Robust stability analysis of networked systems with varying delays

Dritsas, Leonidas; Tzes, Anthony

doi:10.1080/00207170903061705

Cited by 30 publications

(29 citation statements)

References 25 publications

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“…1 polytopic uncertainties (Cloosterman et al, 2006;Heemels et al, 2010;Gielen et al, 2008) 2 norm bounded uncertainties (Shi et al, 2006;Dritsas and Tzes, 2009;Wu et al, 2011).…”

Section: Review On the Analysis And Design Of Ncssmentioning

confidence: 98%

“…In general, the considered delays have the following characteristics: 1 they are variable and limited to up a single sampling period Zhang et al, 2001;Dritsas and Tzes, 2009;Cloosterman et al, 2006) and, in some cases, they are limited to two or three sampling periods (Cloosterman et al, 2009) with bounded derivative (Niculescu et al, 2003;Gao et al, 2008) or not Zhang et al, 2001;Dritsas and Tzes, 2009) There are few models that describe arbitrary variations of delays limited to a value greater than one sample period (Yang et al, 2004;Cloosterman, 2008). The effects present in real NCS, usually, have been addressed either in isolation or in combination with certain delay condition (in the majority of cases, limited to one sampling period), e.g., the irregular sampling (Seuret, 2011), message rejection (Halevi and Ray, 1988b), quantisation noise present in the communication channel (Goodwin et al, 2008), packet losses Zhang and Yu, 2007;Sahebsaraa et al, 2008;Tian and Levy, 2008;Wang and Yang, 2010) and packet reordering .…”

Section: Review On the Analysis And Design Of Ncssmentioning

confidence: 99%

“…Regarding the methodologies used for stability analysis of NCSs, several studies published in literature (e.g., Seuret, 2011;Seuret and Silva, 2011;Cloosterman et al, 2009;Heemels et al, 2010;Dritsas and Tzes, 2009;Gao et al, 2008;and internal references), are based on Lyapunov theory, differing from each other only by the Lyapunov function adopted and by the way the uncertainties are modelled. In general, the stability analysis of the closed-loop system is performed using a quadratic Lyapunov function (Dritsas and Tzes, 2009;Heemels et al, 2010;Cloosterman et al, 2006) or a Lyapunov Krasovskii function (Gao et al, 2008;Seuret, 2011;Chen and Zheng, 2011) with LMI solutions Cloosterman et al, 2006Cloosterman et al, , 2009Dritsas and Tzes, 2009;Zhang et al, 2001;Li et al, 2004;Heemels et al, 2010).…”

Section: Review On the Analysis And Design Of Ncssmentioning

confidence: 99%

“…Some approaches incorporate the delays in the system matrix describing them as a time-varying uncertain system Cloosterman et al, 2009). The considered delays are time-varying, usually, limited to one or two sampling periods Cloosterman et al, 2006Cloosterman et al, , 2009Zhang et al, 2001;Dritsas and Tzes, 2009), and its dynamic behaviour is represented in a limited way with smooth derivatives, e.g., dτ(t) / dt ≤ 1 (Niculescu et al, 2003;Seuret, 2011). In Niculescu et al (2003), for example, it is considered that the time derivative of the delays lies between 0 and 1 and, in Seuret (2011), between -1 and 1.…”

Section: Introductionmentioning

confidence: 99%

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On the effects of time delay variations in the design of networked control system

Batista

Jota

2013

IJSCC

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Networked control system (NCS) is an emerging theme that requires the concurrence of proper tools for representation, analysis and synthesis of controlled feedback systems, aiming at reducing the existing gap between the theoretical achievement and practical applications of NCS. Given that only a few review papers on NCS delays have been published, the objective of this paper is to provide a better understanding of the existing tools for application to real NCSs with random delays. This paper presents a survey on some relevant contributions published in the literature and discusses real application limitations, with emphasis on the varying delay issues. It is highlighted the importance of considering (somehow), in the analysis and synthesis tools, the effects of delays statistics and the probability of uncertain events (present in real NCS) occur (or not).

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“…1 polytopic uncertainties (Cloosterman et al, 2006;Heemels et al, 2010;Gielen et al, 2008) 2 norm bounded uncertainties (Shi et al, 2006;Dritsas and Tzes, 2009;Wu et al, 2011).…”

Section: Review On the Analysis And Design Of Ncssmentioning

confidence: 98%

Section: Review On the Analysis And Design Of Ncssmentioning

confidence: 99%

Section: Review On the Analysis And Design Of Ncssmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

On the effects of time delay variations in the design of networked control system

Batista

Jota

2013

IJSCC

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“…By using optimal stochastic control method, Hu and Zhu [7] presented the stability analysis and the corresponding stabilizing controller design of NCSs with long time delays. By decomposing time-varying delay into fixed and varying (though bounded) parts, the NCSs with varying delays were modeled as parameter-uncertain systems and robustly delay-dependent stability conditions were presented by Xie [8], Li [9] and Dritsas [10]. With partition method for delays, Zhao [11,12] discussed the stability and guaranteed cost control of T-S fuzzy dynamic systems,respectively.…”

Section: Introductionmentioning

confidence: 99%

H ∞ control of networked control systems with packet disordering with an improved prediction-based method

Song

Wang

Shi

et al. 2011

Int. J. Control Autom. Syst.

