Distributed Observers with Dynamic Event-Triggered Communication
Pith reviewed 2026-05-10 16:25 UTC · model grok-4.3
The pith
Dynamic event-triggered distributed observers for linear systems enforce strictly positive minimum inter-event times while driving estimation errors to zero exponentially.
A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.
Core claim
The proposed dynamic event-triggered distributed observer, constructed with new comparison functions inside the triggering condition, guarantees that the minimum inter-event time remains strictly positive for both node-based and edge-based mechanisms and that the distributed estimation error converges to zero exponentially for any linear time-invariant system.
What carries the argument
Dynamic event-triggering law augmented by comparison functions that evolve an internal variable to raise the triggering threshold and thereby enforce a positive dwell time between communications.
If this is right
- Both node-based and edge-based dynamic triggers become viable for distributed observers without Zeno behavior.
- Exponential convergence of the estimation error holds under the same Lyapunov-type conditions used for continuous communication.
- Average communication rate drops compared with periodic or static event schemes while stability margins are retained.
- The design applies directly to networks of sensors estimating a common LTI state vector.
Where Pith is reading between the lines
- The same comparison-function technique might be adapted to obtain positive inter-event times for nonlinear or switched observers if suitable bounding functions can be derived.
- Coupling the observer with an event-triggered controller could yield a fully event-based closed-loop architecture with guaranteed positive dwell times.
- Large-scale network simulations could test whether the positive-MIET bound degrades with network size or communication delays.
Load-bearing premise
The comparison functions and trigger parameters can be selected so that the resulting inter-event intervals stay bounded away from zero while the observer error system remains exponentially stable.
What would settle it
A concrete linear system, observer gain matrix, and set of comparison functions for which the simulated inter-event times approach zero or the estimation error norm fails to decay exponentially.
Figures
read the original abstract
This paper studies the problem of distributed state estimation of linear time-invariant (LTI) systems under event-triggered communication. For event-triggering mechanisms, the existence of positive minimum inter-event times (MIETs) is an essential property for ensuring practicality. It is widely recognized that dynamic event-triggering mechanisms can effectively reduce redundant communication. However, for distributed observers, it remains unclear whether dynamic event-triggering mechanisms can ensure positive MIETs. This paper proposes a dynamic event-triggered distributed observer. By introducing new comparison functions, it is proven that the dynamic event-triggered distributed observer can guarantee strictly positive MIETs and ensure the exponential convergence of the estimation error. Moreover, most existing works on event-triggered distributed observers only consider node-based event-triggering mechanisms, while both node-based and edge-based dynamic event-triggering mechanisms are constructed in this paper. Numerical examples are provided to illustrate the effectiveness of the proposed results.
Editorial analysis
A structured set of objections, weighed in public.
Referee Report
Summary. This paper studies distributed state estimation for linear time-invariant systems under event-triggered communication. It proposes both node-based and edge-based dynamic event-triggered distributed observers and introduces new comparison functions to prove that these mechanisms guarantee strictly positive minimum inter-event times (MIETs) while ensuring exponential convergence of the estimation errors.
Significance. If the central claims hold, the work is significant for practical multi-agent estimation because positive MIETs prevent Zeno behavior, a common obstacle in event-triggered designs. The extension to edge-based dynamic triggering and the use of tailored comparison functions to bound inter-event times provide a concrete technical route that aligns with and extends existing literature on dynamic event-triggering for distributed observers.
minor comments (2)
- The abstract states that new comparison functions are introduced to prove positive MIETs, but the manuscript should explicitly state the minimal assumptions on system observability, graph connectivity, and the choice of design parameters that make the comparison functions feasible (e.g., in the stability and MIET analysis sections).
- Numerical examples are mentioned to illustrate effectiveness; the manuscript would benefit from reporting the specific parameter values used for the dynamic triggering thresholds and comparison functions so that the positive MIET property can be directly verified from the simulations.
Simulated Author's Rebuttal
We thank the referee for the positive summary of our work and the recommendation for minor revision. The assessment correctly highlights the significance of guaranteeing strictly positive MIETs via dynamic event-triggering for both node-based and edge-based distributed observers, along with the use of tailored comparison functions to establish exponential convergence.
Circularity Check
No significant circularity detected
full rationale
The paper derives positive MIETs and exponential error convergence by introducing new comparison functions into the dynamic event-triggered observer analysis. This step applies standard comparison lemmas to the augmented error dynamics and does not reduce by construction to fitted parameters, self-definitions, or load-bearing self-citations. The node- and edge-based mechanisms are constructed explicitly, with the MIET lower bound obtained independently via the new functions rather than renamed from prior results. The derivation remains self-contained and consistent with external event-triggered control techniques.
Axiom & Free-Parameter Ledger
axioms (1)
- domain assumption The underlying LTI system is detectable and the communication graph is connected.
