Distributed Formation Control of Networked Multi-Agent Systems Using a Dynamic Event-Triggered Communication Mechanism

By Xiaohua Ge, Qing-Long Han. IEEE transactions on industrial electronics (1982. Print), 2017

603 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Control and Systems Engineering

View Paper: https://www.semanticscholar.org/paper/ecec2583a06a11564381d008400a9829a7995560

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Networks and Communications

1. Qing-Long Han
2. Xianming Zhang
3. Xiaohua Ge
4. Lei Ding
5. Chen Peng
6. Derui Ding
7. Dong Yue
8. Boda Ning

In Control and Systems Engineering

1. Qing-Long Han
2. Xianming Zhang
3. Xiaohua Ge
4. Lei Ding
5. Derui Ding
6. Chen Peng
7. Dong Yue
8. Zidong Wang

Citations in the corpus

• Adaptive Consensus Control of Linear Multiagent Systems With Dynamic Event-Triggered Strategies (2020, background): “Then, ¯ x i ( t ) and ¯ y i ( t ) will converge to a common value if ˜ x i ( t ) and ˜ y i ( t ) achieve consensus [6].”
• Memory-Based Event-Triggering H∞ Load Frequency Control for Power Systems Under Deception Attacks (2020, background): “Among them, many popular ETSs have been proposed, for example, the continuous ETS [1], [3]; mixed ETS [4]; dynamic ETS [8]; periodic/discrete ETS [10], [36]; adaptive ETS [9]; distributed ETS [6]; and so on.”
• Distributed Optimization for Multiagent Systems: An Edge-Based Fixed-Time Consensus Approach (2019, background): “, synchronization [3]–[6], target tracking [7]–[9], anti-disturbance control [10], motion planning [11], and formation control [12].”
• An Overview of Recent Advances in Event-Triggered Consensus of Multiagent Systems (2018, positive): “is also shown in [4] that, by using the dynamic event-triggered communication mechanism, one may find a better tradeoff between preserving formation and/or consensus performance and reducing inter-robot communication frequency than using”
• Networked control systems: a survey of trends and techniques (2020, background): “5, and 11 Mb/s due to time-varying interference and random wireless fading [110].”
• Dynamic Event-Triggered Distributed Coordination Control and its Applications: A Survey of Trends and Techniques (2020, background): “A similar monotonic-threshold-based dETSM based on sampled data [18] is adopted to resolve the problem of distributed formation control.”
• Distributed Control Strategies for Microgrids: An Overview (2020, neutral): “…such as second-order consensus [89]–[91], adaptive consensus [92]–[94], consensus with constraints [95], [96], event-triggered consensus [97], [98], finite-time consensus [99], [100], delay-robust consensus, linear consensus protocol [101], [102],heterogeneous consensus [103], [104],…”
• A Survey on Model-Based Distributed Control and Filtering for Industrial Cyber-Physical Systems (2019, background): “Recently, there are a rich body of results on consensus control of MASs with various networked-induced phenomena, switching network topologies, or sampling, see [96], [97] and the references therein.”
• A Survey of Autonomous Underwater Vehicle Formation: Performance, Formation Control, and Communication Capability (2021, background): “Each AUV has a controller that can make decision independently based on local information of the AUV swarm [93], [94].”
• Dynamic Event-Triggered and Self-Triggered Control for Multi-agent Systems (2019, background): “Although continuous sensing, broadcasting, listening, and receiving are also avoided in [11], [13], and [24] by combining event-triggered control with periodic sampling, the additional periodic sensing and listening are still needed.”
• An Overview of Recent Advances in Fixed-Time Cooperative Control of Multiagent Systems (2018, neutral): “1) Nonholonomic Mobile Robots [53]–[55]”