Mean-square consensus of heterogeneous multi-agent systems with nonconvex constraints, Markovian switching topologies and delays

Mo, Lipo; Guo, Shaoyan; Yu, Yongguang

doi:10.1016/j.neucom.2018.02.075

Cited by 47 publications

(37 citation statements)

References 21 publications

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“…According to Lemma 5, the matrix Q in (8) and (9) can be found by solving the linear matrix (8) and (9) provide the control design for synchronization of network (2). It is easy to see that the coupling strengths c andĉ play a key role in (8) and (9). If the coupling strengths c andĉ can be designed, the larger c and the smallerĉ can make these conditions easier to satisfy.…”

Section: Remarkmentioning

confidence: 99%

“…Remark 6. The synchronization conditions (31) and (32) are easier to verify than (8). Thus, Theorem 4 has more practical value.…”

Section: Theorem 3 (Necessary Condition) Suppose Assumptions 1-3 Holmentioning

confidence: 99%

“…Thus, Theorem 4 has more practical value. Meanwhile, the conditions (8), (31), and (32) provide a method of controller design for synchronization of the complex networks (2).…”

Section: Theorem 3 (Necessary Condition) Suppose Assumptions 1-3 Holmentioning

confidence: 99%

“…Synchronization, as one of the most important collective behaviors of complex dynamical systems, widely exists in the world, ranging from natural systems to man-made networks [7,8]. In recent years, synchronization has received a great deal of attention due to its potential application in various fields, including signal processing, secure communication, biological systems, and so on [9][10][11].…”

Section: Introductionmentioning

confidence: 99%

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Adaptive Pinning Synchronization of Fractional Complex Networks with Impulses and Reaction–Diffusion Terms

Hai

Ren

et al. 2019

Mathematics

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In this paper, a class of fractional complex networks with impulses and reaction–diffusion terms is introduced and studied. Meanwhile, a class of more general network structures is considered, which consists of an instant communication topology and a delayed communication topology. Based on the Lyapunov method and linear matrix inequality techniques, some sufficient criteria are obtained, ensuring adaptive pinning synchronization of the network under a designed adaptive control strategy. In addition, a pinning scheme is proposed, which shows that the nodes with delayed communication are good candidates for applying controllers. Finally, a numerical example is given to verify the validity of the main results.

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Section: Remarkmentioning

confidence: 99%

“…Remark 6. The synchronization conditions (31) and (32) are easier to verify than (8). Thus, Theorem 4 has more practical value.…”

Section: Theorem 3 (Necessary Condition) Suppose Assumptions 1-3 Holmentioning

confidence: 99%

“…Thus, Theorem 4 has more practical value. Meanwhile, the conditions (8), (31), and (32) provide a method of controller design for synchronization of the complex networks (2).…”

Section: Theorem 3 (Necessary Condition) Suppose Assumptions 1-3 Holmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Adaptive Pinning Synchronization of Fractional Complex Networks with Impulses and Reaction–Diffusion Terms

Hai

Ren

et al. 2019

Mathematics

Self Cite

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“…Remark 1. e Laplacian matrix of the multiagent systems is defined as H � H − D in this paper. In (7), the Laplacian of the time-varying directed graph is redefined as…”

Section: Problem Formulationmentioning

confidence: 99%

Robust Protocol‐Based ℋ_∞ Consensus Control of Time‐Varying Uncertain Multiagent Systems Subject to Missing Measurements

Sun

Chen

2019

Complexity

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In this paper, we consider the design problem of a robust H ∞ consensus controller for discrete time-varying uncertain multiagent systems (DTVUMASs) with stochastic communication protocol (SCP) and missing measurements. e SCP is described by a set of random variables with a known probability to arrange signal transmission of addressed multiagent systems. Moreover, we depict the missing measurement phenomenon by a sequence of Bernoulli-distributed random variables having known probabilities. e controller parameters are designed to ensure that the closed-loop DTVUMASs satisfy the H ∞ performance with the satisfactory consensus criterion. Together with the completing squares approach and the stochastic analysis methodology, some su cient conditions are proposed by solving coupled backward recursive Riccati di erence equations (BRRDEs) to guarantee the H ∞ consensus performance. Finally, we present a numerical simulation example to illustrate the e ectiveness of the designed controller design scheme. e consensus control problems for rst-order multiagent systems with switching topology and time delays were studied in [1], and the initiative works were conducted to solving the consensus control problems of rst-order multiagent systems (FOMASs). Since then, some control problems under certain requirements were investigated for complex dynamical systems by taking the in uences caused by nonlinearities, quantization, transmission losses, and communication noise into account, see, e.g., [3][4][5]. Besides, the consensus control problems of second-order multiagent systems (SOMASs) also received a lot of research attention. For example, the e ects of xed topology and switching topology were discussed in [6-9] and related methods were given. Subsequently, in [10], the leader-following consensus control problems of high-order multiagent systems (HOMASs) were solved by using a novel distributed eventtriggered communication protocol based on state estimates of neighboring agents. In recent years, more and more researchers pay attention to the consensus control problems for general multiagent systems (GMASs) [2,[11][12][13], where some new consensus methods were presented by designing the controller parameters. For instance, a new non-fragile consensus control method based on the output feedback technique was provided to tackle the deception attacks in quantized GMASs.Generally, we all expect the unlimited bandwidth during the communications in order to obtain satisfactory control performance, but it cannot be ensured in the engineering Hindawi Complexity

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Fault‐tolerant control of heterogeneous multi‐agent systems with state constraints

Jia

Wang

Liu

2023

Adaptive Control & Signal

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In this paper, the adaptive fault-tolerant control (FTC) problem of heterogeneous multi-agent systems (HMASs) with state constraints composed of first-order and second-order agents is studied. The problems of fault and constraints are inevitable during the operation of the system, the authors consider the fault of the system as actuator fault, and the constraints of the system can be considered as state constraints. Based on the backstepping framework, the logarithmic barrier Lyapunov function is selected to study the stability of system with constraints. For the bias fault of actuator fault, adaptive estimation is carried out, which can estimate the fault more accurately. Finally, an adaptive constrained FTC scheme is successfully designed to ensure that each signal of the system is bounded. Simulation examples show that the constrained FTC scheme is effective.

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Mean-square consensus of heterogeneous multi-agent systems with nonconvex constraints, Markovian switching topologies and delays

Cited by 47 publications

References 21 publications

Adaptive Pinning Synchronization of Fractional Complex Networks with Impulses and Reaction–Diffusion Terms

Adaptive Pinning Synchronization of Fractional Complex Networks with Impulses and Reaction–Diffusion Terms

Robust Protocol‐Based ℋ_∞ Consensus Control of Time‐Varying Uncertain Multiagent Systems Subject to Missing Measurements

Fault‐tolerant control of heterogeneous multi‐agent systems with state constraints

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Mean-square consensus of heterogeneous multi-agent systems with nonconvex constraints, Markovian switching topologies and delays

Cited by 47 publications

References 21 publications

Adaptive Pinning Synchronization of Fractional Complex Networks with Impulses and Reaction–Diffusion Terms

Adaptive Pinning Synchronization of Fractional Complex Networks with Impulses and Reaction–Diffusion Terms

Robust Protocol‐Based ℋ∞ Consensus Control of Time‐Varying Uncertain Multiagent Systems Subject to Missing Measurements

Fault‐tolerant control of heterogeneous multi‐agent systems with state constraints

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Robust Protocol‐Based ℋ_∞ Consensus Control of Time‐Varying Uncertain Multiagent Systems Subject to Missing Measurements