Reference graph
Works this paper leans on
-
[1]
Dimos V Dimarogonas, Emilio Frazzoli, and Karl H Johansson. Distributed event-triggered control for multi- agent systems.IEEE Transactions on Automatic Control, 57(5):1291–1297, 2011
work page 2011
-
[2]
Lei Ding, Qing-Long Han, Xiaohua Ge, and Xian-Ming Zhang. An overview of recent advances in event-triggered consensus of multiagent systems.IEEE Transactions on Cybernetics, 48(4):1110–1123, 2018
work page 2018
-
[3]
Victor S Dolk, Dominicus P Borgers, and WPMH Heemels. Output-based and decentralized dynamic event-triggered control with guaranteedL p-gain performance and Zeno- freeness.IEEE Transactions on Automatic Control, 62(1):34– 49, 2017
work page 2017
-
[4]
Antoine Girard. Dynamic triggering mechanisms for event- triggered control.IEEE Transactions on Automatic Control, 60(7):1992–1997, 2015
work page 1992
-
[5]
An introduction to event-triggered and self- triggered control
Wilhelmus PMH Heemels, Karl Henrik Johansson, and Paulo Tabuada. An introduction to event-triggered and self- triggered control. InProceedings of the IEEE Conference on Decision and Control, pages 3270–3285, Maui, Hawaii, USA, December 10-13, 2012
work page 2012
-
[6]
Convergence properties of a decentralized Kalman filter
Maryam Kamgarpour and Claire Tomlin. Convergence properties of a decentralized Kalman filter. InProceedings of the IEEE Conference on Decision and Control, pages 3205– 3210, Cancun, Mexico, December 9-11, 2008
work page 2008
-
[7]
Upper Saddle River, New Jersey: Prentice-Hall, 2002
Hassan K Khalil.Nonlinear Systems. Upper Saddle River, New Jersey: Prentice-Hall, 2002
work page 2002
-
[8]
On distributed optimal Kalman-Bucy filtering by averaging dynamics of heterogeneous agents
Jaeyong Kim, Hyungbo Shim, and Jingbo Wu. On distributed optimal Kalman-Bucy filtering by averaging dynamics of heterogeneous agents. InProceedings of the IEEE Conference on Decision and Control, pages 6309–6314, Las Vegas, NV, USA, December 12-14, 2016
work page 2016
-
[9]
Taekyoo Kim, Chanhwa Lee, and Hyungbo Shim. Completely decentralized design of distributed observer for linear systems.IEEE Transactions on Automatic Control, 65(11):4664–4678, 2020
work page 2020
-
[10]
Shuqi Li, Feng Xiao, Aiping Wang, and Yuanshi Zheng. Distributed observers for linear time-invariant systems with time-varying delays: A switching event-triggered approach. IEEE Transactions on Cybernetics, 55(9):4441–4452, 2025
work page 2025
-
[11]
Yan Liu and Guanghong Yang. Resilient event-triggered distributed state estimation for nonlinear systems against DoS attacks.IEEE Transactions on Cybernetics, 52(9):9076– 9089, 2022
work page 2022
-
[12]
Mingkang Long, Housheng Su, Wei Xing Zheng, Yong Wang, and Rong Su. Adaptive event-triggered distributed observer for unknown-input LTI systems.IEEE Transactions on Automatic Control, 70(12):8274–8281, 2025
work page 2025
-
[13]
Yuezu Lv, Guanghui Wen, and Tingwen Huang. Adaptive protocol design for distributed tracking with relative output information: A distributed fixed-time observer approach. IEEE Transactions on Control of Network Systems, 7(1):118– 128, 2020
work page 2020
-
[14]
Yuezu Lv, Guanghui Wen, Tingwen Huang, and Zhisheng Duan. Adaptive attack-free protocol for consensus tracking with pure relative output information.Automatica, 117:108998, 2020
work page 2020
-
[15]
Consensus-based linear distributed filtering.Automatica, 48(8):1776–1782, 2012
Ion Matei and John S Baras. Consensus-based linear distributed filtering.Automatica, 48(8):1776–1782, 2012
work page 2012
-
[16]
Event based agreement protocols for multi-agent networks.Automatica, 49(7):2125– 2132, 2013
Xiangyu Meng and Tongwen Chen. Event based agreement protocols for multi-agent networks.Automatica, 49(7):2125– 2132, 2013
work page 2013
-
[17]
Periodic event-triggered average consensus over directed graphs
Xiangyu Meng, Lihua Xie, Yeng Chai Soh, Cameron Nowzari, and George J Pappas. Periodic event-triggered average consensus over directed graphs. InProceedings of the IEEE Conference on Decision and Control, pages 4151–4156. IEEE, 2015
work page 2015
-
[18]
Distributed observers for LTI systems.IEEE Transactions on Automatic Control, 63(11):3689–3704, 2018
Aritra Mitra and Shreyas Sundaram. Distributed observers for LTI systems.IEEE Transactions on Automatic Control, 63(11):3689–3704, 2018
work page 2018
-
[19]
Cameron Nowzari, Eloy Garcia, and Jorge Cort´ es. Event- triggered communication and control of networked systems for multi-agent consensus.Automatica, 105:1–27, 2019
work page 2019
-
[20]
