Cooperative tracking control of single-integrator multi-agent systems with multiple leaders

Martinović, Luka; Zečević, Žarko; Krstajić, Božo

doi:10.1016/j.ejcon.2021.11.003

Cited by 16 publications

(2 citation statements)

References 26 publications

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“…In Reference 12, the necessary and sufficient conditions for structure‐controllability in associated graph topologies with multiple leaders consensus have proposed. Luka Martinov 13 constructed a single integrator with multiple leaders formation tracking model and proposed a distributed observer‐based control strategy . In terms of time‐varying formation tracking control, Dong et al have acquired some meaningful achievements 14‐16 .…”

Section: Introductionmentioning

confidence: 99%

Multiple leaders formation tracking with switching topology and aperiodic sampled data under intermittent control scheme

Liu

Deng

Zhao

et al. 2022

Intl J Robust & Nonlinear

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This article studies the problem of second-order formation tracking with multiple leaders under intermittent control scheme in stochastic multi-agent networked systems. Based on the aperiodic sampled data, the formation tracking control protocol is proposed by considering switching topology and the time-varying transmission delay of information interaction between each agent. Using the algebraic graph theory, stochastic systems theory, Lyapunov theory, and Halanay inequality, the sufficient conditions of mean square stability for formation tracking with multiple leaders are obtained. To further alleviate the computation resources of the controller, the intermittent control strategy is proposed. Meanwhile, a novel stability analysis method for intermittent control is introduced based on an auxiliary system and comparison principle. Furthermore, the lower bound of the duty cycle for a certain control period is obtained and the desired formation mode is also reached under the designed intermittent control scheme. Finally, numerical examples are given to verify the correctness and effectiveness of the proposed methods.

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Section: Introductionmentioning

confidence: 99%

Multiple leaders formation tracking with switching topology and aperiodic sampled data under intermittent control scheme

Liu

Deng

Zhao

et al. 2022

Intl J Robust & Nonlinear

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“…Distributed averaging is an instance of distributed computation aiming to determine the global average of a set of values by iterating local calculations. It has been extensively studied as the primary tool for solving cooperative control problems in multi-agent systems [1] such as distributed sensor networks, micro-grids, transport networks, power distribution systems, and biological networks [2]. In these settings, the value of an aggregate function over the entire network data is often more relevant than individual data at nodes.…”

Section: Introductionmentioning

confidence: 99%

Topological network features determine convergence rate of distributed average algorithms

Sirocchi

Bogliolo²

2022

Sci Rep

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Gossip algorithms are message-passing schemes designed to compute averages and other global functions over networks through asynchronous and randomised pairwise interactions. Gossip-based protocols have drawn much attention for achieving robust and fault-tolerant communication while maintaining simplicity and scalability. However, the frequent propagation of redundant information makes them inefficient and resource-intensive. Most previous works have been devoted to deriving performance bounds and developing faster algorithms tailored to specific structures. In contrast, this study focuses on characterising the effect of topological network features on performance so that faster convergence can be engineered by acting on the underlying network rather than the gossip algorithm. The numerical experiments identify the topological limiting factors, the most predictive graph metrics, and the most efficient algorithms for each graph family and for all graphs, providing guidelines for designing and maintaining resource-efficient networks. Regression analyses confirm the explanatory power of structural features and demonstrate the validity of the topological approach in performance estimation. Finally, the high predictive capabilities of local metrics and the possibility of computing them in a distributed manner and at a low computational cost inform the design and implementation of a novel distributed approach for predicting performance from the network topology.

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Event-Triggered Consensus Tracking for Time-Delay Multi-Agent Systems with Input Saturation Via Dynamic Output Feedback

Li,

2023

J Intell Robot Syst

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Cooperative tracking control of single-integrator multi-agent systems with multiple leaders

Cited by 16 publications

References 26 publications

Multiple leaders formation tracking with switching topology and aperiodic sampled data under intermittent control scheme

Multiple leaders formation tracking with switching topology and aperiodic sampled data under intermittent control scheme

Topological network features determine convergence rate of distributed average algorithms

Event-Triggered Consensus Tracking for Time-Delay Multi-Agent Systems with Input Saturation Via Dynamic Output Feedback

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