Decentralised adaptive synchronisation of a class of discrete-time and nonlinearly parametrised coupled multi-agent systems

Zhang, Xinghong; Ma, Hongbin; Zhang, Chao

doi:10.1080/00207179.2019.1598577

Cited by 6 publications

(16 citation statements)

References 36 publications

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“…Several effective methods have been proposed to address the consensus issue of MASs. [9][10][11][12][13][14][15][16][17] Fully distributed control methods have been applied to avoid the use of global data in linear MASs. 9 A decentralized adaptive control method was investigated by combining the projection algorithm with certainty equivalence principle.…”

Section: Introductionmentioning

confidence: 99%

“…9 A decentralized adaptive control method was investigated by combining the projection algorithm with certainty equivalence principle. 10,11 The consensus issue on the communication topology under the leader-follower framework has been explored. 12,13 The consensus issue of MASs has been considered under switching topologies.…”

Section: Introductionmentioning

confidence: 99%

“…Multiples can be deployed in combination through the communication and coordination cooperation between agents to achieve more complex missions than the use of one agent alone. Several effective methods have been proposed to address the consensus issue of MASs 9–17 . Fully distributed control methods have been applied to avoid the use of global data in linear MASs 9 .…”

Section: Introductionmentioning

confidence: 99%

“…Fully distributed control methods have been applied to avoid the use of global data in linear MASs 9 . A decentralized adaptive control method was investigated by combining the projection algorithm with certainty equivalence principle 10,11 . The consensus issue on the communication topology under the leader‐follower framework has been explored 12,13 .…”

Section: Introductionmentioning

confidence: 99%

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Event‐triggered model‐free adaptive consensus tracking control for nonlinear multi‐agent systems under switching topologies

Wang

et al. 2022

Intl J Robust & Nonlinear

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A distributed event-triggered data-based control protocol is proposed for a class of unknown nonlinear heterogeneous multi-agent systems (MASs) to address consistent reference signal tracking issue subject to the limited communication bandwidth. First, an event-triggering condition that only relies on local output data of each agent is designed, and the event-triggered communication between different agents depends on this condition. Second, agent models are constructed dynamically using dynamic linearization technology. Third, a novel distributed data-driven control strategy based on event-triggered communication mechanism is designed for heterogeneous agents to realize consistent desired trajectory tracking mission under switching topologies. The proposed control protocol is characterized by the information transmission of each agent in a fully intermittent manner without any global I/O (Input and Output) data. On this basis, convergence performance is analyzed using the principle of compressed mapping. Results showed that the tracking error of all agents is uniformly bounded. Effectiveness of the proposed method is verified through two numerical experiments.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Event‐triggered model‐free adaptive consensus tracking control for nonlinear multi‐agent systems under switching topologies

Wang

et al. 2022

Intl J Robust & Nonlinear

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“…For identifying model structure uncertainty, fuzzy logic algorithm, neural networks (NNs) and wavelet are applied in [16]- [19]. Thus, facing to uncertainties, in the tracking control community, the adaptive control of the MASs with model parameters and model structure uncertainties have been investigated in [20]- [22].…”

Section: Introductionmentioning

confidence: 99%

Decentralized Adaptive Tracking Control of a Class of Nonlinear Discrete-Time Coupled Multi-Agent Systems With Unknown Dynamics

Zhang

2020

IEEE Access

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This paper studies the trajectory tracking control of a class of multi-agent systems, in which, each agent is expressed by a nonlinear discrete-time unknown dynamics and can interact with its neighbors via the history outputs of its neighbors. In order to tackle each unknown dynamics, based on its neighbors' and its own history I/O data and neural network, an approximate model is established by the direct data-driven method. Using the neighbors' history information and the reference trajectory, the decentralized adaptive indirect data-driven control is designed; then, the feedback gain matrix online is designed and adjusted by measured output data and previous estimates. For each agent, this is an adaptive control process of prediction, estimation, and adjustment, which needs to solve some nonlinear optimization problems online, can surmount the negative effects of the modeling errors caused by neural networks, and is the key to making each agent output asymptotically track the given reference trajectory. The convergence analysis shows that the applied method is effective and feasible. INDEX TERMS Multi-agent system, tracking control, indirect data-driven method, adaptive control, nonlinear discrete-time system.

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Multiple models for decentralised adaptive control of discrete‐time systems

Makam,

George

2024

Adaptive Control & Signal

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This paper investigates decentralised adaptive control of discrete‐time systems consisting of linear time‐invariant systems and a class of nonlinear systems. The parameters of the subsystems and the interconnection strengths between the subsystems are assumed unknown. Multiple adaptive prediction models with switching are used in this paper to address the relatively poor transient performance that typically results from a single prediction model. However, the application of this methodology requires indirect model reference discrete‐time adaptive control, and there appears to be very little focus in the literature on this. The principal contribution of this paper is to fill this void by arriving at proof of global stability of such decentralised adaptive systems using the theory of Lyapunov and properties of square‐summable sequences. The chosen representation of the system enables the same results to be directly applicable to both linear time‐invariant and linear‐in‐the‐parameters nonlinear subsystems. We consider two parametric update algorithms, one of which has a normalisation factor. Simulation studies included in this paper demonstrate the improvement in transient performance.

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Decentralised adaptive synchronisation of a class of discrete-time and nonlinearly parametrised coupled multi-agent systems

Cited by 6 publications

References 36 publications

Event‐triggered model‐free adaptive consensus tracking control for nonlinear multi‐agent systems under switching topologies

Event‐triggered model‐free adaptive consensus tracking control for nonlinear multi‐agent systems under switching topologies

Decentralized Adaptive Tracking Control of a Class of Nonlinear Discrete-Time Coupled Multi-Agent Systems With Unknown Dynamics

Multiple models for decentralised adaptive control of discrete‐time systems

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