Distributed Kalman filtering for sensor networks
Reza Olfati-Saber. Distributed Kalman filtering for sensor networks. InProceedings of the IEEE Conference on Decision and Control, pages 5492–5498, New Orleans, LA, USA, December 12-14, 2007
work page 2007
-
[21]
Distributed Kalman filter with embedded consensus filters
Reza Olfati-Saber. Distributed Kalman filter with embedded consensus filters. InProceedings of the IEEE Conference on Decision and Control, pages 8179–8184, Seville, Spain, December 12-15, 2005
work page 2005
-
[22]
Kalman-consensus filter: Optimality, stability, and performance
Reza Olfati-Saber. Kalman-consensus filter: Optimality, stability, and performance. InProceedings of the IEEE Conference on Decision and Control held jointly with Chinese Control Conference, pages 7036–7042, Shanghai, China, December 15-18, 2009
work page 2009
-
[23]
Shinkyu Park and Nuno C Martins. Design of distributed LTI observers for state omniscience.IEEE Transactions on Automatic Control, 62(2):561–576, 2017. 14
work page 2017
-
[24]
Optimal remote state estimation for self-propelled particle models
Shinkyu Park and Nuno C Martins. Optimal remote state estimation for self-propelled particle models. InProceedings of the IEEE Conference on Decision and Control, pages 327– 333, Las Vegas, NV, USA, December 12-14, 2016
work page 2016
-
[25]
Fabio Pasqualetti, Ruggero Carli, and Francesco Bullo. Distributed estimation via iterative projections with application to power network monitoring.Automatica, 48(5):747–758, 2012
work page 2012
-
[26]
Consensus-based distributed estimation for target tracking in heterogeneous sensor networks
Antonio Petitti, Donato Di Paola, Alessandro Rizzo, and Grazia Cicirelli. Consensus-based distributed estimation for target tracking in heterogeneous sensor networks. In Proceedings of the IEEE Conference on Decision and Control and European Control Conference, pages 6648–6653, Orlando, FL, USA, December 12-15, 2011
work page 2011
-
[27]
Yang-Yang Qian, Lu Liu, and Gang Feng. Output consensus of heterogeneous linear multi-agent systems with adaptive event-triggered control.IEEE Transactions on Automatic Control, 64(6):2606–2613, 2019
work page 2019
-
[28]
Yang-Yang Qian and Yan Wan. Design of distributed adaptive event-triggered consensus control strategies with positive minimum inter-event times.Automatica, 133:109837, 2021
work page 2021
-
[29]
Housheng Su, Haoxuan Zhu, and Zhigang Zeng. Adaptive event-triggered distributed observer under communication link faults.IEEE Transactions on Automatic Control, 70(5):2992–3007, 2025
work page 2025
-
[30]
Yuancheng Sun and Guanghong Yang. Event-triggered distributed state estimation for multiagent systems under DoS attacks.IEEE Transactions on Cybernetics, 52(7):6901– 6910, 2022
work page 2022
-
[31]
Lili Wang and A Stephen Morse. A distributed observer for a time-invariant linear system.IEEE Transactions on Automatic Control, 63(7):2123–2130, 2018
work page 2018
-
[32]
Xiaoling Wang, Guo-Ping Jiang, Housheng Su, and Zhigang Zeng. Consensus-based distributed reduced-order observer design for LTI systems.IEEE Transactions on Cybernetics, 52(7):6331–6341, 2022
work page 2022
-
[33]
Dynamic event- triggered consensus can ensure positive inter-event times
Sikang Zhan, Xianwei Li, and Shaoyuan Li. Dynamic event- triggered consensus can ensure positive inter-event times. IEEE Transactions on Automatic Control, 71(1):458–465, 2026
work page 2026
-
[34]
Lan Zhang, Martin Guay, Maobin Lu, and Shimin Wang. Distributed state estimation for discrete-time uncertain linear systems over jointly connected switching networks. Automatica, 173:112079, 2025
work page 2025
-
[35]
Lan Zhang, Maobin Lu, Fang Deng, and Jie Chen. Distributed state estimation under jointly connected switching networks: Continuous-time linear systems and discrete-time linear systems.IEEE Transactions on Automatic Control, 69(2):1104–1111, 2024
work page 2024
-
[36]
Haoxuan Zhu and Housheng Su. Hybrid-triggered distributed observer design with measurement and event-verifying sampling.IEEE Transactions on Automatic Control, 2025. DOI: 10.1109/TAC.2025.3649727
-
[37]
On the cooperative observability of a continuous-time linear system on an undirected network
Henghui Zhu, Kexin Liu, Jinhu L¨ u, Zongli Lin, and Yao Chen. On the cooperative observability of a continuous-time linear system on an undirected network. InProceedings of the International Joint Conference on Neural Networks, pages 2940–2944, Beijing, China, July 6-11, 2014. 15
work page 2014
discussion (0)
Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.