Leader-Following Consensus for a Class of Nonlinear Strick-Feedback Multiagent Systems With State Time-Delays

Chen, Kairui; Wang, Junwei; Zhang, Yun; Li, Zhi

doi:10.1109/tsmc.2018.2813399

Cited by 73 publications

(42 citation statements)

References 58 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In these methods, Hopf bifurcation theory is usually used to solve fixed time delay. Many papers calculated the upper bound of time delay by constructing Lyapunov-Krasovskii function (Chen et al, 2020; Han et al, 2015; He et al, 2016) or Lyapunov-Razumikhin function (Xie and Cheng, 2014). For time delay system, due to the complexity of its solution, few papers used Lyapunov first method to establish the consensus/tracking control criteria of MASs with time delays and compute the upper bound of time delay.…”

Section: Introductionmentioning

confidence: 99%

Leader-following consensus of second-order multi-agent systems with time-varying delays and arbitrary weights

Shi

Xie

2020

Transactions of the Institute of Measurement and Control

View full text Add to dashboard Cite

Using Lyapunov first method instead of traditional Lyapunov second method, this paper focuses on studying the consensus tracking control problem of multi-agent systems (MASs) with time-varying delays and arbitrary adjacent weights under fixed topology and switching topology, respectively. We first give four equivalent criteria for MASs with fixed communication topology, where the positive stability of matrix [Formula: see text] ( L is the Laplacian matrix of [Formula: see text], B is the leader’s adjacency matrix) not only plays a key role as usual but also becomes an urgent and more complicated problem due to the introduction of negative weights in MASs. Second, for MASs with switching communication topology if the average dwell time of switching topology, the total activation time of stable subsystems and the upper bound of time delay satisfy some conditions, then MASs with all stable subsystems (partially stable subsystems) can achieve consensus tracking. Finally, simulations are given to demonstrate the effectiveness of our theoretical results.

show abstract

Section: Introductionmentioning

confidence: 99%

Leader-following consensus of second-order multi-agent systems with time-varying delays and arbitrary weights

Shi

Xie

2020

Transactions of the Institute of Measurement and Control

View full text Add to dashboard Cite

show abstract

“…The tracking control for MASs is a common control problem, which has been widely studied [4]- [10]. Specifically, the adaptive tracking control for MASs has been investigated as one of paradigms to deal with some uncertainties [11]- [14].…”

Section: Introductionmentioning

confidence: 99%

Multi-Model Method Decentralized Adaptive Control for a Class of Discrete-Time Multi-Agent Systems

2020

View full text Add to dashboard Cite

This paper studies the decentralized adaptive tracking control problem for a class of discretetime multi-agent systems with unknown parameters and high-frequency gains using multi-model method. Each agent is strong coupling with its neighbors by the historical outputs. All agents are interacted either directly or indirectly. In the face of uncertainties, the projection algorithm as a normal adaptive method is adopted. In order to improve quality of identification, the multi-model method is taken to identify unknown parameters and high-frequency gains using switching sets of the multiple parameters' and high-frequency gains' estimates, and the index switching functions. Using the certainty equivalence principle, the control law for the hidden leader agent is designed by the desired reference signal; the control law for each follower agent is devised by neighbors' historical outputs. Moreover, the proposed decentralized adaptive control laws can guarantee the following performances of the system: (1) the leader agent tracks the reference trajectory and each follower agent follows the average value of its neighborhood historical outputs; (2) the synchronization of all the follower agents to the leader agent is achieved; (3) all the agents track the reference trajectory, and the closed-loop system eventually achieves strong synchronization. Finally, simulations validate the effectiveness on improving control performance of multi-model adaptive algorithm by comparing with the projection algorithm.

show abstract

“…However, it is assumed in the above work that there is no time delay in the followers' dynamics. In [34–36], adaptive control schemes are provided for a non‐linear MAS with unknown state delay, where the non‐linearities of the system are modelled by a NN. Furthermore, the delay terms in the non‐linear MAS are supposed to be bounded.…”

Section: Introductionmentioning

confidence: 99%

“…The main contributions of this paper are as follows: (i) The proposed method does not require the so‐called ‘strict assumption’ on the time‐delay terms in the MAS [34–36]. (ii) By the proposed approach, the singularity problem in the design of the controller is solved.…”

Section: Introductionmentioning

confidence: 99%

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

Zamani

Askari

Kamali

et al. 2020

IET Control Theory & Appl

View full text Add to dashboard Cite

In this study, a novel distributed adaptive controller is provided for consensus control of high‐order non‐linear multi‐agent systems with unknown time‐varying delays. The system is subject to uncertain disturbances, and the agents' dynamics are not known. Unlike the existing literature, the proposed method does not require time‐delay terms in system dynamics to be bounded. A neural network is used to model the unknown non‐linear dynamics. Then, despite the destabilising effect of the unknown delays, some adaptive rules based on the dynamic surface control are designed to achieve the consensus objective. The semi‐global uniform boundedness of the resultant closed‐loop signals and the convergence of the tracking errors to a neighbourhood of the origin are shown mathematically. Simulations verify the effectiveness of the results.

show abstract

Leader-Following Consensus for a Class of Nonlinear Strick-Feedback Multiagent Systems With State Time-Delays

Cited by 73 publications

References 58 publications

Leader-following consensus of second-order multi-agent systems with time-varying delays and arbitrary weights

Leader-following consensus of second-order multi-agent systems with time-varying delays and arbitrary weights

Multi-Model Method Decentralized Adaptive Control for a Class of Discrete-Time Multi-Agent Systems

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

Contact Info

Product

Resources

About