Distributed optimisation of second‐order multi‐agent systems by control algorithm using position‐only interaction with time‐varying delay

Tran, Ngoc Tu; Wang, Yan Wu; Liu, Xiao Kang; Xiao, Jiang

doi:10.1049/iet-cta.2017.0064

Cited by 16 publications

(14 citation statements)

References 44 publications

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“…However, the diminishing step‐sizes approaches will lead to the slow convergence rate. In the works of Yang et al and Tran et al, some auxiliary variables are introduced to address the optimization problem with time‐varying communication delays. However, the extra variables will increase the communication and computation burden.…”

Section: Resultsmentioning

confidence: 99%

“…We can verify that the controller (34) also satisfies the ZGS property for a weight-balanced switching connected communication graph. Considering the Lyapunov function defined in (36), by virtue of (39) and (40), one can obtaiṅ…”

Section: Distributed Zgs Optimization Algorithm With Time-varying Delmentioning

confidence: 99%

“…2018;28:4900-4915.Remark 3. Different from the LMIs conditions, [25][26][27][28][29][30][31][32][33]36 we derive an explicit sufficient condition for the maximum admissible time delays, which is easier to calculate and implement. From (9), we get that the upper bound d depends on the gain constant , the minimum convexity parameter m, and the maximum eigenvalue max (L).…”

mentioning

confidence: 99%

“…However, the extra variables will increase the communication and computation burden. In contrast to other works, [29][30][31][32][33]36 we consider both the effects of time-varying communication delays and link failures. Our strategy under the ZGS framework can achieve exact convergence without introducing the extra auxiliary variables and get an explicit sufficient condition for the maximum admissible time delays rather than the LMI conditions.…”

mentioning

confidence: 99%

“…Our strategy under the ZGS framework can achieve exact convergence without introducing the extra auxiliary variables and get an explicit sufficient condition for the maximum admissible time delays rather than the LMI conditions. 29,36 As we all know, it is not easy to compute max (L) for some complex communication network. By Lemmas 1 and 2, we have the following corollary.…”

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confidence: 99%

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Distributed zero‐gradient‐sum algorithm for convex optimization with time‐varying communication delays and switching networks

Guo

Chen

2018

Intl J Robust & Nonlinear

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Summary The distributed convex optimization problem subject to time‐varying communication delays and switching network topologies is addressed in this paper. Based on continuous‐time Zero‐Gradient‐Sum scheme, the novel distributed algorithms are proposed to minimize the global objective function which is composed of a sum of strictly convex local cost functions. In the fixed network topology case, by constructing a new Lyapunov‐Krasovskii function, two explicit sufficient conditions for the maximum admissible time delay are derived to guarantee that all agents' states converge to the optimal solution. In the switching network topology case, the stability condition is derived by the common Lyapunov function theory. In addition, two sufficient conditions about the maximum admissible time delays are also derived for the fixed and switching weight‐balanced network topologies, respectively. Several simulation tests are used to illustrate the effectiveness of our obtained theoretical results.

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Section: Resultsmentioning

confidence: 99%

Section: Distributed Zgs Optimization Algorithm With Time-varying Delmentioning

confidence: 99%