Distributed Event-Based Control of Hierarchical Leader-Follower Networks with Time-Varying Layer-To-Layer Delays

Xu, Ge Ning; Xu, Meng; Ge, Ming‐Feng; Ding, Teng-Fei; Feng, Qinghua; Li, Meng

doi:10.3390/en13071808

Cited by 7 publications

(6 citation statements)

References 35 publications

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“…As shown in Table 2, the performance of FA is determined by the value of k. To be specific, a small k produces better results than a large k for most of the functions. In order to ascertain the optimal value of k, the Friedman test is conducted in this paper on the data shown in Table 2, with the results listed in Table 3 [31].…”

Section: Investigations Of the Model Parametermentioning

confidence: 99%

A new firefly algorithm with mean condition partial attraction

Zhang

Lai

2021

Appl Intell

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As compared with other optimization algorithms (e.g., genetic algorithm, ant colony algorithm, and particle swarm algorithm), FA is relatively simple to be realized. It does not require strict continuous and differentiable conditions, requires less prior knowledge. However, it still cannot effectively avoid slow convergence and poor stability. To optimize FA for the attraction model, a new FA with mean condition partial attraction is proposed (mcFA) in this paper. McFA, characterized by fast computing power, high precision, and easy implementation, is capable of remedying the defect that the FA is easy to converge slowly. As opposed to standard FA, mcFA has determined excellent model parameter values, and the mean condition partial attraction model is more suitable for different dimensional solutions than the full attraction model. Lastly, as verified by the theoretical and experimental results, mcFA outperforms other algorithms on most of the test functions. Moreover, the mean condition partial attraction model is shown to yield better solutions than the full attraction model.

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Section: Investigations Of the Model Parametermentioning

confidence: 99%

A new firefly algorithm with mean condition partial attraction

Zhang

Lai

2021

Appl Intell

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“…To cope with time-varying layer-to-layer delays among hierarchical leaderfollowing MASs, Ref. [30] proposes a distributed ETM protocol to achieve the consensus of networks. Ref.…”

Section: Introductionmentioning

confidence: 99%

A Fully Distributed Protocol with an Event-Triggered Communication Strategy for Second-Order Multi-Agent Systems Consensus with Nonlinear Dynamics

Qiu

Zhao

2021

Sensors

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This paper presents the communication strategy for second-order multi-agent systems with nonlinear dynamics. To address the problem of the scarcity of communication channel resources and get rid of using continuous signals among the followers in lead-follower multi-agent systems, a novel event-triggered communication mechanism is proposed in this paper. To avoid employing the centralized information that depends on the Laplacian matrix spectrum, a network protocol with updated coupling gains is proposed, as well as an event-triggered strategy with updated thresholds. To eliminate the ill effects of inter-node communicating noise, relative positions are employed by the protocol instead of absolute positions. By a Lyapunov–Krasovskii functional, it is rigorously proven that the leader-following consensus of MASs is achieved without Zeno behavior, under the control of the proposed protocol with an event-triggered mechanism communication. The effectiveness of the proposed protocol is verified through numerical examples.

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“…Coordinated control for multi-agent networks has been studied with more and more attention recently owing to its diversified application value, such as consensus [ 1 , 2 , 3 ], formation [ 4 , 5 , 6 ], containment [ 7 , 8 ], flocking [ 9 , 10 ] and tracking [ 11 , 12 ] control problems. In [ 13 ], the synchronization control problem of multi-agent networks is solved by using chaos theory and the result is applied to the coupling circuits.…”

Section: Introductionmentioning

confidence: 99%

Formation Tracking Control for Multi-Agent Networks with Fixed Time Convergence via Terminal Sliding Mode Control Approach

Chen

et al. 2021

Sensors

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This paper investigates formation tracking control for multi-agent networks with fixed time convergence. The control task is that the follower agents are required to form a prescribed formation within a fixed time and the geometric center of the formation moves in sync with the leader. First, an error system is designed by using the information of adjacent agents and a new control protocol is designed based on the error system and terminal sliding mode control (TSMC). Then, via employing the Lyapunov stability theorem and the fixed time stability theorem, the control task is proved to be possible within a fixed time and the convergence time can be calculated by parameters. Finally, numerical results illustrate the feasibility of the proposed control protocol.

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Distributed Event-Based Control of Hierarchical Leader-Follower Networks with Time-Varying Layer-To-Layer Delays

Cited by 7 publications

References 35 publications

A new firefly algorithm with mean condition partial attraction

A new firefly algorithm with mean condition partial attraction

A Fully Distributed Protocol with an Event-Triggered Communication Strategy for Second-Order Multi-Agent Systems Consensus with Nonlinear Dynamics

Formation Tracking Control for Multi-Agent Networks with Fixed Time Convergence via Terminal Sliding Mode Control Approach

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