Abstract:Input saturation, which brings input non-linearity to systems and limits the closed-loop systems' performances severely, is an ubiquitous problem in practice. Here, triggered finitetime consensus problem of disturbed leader-follower multi-agent systems is addressed under input saturation constraint. To overcome the coupling of the non-linearity and finitetime convergence together with input saturation, non-linear triggered control protocol has been proposed, which is confirmed through a two-step stabilization … Show more
“…During the past, much attention has been given to the analysis of consensus issues, which are about first-order MASs. [7][8][9][10][11][12] In Reference 7, the fixed-time consensus tracking for nonlinear and discontinuous first-order MASs with disturbances is studied. In Reference 8, the method based on dynamic hybrid quantizer is proposed to investigate the leader-following consensus of the first-order MASs.…”
Section: Literature Reviewmentioning
confidence: 99%
“…Consider the first-order MAS (1) consisting of ten agents. Select the initial position x(0) = (10,23,13,30,11,20,18,25,36,12) T of the agents.…”
Section: Group Consensus With Reference States Of the First-order Masmentioning
confidence: 99%
“…During the past, much attention has been given to the analysis of consensus issues, which are about first‐order MASs 7‐12 . In Reference 7, the fixed‐time consensus tracking for nonlinear and discontinuous first‐order MASs with disturbances is studied.…”
Section: Introductionmentioning
confidence: 99%
“…Select the initial states x(0) =(9,21,6,10,18,15,3,13,12,25) T of the agents. Under control protocol(17), choose the pinning control gain 𝛾 10 = 2.3, 𝛾 k = 0, k = 1, 2, … , 9, reference states x 𝜗 k = 13, k = 1, 6,…”
This article investigates the group consensus via pinning control for continuous‐time first‐order and second‐order multi‐agent systems (MASs) with reference states. For the group consensus of first‐order MASs, the dependence between the agent's state and the control input is considered. For second‐order MASs, group consensus control without the velocity information of agents is considered. Instead, the virtual velocity estimation controller is designed. Meanwhile, for the designed control protocols, not only under fixed topology, but also under switching topology are considered. It is demonstrated that group consensus could be obtained under the proposed control protocols by using graph theory and stability theory. Finally, a series of numerical examples are provided to verify the control performance of the propounded control protocols.
“…During the past, much attention has been given to the analysis of consensus issues, which are about first-order MASs. [7][8][9][10][11][12] In Reference 7, the fixed-time consensus tracking for nonlinear and discontinuous first-order MASs with disturbances is studied. In Reference 8, the method based on dynamic hybrid quantizer is proposed to investigate the leader-following consensus of the first-order MASs.…”
Section: Literature Reviewmentioning
confidence: 99%
“…Consider the first-order MAS (1) consisting of ten agents. Select the initial position x(0) = (10,23,13,30,11,20,18,25,36,12) T of the agents.…”
Section: Group Consensus With Reference States Of the First-order Masmentioning
confidence: 99%
“…During the past, much attention has been given to the analysis of consensus issues, which are about first‐order MASs 7‐12 . In Reference 7, the fixed‐time consensus tracking for nonlinear and discontinuous first‐order MASs with disturbances is studied.…”
Section: Introductionmentioning
confidence: 99%
“…Select the initial states x(0) =(9,21,6,10,18,15,3,13,12,25) T of the agents. Under control protocol(17), choose the pinning control gain 𝛾 10 = 2.3, 𝛾 k = 0, k = 1, 2, … , 9, reference states x 𝜗 k = 13, k = 1, 6,…”
This article investigates the group consensus via pinning control for continuous‐time first‐order and second‐order multi‐agent systems (MASs) with reference states. For the group consensus of first‐order MASs, the dependence between the agent's state and the control input is considered. For second‐order MASs, group consensus control without the velocity information of agents is considered. Instead, the virtual velocity estimation controller is designed. Meanwhile, for the designed control protocols, not only under fixed topology, but also under switching topology are considered. It is demonstrated that group consensus could be obtained under the proposed control protocols by using graph theory and stability theory. Finally, a series of numerical examples are provided to verify the control performance of the propounded control protocols.
“…A concise overview of coordination or consensus in MASs is presented in Reference 4. Recently, there has been a tremendous surge of interest in distributed consensus control of first-order, 5 second-order, 6 and high-order MASs, 7 as well as in linear MASs with unknown external disturbances 8 and nonlinear MASs with mismatched uncertainties. 9 Distributed consensus and coordination in MASs require accurate and reliable information interaction of each agent through cyber topologies.…”
SummaryThis study addresses the issue of distributed fault‐tolerant consensus control for second‐order multi‐agent systems subject to simultaneous actuator bias faults in the physical layer and deception attacks in the cyber layer. Cyber‐physical threats (malicious state‐coupled nonlinear attacks and physical deflection faults), unknown control gains, external disturbances and uncertainties force the failure of the existing graph theory‐based consensus control schemes, leading to disruptions in the cooperation and coordination of multi‐agent systems. Then, the power integrator‐based virtual control is incorporated in the distributed fault‐tolerant consensus to achieve unknown parameter estimations with the adaptive technique. The consensus‐based robustness to lumped uncertainties, resilience to attacks, compensation to faults, and novel finite‐time convergence of the neighborhood errors and velocity errors are also realized within a prescribed finite‐time settling bound. The simulation is conducted to verify the effectiveness of the distributed finite‐time adaptive fault‐tolerant consensus algorithm.
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