Stabilization of networked control systems with both network-induced delay and packet dropout

Tan, Cheng; Li, Lin; Zhang, Huanshui

doi:10.1016/j.automatica.2015.06.026

Cited by 142 publications

(71 citation statements)

References 17 publications

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“…, network‐induced delays, data packet dropouts and disordering. These make the analysis and design of NCSs more complex than traditional control systems . Most NCS mechanisms so far are based on time‐triggered communications, which means that all sampled‐data are transmitted over the communication networks at a fixed interval.…”

Section: Introductionmentioning

confidence: 99%

Mixed Event‐Triggered Mechanism Modeling and Controlling for Networked Control Systems with Time‐Varying Delays and Uncertainties

Liu

2018

Asian Journal of Control

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This paper is concerned with modeling and controlling under the mixed event‐triggered mechanism (ETM) for networked control systems (NCSs) with time‐varying delays and uncertainties. Firstly, an event‐triggered threshold is set by using both state and state‐independent informations in the mixed ETM. Then the event‐triggered NCSs with network‐induced time‐varying delays which exist in both sensor‐to‐controller and controller‐to‐actuator channels are modeled as a general time‐delay system. Based on the piecewise differentiable characteristic of the time‐varying delay and by using the approach of free weighting matrix and reciprocally convex, a less conservative criterion to be globally uniformly ultimately bounded (GUUB) stability and a controller design method are derived. Furthermore, an algorithm is proposed to obtain the desired mixed ETM and state‐feedback controller which can render the network load and control performance to reach an expected level. Compared with the relative and absolute ETMs, the proposed mechanism can effectively improve the transmission efficiency during the whole working time. Finally, a numerical example is given to show the effectiveness of the proposed approach.

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Section: Introductionmentioning

confidence: 99%

Mixed Event‐Triggered Mechanism Modeling and Controlling for Networked Control Systems with Time‐Varying Delays and Uncertainties

Liu

2018

Asian Journal of Control

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“…According to [11,Theorem 3], for any sub-system i, if {γ i k : k = 1, 2, · · · , } are i.i.d. with P (γ i k = 0) = q i , where q i ∈ [0, 1] is called the packet dropout rate of sub-system i, then sub-system i is (mean-square) stable if and only if 4…”

Section: A Maximum Dropout Rate Of Control System [11]mentioning

confidence: 99%

“…is the predicted state in frame k + 1 based on the observation of the state in frame k and the control variable in frame k − 1. Please refer to [11] for the details and proofs.…”

Section: A Maximum Dropout Rate Of Control System [11]mentioning

confidence: 99%

On Stability Condition of Wireless Networked Control Systems under Joint Design of Control Policy and Network Scheduling Policy

Deng

Tan

Wong

2018

2018 IEEE Conference on Decision and Control (CDC)

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In this paper, we study a wireless networked control system (WNCS) with N ≥ 2 sub-systems sharing a common wireless channel. Each sub-system consists of a plant and a controller and the control message must be delivered from the controller to the plant through the shared wireless channel. The wireless channel is unreliable due to interference and fading. As a result, a packet can be successfully delivered in a slot with a certain probability. A network scheduling policy determines how to transmit those control messages generated by such N subsystems and directly influences the transmission delay of control messages. We first consider the case that all sub-systems have the same sampling period. We characterize the stability condition of such a WNCS under the joint design of the control policy and the network scheduling policy by means of 2 N linear inequalities. We further simplify the stability condition into only one linear inequality for two special cases: the perfect-channel case where the wireless channel can successfully deliver a control message with certainty in each slot, and the symmetric-structure case where all sub-systems have identical system parameters. We then consider the case that different sub-systems can have different sampling periods, where we characterize a sufficient condition for stability.

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“…In addition to the sampling interval, the packet dropout is another critical factor that affects the performance. When consecutive dropouts occur, the system's performance further degrades or even becomes unstable . Usually, sampling intervals, packet dropouts, and communication delays are modeled as a time‐varying delay; hence, in most cases, NCSs are treated and studied as the time‐delay systems …”

Section: Introductionmentioning

confidence: 99%

“…When consecutive dropouts occur, the system's performance further degrades or even becomes unstable. 6 Usually, sampling intervals, packet dropouts, and communication delays are modeled as a time-varying delay; hence, in most cases, NCSs are treated and studied as the time-delay systems. 7 In the time domain, the Lyapunov-Krasovskii functional (LKF) method has been widely used for analyzing such time-delay systems.…”

Section: Introductionmentioning

confidence: 99%

Robust ‐gain codesign of networked control systems

Sun

Zeng

Luo

et al. 2018

Intl J Robust & Nonlinear

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Summary This paper examines the problem of codesigning a robust L2‐gain networked control system along with the network's properties such as sampling interval, service rate, and packet dropout. On the basis of the generalized integral inequality of Bessel‐Legendre inequality approach, sufficient conditions for the existence of a robust L2‐gain controller that incorporates the network's properties are derived and expressed in terms of linear matrix inequalities. Finally, two examples are used to illustrate the effectiveness of the proposed methodology.

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Stabilization of networked control systems with both network-induced delay and packet dropout

Cited by 142 publications

References 17 publications

Mixed Event‐Triggered Mechanism Modeling and Controlling for Networked Control Systems with Time‐Varying Delays and Uncertainties

Mixed Event‐Triggered Mechanism Modeling and Controlling for Networked Control Systems with Time‐Varying Delays and Uncertainties

On Stability Condition of Wireless Networked Control Systems under Joint Design of Control Policy and Network Scheduling Policy

Robust ‐gain codesign of networked control systems

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