Adaptive guaranteed-performance consensus design for high-order multiagent systems

Xi, Jianxiang; Yang, Jie; Liu, Hao; Tang, Zheng

doi:10.1016/j.ins.2018.07.069

Cited by 22 publications

(15 citation statements)

References 47 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In the practical systems, convergence rate is of great significance for the consensus control of MASs owing to its enormous advantages. Asymptotic consensus relevant research results were presented in [6], [7], which means that convergence time was infinite. Consequently, finite-time control techniques were considered.…”

Section: Introductionmentioning

confidence: 99%

Adaptive Fast Finite-Time Consensus for Second-Order Uncertain Nonlinear Multi-Agent Systems With Unknown Dead-Zone

et al. 2020

View full text Add to dashboard Cite

This paper presents an adaptive fast finite-time consensus (FTC) for second-order uncertain nonlinear (UN) multi-agent systems (MASs) with unknown nonsymmetric dead-zone and external disturbances. In the process of control protocols design, based on the estimation of the dead-zone width that is obtained by using adaptive method, a fuzzy logic dead-zone compensator is adopted to deal with the nonsymmetric dead-zone input phenomenon. Combining finite-time control technique and Lyapunov's relevant theory, a new fast FTC protocol is developed. Based on the basis of radial basis function neural networks (RBFNNs) theories, the unknown nonlinear functions are approximated. Under the presented consensus protocols and adaptive laws, it can be proved that the position errors of arbitrary two agents can reach a small region of zero in finite time as well as the velocity errors. Ultimately, the effectiveness of the designed method is tested via two numerical examples.

show abstract

Section: Introductionmentioning

confidence: 99%

Adaptive Fast Finite-Time Consensus for Second-Order Uncertain Nonlinear Multi-Agent Systems With Unknown Dead-Zone

et al. 2020

View full text Add to dashboard Cite

show abstract

“…Over the past several tens of years, great progress has been made in multi-agent systems (MASs) coordination control, and scholars investigated the coordination control from different perspectives [1], [2]. As a basic and significant issue in coordination control, the consensus has gained much attention from the control community [3], [4], especially the leader-follower consensus [5], [6] or consensus tracking [7] which refers to that followers can track a leader in a distributed fashion. Whereas in earlier researches [1], [3] and [4], the coupling gains and spectra of graph matrix must meet some extra requirements, which contained the global information and did not fully utilize the distributed characteristics of MASs.…”

Section: Introductionmentioning

confidence: 99%

Distributed Robust Adaptive Learning Coordination Control for High-Order Nonlinear Multi-Agent Systems With Input Saturation

Yang

2020

IEEE Access

View full text Add to dashboard Cite

The paper involves the distributed robust adaptive learning coordination control for highorder nonlinear multi-agent systems, where the leader has nonzero input and followers are subject to input saturation. To solve the problem, two initial assumptions concerning initial state learning and alignment initial condition are introduced, and the distributed learning protocols as well as parameter adaptive laws are designed. It should be noted that the protocols proposed under initial state learning containing the global information are not fully distributed, while the fully distributed protocols can be obtained by the alignment initial condition. Through the rigorous analysis, it is proved that each follower can perfectly track the leader on a finite time interval under both two assumptions. Then, the consensus results under the alignment initial condition are generalized to formation control and two simulation examples verify the correctness and feasibility of the proposed algorithms. INDEX TERMS Adaptive coordination control, iterative learning control, high-order nonlinear multi-agent systems, input saturation.

show abstract

“…For leader‐following cases, the leader does not receive any information from followers and the states of all followers track the states of the leader when the leader‐following consensus is obtained. In other works, the consensus problems for linear multiagent systems were taken into account and some novel and interesting results were proposed.…”

Section: Introductionmentioning

confidence: 99%

Guaranteed‐performance consensus design for Lipschitz nonlinear multiagent systems with jointly connected topologies

Tang

Mei

et al. 2019

Intl J Robust & Nonlinear

Self Cite

View full text Add to dashboard Cite

Guaranteed-performance consensualization problems for both leaderless and leader-following multiagent systems with jointly connected topologies and Lipschitz nonlinear dynamics are investigated. To achieve the guaranteedperformance consensus, the control protocols and quadratic performance functions based on state errors are proposed. The state error method is utilized to deal with the guaranteed-performance consensualization problems for both leaderless and leader-following cases. Then, the Lipschitz nonlinear problems are solved by using the Lipschitz condition. Moreover, guaranteed-performance consensualization criteria for both leaderless and leader-following cases with jointly connected topologies are presented in terms of linear matrix inequalities. Meanwhile, the guaranteed-performance costs with the structure properties of both leaderless and leader-following structures are determined. Finally, two numerical simulations are presented to verify the effectiveness of the theoretical results.

show abstract

Adaptive guaranteed-performance consensus design for high-order multiagent systems

Cited by 22 publications

References 47 publications

Adaptive Fast Finite-Time Consensus for Second-Order Uncertain Nonlinear Multi-Agent Systems With Unknown Dead-Zone

Adaptive Fast Finite-Time Consensus for Second-Order Uncertain Nonlinear Multi-Agent Systems With Unknown Dead-Zone

Distributed Robust Adaptive Learning Coordination Control for High-Order Nonlinear Multi-Agent Systems With Input Saturation

Guaranteed‐performance consensus design for Lipschitz nonlinear multiagent systems with jointly connected topologies

Contact Info

Product

Resources

About