiagent system with time-varying digraph network is explored in [34], however, the constraint case and general step-size are not considered.…”

Nonfragile Integral‐Based Event‐Triggered Control of Uncertain Cyber‐Physical Systems under Cyber‐Attacks

“…Some e ective manners such as event-triggered scheme (ETS) [10], signal quantization [11], and real-time scheduling [12,13] have been proposed to save communication resources and reduce computation burden. Recently, ETS has gained growing attention and interests in existing research studies [14][15][16][17][18][19][20][21][22][23] for its simplicity of execution and e ectiveness of reducing data transmissions. Due to this fact, the idea of ETS is introduced into security control for CPSs and has produced many interesting results [24][25][26][27][28][29].…”

On Stability of Multi‐Valued Nonlinear Feedback Shift Registers

“…[10]. Over the last decades, Boolean networks have attracted much attention in many communities, such as biology [11][12][13], physics [14][15][16], system sciences [17][18][19][20][21], and control theory [22,23]. In the community of system sciences, Cheng and his collaborators [24] developed an algebraic framework for Boolean networks using a semitensor product approach.…”