Modified performance of MIMO wireless networked time‐delay systems over fading channels

Asian Journal of Control

et al. 2021

In this work, we study the error limits of the network delay systems in terms of bandwidth and packet loss. The tracking error index of networked delay systems is identified by the tracking error energy. The error limits of the network delay systems are achieved by the spectral decomposition and partial decomposition techniques. The results of this work show that the tracking error limits are relevant to the inherent characteristics of the provided object (non‐minimum phase zero, time delay, and unstable pole). In addition, the packet loss, channel noise, and bandwidth also determine the error limits of the network delay systems. The simulation results show that the theory presented is valid.

“…According to the result presented in [28], we get the following expression.

{‖(L_{z}^{- 1} - 1) ϕ_{1}‖}_{2}^{2} = \sum_{i = 1}^{n} 2 Re (z_{i}) ϕ_{1}^{2}

We define

J_{11}^{*} = \inf_{Q \in ℜ H_{\infty}} {‖\frac{(e^{τ s} - N_{m} Y)}{B_{p}} ϕ_{1} - N_{m} Q M_{m} ϕ_{1}‖}_{2}^{2} .

Based on the partial fraction procedure,

\begin{matrix} J_{11}^{*} & = \inf_{Q \in ℜ {normalH}_{\infty}} (‖‖, false(\sum_{j \in m} ((), \frac{{\overset{p}{true}}_{j} + s}{s - p_{j}}) \frac{e^{τ p_{j}} - {normalN}_{m} ((), p_{j}) Y ((), p_{j})}{b_{j}} + R_{1} - N_{m} Q M_{m} false) ϕ...) \end{matrix}

…”

Section: Problem Formulationmentioning

confidence: 99%

Performance limits of network delay systems based on bandwidth and packet loss constraints

Asian Journal of Control

et al. 2021

“…In recent years, researches on distributed cooperative control of multi-agent system have attracted widespread attention because of wide applications by many researchers (Hu et al, 2021;Lu et al, 2021;Zhan et al, 2020Zhan et al, , 2021, such as robot manipulators systems, unmanned air vehicles, underwater vehicle, and so on. Consensus is a typical problem in the field of cooperative control for multi-agent system (Wang et al, 2022;Wu et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

Fixed-time consensus of second-order multi-agent systems with nonlinear dynamics

Transactions of the Institute of Measurement and Control

et al. 2023

Self Cite

The authors mainly discuss finite-time tracking consensus and fixed-time tracking consensus of multi-agent systems for second-order with inherent nonlinear function and disturbance under a directed interaction graph in this work. By sliding mode control theory, consensus tracking controllers are proposed to ensure that sliding mode can be reached and maintain on it in finite time and fixed time. By using some theoretical knowledge of control, such as graph theory and Lyapunov theory, we make the system to reach consensus in finite time and fixed time by choosing the right parameters. In addition, the calculation leads to the conclusion that settling time of finite-time consensus is associated to initial state, while settling time of fixed-time consensus is interrelated to parameters but not to the initial state. The feasibility of the theory is proved by simulation experiments.

“…As network communication technology advances, the control system becomes more networked and intelligent [1][2][3][4], and the networked control system (NCS) emerges accordingly. Compared with conventional control systems, NCS offers advantages of strong flexibility, low cost, simple installation and maintenance, lightweight, and low power consumption [5][6][7][8][9].…”

Section: Introductionmentioning

confidence: 99%

Regulation performance limitation of networked time‐delay systems with incomplete information

Yang

Asian Journal of Control

et al. 2022

In this paper, the regulation performance limitation of networked time‐delay systems is studied. The communication network is mainly affected by parameters such as packet dropouts, encoding‐decoding, interference signal, and channel noises. Non‐minimum phase zeros, unstable poles, and time delay are all considered for a given plant. The corresponding regulation performance expression is derived using coprime factorization and spectral decomposition techniques in the frequency domain. The results indicate that the regulation performance of the system is related to the inherent characteristics of the given plant, including non‐minimum phase zeros, unstable poles, and time delay. Additionally, network communication parameters such as white Gaussian noise, packet dropouts, encoding‐decoding, and external interference signals all affect the regulation performance of networked time‐delay systems. Finally, some simulation examples are provided to demonstrate the effectiveness of the theory.