An improved delay-dependent stability criterion of networked control systems

Liu, Yuzhi; Li, Muguo

doi:10.1016/j.jfranklin.2013.12.002

Cited by 36 publications

(31 citation statements)

References 29 publications

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“…From equation (1), the load disturbance of DC motor speed control system is modelled as time-varying non-linear disturbance in current x(t) and delayed state vector Fang, 1998;He et al, 2007;Jeeva Sathya Theesar and Balasubramanian, 2013;Jiang et al, 2012;Krishnan et al, 2017;Krishnasamy and Balasubramanian, 2015;Liu and Cheng, 2016;Liu and Li, 2014;Liu, 2013Liu, , 2014Liu, , 2015Ramakrishnan and Ray, 2010. They are considered to satisfy ( ) ( ) 0, 0, 0 f t g t = = and following normbounded condition .…”

Section: Load Disturbance Model For Time Delaymentioning

confidence: 99%

“…In this paper, an effort has been done to address the problem of delay-dependent stability of DC motor speed control system considered into an account the effect of disturbance in the stability analysis (Fang, 1998;Jeeva Sathya Theesar and Balasubramanian, 2013;Jiang et al, 2012;Krishnan et al, 2017;Liu and Li, 2014;Park and Ko, 2007;Park et al, 2011;Ramakrishnan and Ray, 2010Zhu and Yang, 2008). In the stability analysis novelty is importantly lies in the modelling of load disturbance of a current and delayed state vectors (Jeeva Sathya Theesar and Balasubramanian, 2013; Krishnan et al, 2017;Ramakrishnan and Ray, 2010Fang, 1998).…”

Section: Introductionmentioning

confidence: 99%

“…where h and μ are the upper bound of the time-varying delay and the derivative of the delay, respectively, 1 μ < (Liu and Li, 2014).…”

Section: Introductionmentioning

confidence: 99%

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LMI based stability analysis of non-linearly perturbed DC motor speed control system with constant and time-varying delays

Venkatachalam¹,

Prabhakaran²,

Thirumarimurugan³

et al. 2019

IJPELEC

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This research work describes the time-delays effect on speed control of DC motor system with non-linear load disturbance in the states. With this task, the paper presents a linearised model of speed control system based on delay-dependent state equation. Since the non-linearly load disturbance in the DC motor system (with time delay) ultimately affects the evolution of the system states, the non-linear load disturbance is modelled (mathematical) as a non-bounded non-linear function of current state vector and delayed state vector, subsequently included into the system stability analyses. In the analysis, two cases are employed: constant time delay and time-varying delay with exogenous load disturbance. In the proposed results, for broad range of PI controller gains, the maximum value of upper bound delay of DC motor speed control system are determined and new stability criterion was identified.Reference to this paper should be made as follows: Venkatachalam, V., Prabhakaran, D., Thirumarimurugan, M. and Ramakrishnan, K. (2019) 'LMI based stability analysis of non-linearly perturbed DC motor speed control system with constant and time-varying delays', Int. ). His research interests include convex optimisation techniques, robust control analysis/synthesis applied to time-delay systems, optimal control and LMI optimisation. This paper is a revised and expanded version of a paper entitled 'LMI based stabılıty analysıs of non-lınearly perturbed dc motor speed control system wıth constant and tıme-varyıng delays' presented at

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Section: Load Disturbance Model For Time Delaymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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LMI based stability analysis of non-linearly perturbed DC motor speed control system with constant and time-varying delays

Venkatachalam¹,

Prabhakaran²,

Thirumarimurugan³

et al. 2019

IJPELEC

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“…Gao et al [19] took advantages of ( − ℎ) to derive a stability criterion, which improved over that in [18], but another marginally delayed state ( − ℎ 1 ) was not employed. In this paper one makes use of it to construct the Lyapunov functional ( ) in (15), thus making − ∫…”

Section: Stability Analysismentioning

confidence: 99%

“…The transmission delay generally includes the sensor-to-control delay and the control-to-actuator delay. In most of existing papers the sensor-to-control delay and the control-to-actuator delay were combined into one state delay, while the data packet dropouts were modeled as delays and absorbed by the state delay, thus formulating networked control systems as systems with one state delay [15]. Among recently reported results based on this modeling idea, to mention a few, event-triggered communication and ∞ control codesign problems were addressed for networked control systems in [16], while exponential state estimation problems were considered for Markovian jumping neural networks in [17].…”

Section: Introductionmentioning

confidence: 99%

H∞Control for a Networked Control Model of Systems with Two Additive Time-Varying Delays

Shao

Zhang

Zhu

et al. 2014

Abstract and Applied Analysis

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This paper is concerned withH∞control for a networked control model of systems with two additive time-varying delays. A new Lyapunov functional is constructed to make full use of the information of the delays, and for the derivative of the Lyapunov functional a novel technique is employed to compute a tighter upper bound, which is dependent on the two time-varying delays instead of the upper bounds of them. Then the convex polyhedron method is proposed to check the upper bound of the derivative of the Lyapunov functional. The resulting stability criteria have fewer matrix variables but less conservatism than some existing ones. The stability criteria are applied to designing a state feedback controller, which guarantees that the closed-loop system is asymptotically stable with a prescribedH∞disturbance attenuation level. Finally examples are given to show the advantages of the stability criteria and the effectiveness of the proposed control method.

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Quantized filtering for networked Takagi–Sugeno fuzzy systems with multipath data packet dropouts

Nithya¹,

Sakthivel

Kong

et al. 2023

Math Methods in App Sciences

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This paper concerns the mixed H ∞ and passivity-based filtering problem for networked nonlinear systems with randomly occurring parameter uncertainties, multipath data packet dropouts, time-varying delay, and quantization effects.The discrete-time nonlinear plant considered in this paper is modeled as a Takagi-Sugeno fuzzy system with plant rules. The data missing phenomenon is considered in both measurement and performance output signals due to the unreliable nature of communication links. Further, to reduce the network bandwidth utilization, the measurement quantization is also employed for both the outputs before transmitting through the communication channel. Also, additive filter gain fluctuation is taken into account to reflect the imprecision in filter implementation. Stochastic variables obeying the Bernoulli distribution are incorporated in the model description to characterize the random occurrence of parameter uncertainties and data packet dropouts. A set of sufficient conditions assuring the stochastic stability of the filtering error system with mixed H ∞ and passivity performance is derived according to Lyapunov stability theory. Finally, three numerical examples including mass-spring-damper and tunnel diode circuit model are established to establish the validity of the developed filter design algorithm.

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An improved delay-dependent stability criterion of networked control systems

Cited by 36 publications

References 29 publications

LMI based stability analysis of non-linearly perturbed DC motor speed control system with constant and time-varying delays

LMI based stability analysis of non-linearly perturbed DC motor speed control system with constant and time-varying delays

H∞Control for a Networked Control Model of Systems with Two Additive Time-Varying Delays

Quantized filtering for networked Takagi–Sugeno fuzzy systems with multipath data packet dropouts

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