We study distributed estimation of a high-dimensional static parameter vector through a group of sensors whose communication network is modeled by a fixed directed graph. Different from existing time-triggered communication schemes, an event-triggered asynchronous scheme is investigated in order to reduce communication while preserving estimation convergence. A distributed estimation algorithm with a single step size is first proposed based on an event-triggered communication scheme with a time-dependent decaying threshold. With the event-triggered scheme, each sensor sends its estimate to neighbor sensors only when the difference between the current estimate and the last sent-out estimate is larger than the triggering threshold. We prove that the proposed algorithm has mean-square and almost-sure convergence respectively, under an integrated condition of sensor network topology and sensor measurement matrices. The condition is satisfied if the topology is a balanced digraph containing a spanning tree and the system is collectively observable. Moreover, we provide estimates for the convergence rates, which are related to the step size as well as the triggering threshold. Furthermore, as an essential metric of sensor communication intensity in the event-triggered distributed algorithms, the communication rate is proved to decay to zero with a certain speed almost surely as time goes to infinity. We show that given the step size, adjusting the decay speed of the triggering threshold can lead to a tradeoff between the convergence rate of the estimation error and the decay speed of the communication rate. Specifically, increasing the decay speed of the threshold would make the communication rate decay faster, but reduce the convergence rate of the estimation error.
Numerical simulations are provided to illustrate the developed results.
Distributed Observers with Dynamic Event-Triggered Communication
School of Automation and Intelligent Sensing, Shanghai Jiao Tong University（上海交通大学自动化与智能传感学院）；Key Laboratory of System Control and Information Processing, Ministry of Education of China（教育部系统控制与信息处理重点实验室）；State Key Laboratory of Submarine Geoscience, Shanghai Jiao Tong University（上海交通大学海洋地质国家重点实验室）
Uncertain Multi-Agent Systems with Distributed Constrained Optimization Missions and Event-Triggered Communications: Application to Resource Allocation
Fully Distributed Event-Triggered Protocols for Linear Multi-Agent Networks
State Key Laboratory for Turbulence and Complex Systems, Department of Mechanics and Engineering Science, College of Engineering, Peking University（北京大学工学院力学与工程科学系湍流国家重点实验室）
Distributed Parameter Estimation Under Event-triggered Communications
ACCESS Linnaeus Centre, School of Electrical Engineering and Computer Science. KTH Royal Institute of Technology, Sweden（ACCESS林奈中心，电气工程和计算机学院，瑞典皇家理工学院）；LSC, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, China（系统与控制实验室，数学与系统科学研究院，中国科学院）；University of Chinese Academy of Sciences, China（中国科学院大学）；College of Control Science and Engineering. Zhejiang University, China（控制科学与工程学院，浙江大学）
Event-triggered Dual Gradient Tracking for Distributed Resource Allocation
the Hong Kong University of Science and Technology（香港科技大学）；Department of Chemical and Biological Engineering, the Hong Kong University of Science and Technology（香港科技大学化学及生物工程系）
On Optimal Event-Triggered Distributed Control for Stochastic Multi-Agent Systems via Reinforcement Learning
The Hong Kong University of Science and Technology (Guangzhou)（香港科技大学（广州））；The Hong Kong University of Science and Technology（香港科技大学）；South China Normal University（华南师范大学）；KTH Royal Institute of Technology（皇家理工学院）
Distributed Kalman Filters with State Equality Constraints: Time-based and Event-triggered Communications
KTH Royal Institute of Technology（皇家理工学院）；Key Laboratory of Systems and Control, Academy of Mathematics and Systems Science, Chinese Academy of Sciences（中国科学院数学与系统科学研究院系统与控制重点实验室）；Rocket Force University of Engineering（火箭军工程大学）；Department of Electronic and Computer Engineering, Hong Kong University of Science and Technology（香港科技大学电子及计算机工程系）