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This paper is concerned with H ∞ control of networked control systems (NCSs) with both network-induced delay and packet disordering taken into account. A switching-based method depends on different cases of prediction numbers is presented to model the NCSs as a switched system. With the application of an improved prediciton-based method to compensate for the time delay and packet disordering, H ∞ controller is designed by solving the linear matrix inequalities (LMIs). The proposed method can be applied variously due to all kinds of prediciton numbers of the consective disordering packet have been considered, which means that our techniques are less conservative than existing literatures. Finally numerical examples and simulations are used to illustrate the effectiveness and validity of the proposed switching-based method and the improved prediction-based H ∞ controller design synthesis.

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Adaptive control and signal processing literature survey (No. 17)

2010

Adaptive Control & Signal

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In order to keep readers up-to-date, the journal will contain a list of recently published journal articles relevant to the fields of adaptive control and signal processing six times a year. This list is compiled from a wide range of journals. Please note that even though the list has been broadly categorized these classifications are by no means strict, and are there to assist the reader. Please also note that inclusion in the list is not an endorsement of a paper's quality. If you have any suggestions or comments, please email Erfu Yang at erfu.yang@eee.strath.ac.uk. ADAPTIVE SYSTEMSAhmed-Ali T, Postoyan R, Lamnabhi-Lagarrigue F. Continuous-discrete adaptive observers for state affine systems. Automatica 2009; 45(12):2986-2990. Chang Y. Adaptive sliding mode control of multi-input nonlinear systems with perturbations to achieve asymptotical stability. IEEE Transactions on Automatic Control 2009; 54(12):2863-2869. Fisher J, Bhattacharya R. Linear quadratic regulation of systems with stochastic parameter uncertainties. Automatica 2009; 45(12):2831-2841. Geromel J, Colaneri P. H ∞ and dwell time specifications of continuous-time switched linear systems. IEEE Transactions on Automatic Control 2010; 55(1):207-212. Girard A, Pola G, Tabuada P. Approximately bisimilar symbolic models for incrementally stable switched systems. IEEE Transactions on Automatic Control 2010; 55(1): 116-126. Hu G, Gans N, Fitz-Coy N, Dixon W. Adaptive homography-based visual servo tracking control via a quaternion formulation. IEEE Transactions on Control Systems Technology 2010; 18(1):128-135. Karagiannis D, Sassano M, Astolfi A. Dynamic scaling and observer design with application to adaptive control. Automatica 2009; 45(12):2883-2889. Leva A, Piroddi L, Felice M, Boer A, Paganini A. Adaptive relay-based control of household freezers with on-off actuators. Control Engineering Practice 2010; 18(1):94-102. Lin Z, Lin Y, Zhang W. A unified design for state and output feedback H ∞ control of nonlinear stochastic Markovian jump systems with state and disturbance-dependent noise. robust control of linear motors with dynamic friction compensation using modified LuGre model. Automatica 2009; 45(12):2890-2896. Mojica-Nava E, Quijano N, Rakoto-Ravalontsalama N, Gauthier A. A polynomial approach for stability analysis of switched systems. Systems and Control Letters 2010; 59(1): 98-104. Nuño E, Ortega R, Basañez L. An adaptive controller for nonlinear teleoperators. Automatica 2010; 46(1):155-159. Patre P, MacKunis W, Johnson M, Dixon W. Composite adaptive control for Euler-Lagrange systems with additive disturbances. Automatica 2010; 46(1):140-147. Sang Q, Tao G. Gain margins of adaptive control systems. IEEE Transactions on Automatic Control 2010; 55(1): 104-115. Tanelli M, Picasso B, Bolzern P, Colaneri P. Almost sure stabilization of uncertain continuous-time Markov jump linear systems. IEEE Transactions on Automatic Control 2010; 55(1):195-201. Wang J, Hovakimyan N, Cao C. Verifiable adaptive flight control: unmanned combat aerial vehicle and a...

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Robust stability analysis of networked systems with varying delays

Cited by 30 publications

References 25 publications

On the effects of time delay variations in the design of networked control system

On the effects of time delay variations in the design of networked control system

H ∞ control of networked control systems with packet disordering with an improved prediction-based method

Adaptive control and signal processing literature survey (No. 17)

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