Distributed adaptive consensus tracking control for non‐linear multi‐agent systems with time‐varying delays

Zamani, Najmeh; Askari, Javad; Kamali, Marzieh; Aghdam, Amir G.

doi:10.1049/iet-cta.2020.0281

Cited by 9 publications

(5 citation statements)

References 47 publications

(50 reference statements)

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“…Remark Although there is no restriction on the delayed nonlinear functions, the derivative of time‐varying state delay is required to be less than one. Such condition on time‐varying state delays is widely used 33‐35,42‐44 due to the use of LKFs. So far, no LKFs without this condition can compensate the delayed nonlinearities.…”

Section: Resultsmentioning

confidence: 99%

“…In References 42 and 43, the consensus scheme based on output feedback was designed for nonlinear MASs with time‐varying state delays. In Reference 44, the MAS with multiple time‐varying state delays was studied. However, to the best of our knowledge, there are few reports about nonlinear MASs with time‐varying state delays and unknown control coefficients.…”

Section: Introductionmentioning

confidence: 99%

“…Based on the command filtered backstepping technique, a novel distributed adaptive fuzzy consensus control law is designed. Compared with the previous results, 12‐14,39‐41,44 the finite‐time command filters are constructed to handle the “explosion of complexity” problem. Meanwhile, the filtering errors are compensated to obtain better performance.…”

Section: Introductionmentioning

confidence: 99%

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Distributed consensus tracking control for nonlinear multiagent systems with state delays and unknown control coefficients

Wang

Xiang

2021

Intl J Robust & Nonlinear

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In this article, the distributed consensus tracking problem is investigated for a group of heterogeneous nonlinear multiagent systems (MASs). The dynamic of each follower is subject to multiple time‐varying state delays and unknown non‐identical control coefficients. Most existing results for MASs with unknown non‐identical control coefficients are on the condition that only the specific Nussbaum‐type function can be used. This constraint is removed by employing the enhanced Nussbaum functions. Some appropriate Lyapunov–Krasovskii functionals are constructed to compensate the delayed nonlinear functions. By applying the finite‐time command filters to backstepping technique, a novel distributed adaptive consensus tracking control law is developed, which is independent of multiple state delays. It is proved that each follower's output can track the leader. Finally, the validness of the proposed control algorithm is illustrated by two simulation examples.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Distributed consensus tracking control for nonlinear multiagent systems with state delays and unknown control coefficients

Wang

Xiang

2021

Intl J Robust & Nonlinear

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“…The multiple couplings of three error variables in (15), adaptive weights in (10) and the nonlinear function in ( 12) make the convergence analysis intractable. The obstacle is surrounded by the artfully constructed Lyapunov functions in ( 23) that contains the information of time-varying coupling weights and their derivatives [24,25].…”

Section: And Thenmentioning

confidence: 99%

Adaptive observer protocol designs for consensus tracking of multi‐agent systems

Chu

Gorbachev

Yue

et al. 2022

IET Control Theory & Appl

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In this brief, a type of novel fully distributed adaptive protocols is designed for achieving leader‐follower multi‐agents tracking. The design procedure constitutes three steps. First, a local observer is constructed for each agent (including the leader) in virtue of its own inputs and outputs, aiming to estimating of that agent's state. Second, to propagate the estimate of the leader from target followers to all the followers, a distributed adaptive estimator is then proposed, via embedding with time‐varying coupling weights. At last, an elegant controller is designed for each follower based on the estimate of its own state and the estimate of the leader's state. The rigorous convergence analysis is provided. Finally, the simulation results validate the effectiveness of the proposed protocols.

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“…In ref. [4], the adaptive dynamic surface control law was designed, where the agent can achieve the tracking consensus under the influence of uncertain delays. In ref.…”

Section: Introductionmentioning

confidence: 99%

Dynamic event‐triggered control for leader‐following consensus of multiagent systems with the estimator

Qiu

Chen

et al. 2022

IET Control Theory & Appl

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In this paper, the leader-following consensus problem of general linear multi-agent systems with distributed dynamic event-triggered control is studied. A distributed controller with estimated states is designed and a dynamic event-triggered communication protocol with an auxiliary variable is proposed for each agent to update its triggering threshold. Under this control strategy, the systems only need the states in triggering instants as a result of the utilisation of estimated states. The existence of a dynamic threshold guarantees fewer triggering times, in contrast to the conventional static one. Meanwhile, the estimator is designed between the triggering instants to reduce the state shift, the next state of each agent depends on the local information of itself and its neighbours rather than global information. Then, the multi-agent systems can achieve consensus without Zeno behaviour. Finally, a simulation example is offered to verify the effectiveness and feasibility of the proposed approach.

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Distributed adaptive consensus tracking control for non‐linear multi‐agent systems with time‐varying delays

Cited by 9 publications

References 47 publications

Distributed consensus tracking control for nonlinear multiagent systems with state delays and unknown control coefficients

Distributed consensus tracking control for nonlinear multiagent systems with state delays and unknown control coefficients

Adaptive observer protocol designs for consensus tracking of multi‐agent systems

Dynamic event‐triggered control for leader‐following consensus of multiagent systems with the estimator

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