Xinglong Wan, Xu Yan, Zhenxing Li, Jianlong Qiu, Chengdong Yang
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引用次数: 0
Abstract
Multi-agent systems (MASs) are widely used in many necessary fields such as cybersecurity, precision agriculture, satellites, and smart grids. In many practical processes, a proportion of states cannot be obtained directly. Therefore, it is desired to design an observer. This article explores the utilization of output-feedback adaptive control techniques to achieve consensus in MASs based on partial differential equations (PDEs) with reaction-diffusion terms and time delays. First, in dealing with time-invariant delays, an observer according to the Luenberger method is proposed to assess the state of agents. Convergence conditions of the estimated states are obtained by employing Lyapunov functions and Wirtinger inequality. Using the obtained estimated states, a boundary adaptive control strategy is proposed to make the error system consensus. The merit of this control method lies in the fact that communication between agents only occurs at the spatial boundary position, not throughout the entire spatial domain, and the parameters of the system can be constantly changed. Consensus criteria of MASs with time-invariant delays are obtained by using the output-feedback adaptive control, and the results are further generalized to the model with time-varying delays. Lastly, two experimental scenarios are provided to show the practicality of the proposed theories.
摘要多代理系统(MAS)广泛应用于网络安全、精准农业、卫星和智能电网等许多必要领域。在许多实际过程中,无法直接获得一定比例的状态。因此,人们希望设计一种观测器。本文探讨了如何利用输出反馈自适应控制技术,在基于具有反应扩散项和时间延迟的偏微分方程(PDE)的 MAS 中达成共识。首先,在处理时变延迟时,根据卢恩贝格尔方法提出了一种观测器来评估代理的状态。通过使用 Lyapunov 函数和 Wirtinger 不等式,获得了估计状态的收敛条件。利用获得的估计状态,提出了一种边界自适应控制策略,以使误差系统达成一致。这种控制方法的优点在于,代理之间的通信只发生在空间边界位置,而不是整个空间域,而且系统参数可以不断变化。通过使用输出反馈自适应控制,获得了具有时变延迟的 MAS 的共识准则,并将结果进一步推广到具有时变延迟的模型中。最后,还提供了两个实验场景来说明所提理论的实用性。
期刊介绍:
The International Journal of Adaptive Control and Signal Processing is concerned with the design, synthesis and application of estimators or controllers where adaptive features are needed to cope with uncertainties.Papers on signal processing should also have some relevance to adaptive systems. The journal focus is on model based control design approaches rather than heuristic or rule based control design methods. All papers will be expected to include significant novel material.
Both the theory and application of adaptive systems and system identification are areas of interest. Papers on applications can include problems in the implementation of algorithms for real time signal processing and control. The stability, convergence, robustness and numerical aspects of adaptive algorithms are also suitable topics. The related subjects of controller tuning, filtering, networks and switching theory are also of interest. Principal areas to be addressed include:
Auto-Tuning, Self-Tuning and Model Reference Adaptive Controllers
Nonlinear, Robust and Intelligent Adaptive Controllers
Linear and Nonlinear Multivariable System Identification and Estimation
Identification of Linear Parameter Varying, Distributed and Hybrid Systems
Multiple Model Adaptive Control
Adaptive Signal processing Theory and Algorithms
Adaptation in Multi-Agent Systems
Condition Monitoring Systems
Fault Detection and Isolation Methods
Fault Detection and Isolation Methods
Fault-Tolerant Control (system supervision and diagnosis)
Learning Systems and Adaptive Modelling
Real Time Algorithms for Adaptive Signal Processing and Control
Adaptive Signal Processing and Control Applications
Adaptive Cloud Architectures and Networking
Adaptive Mechanisms for Internet of Things
Adaptive Sliding Mode Control.