Output feedback stabilisation for uncertain nonlinear time-delay systems subject to input constraints

Goodall, D.P.

doi:10.1080/00207170903377119

Cited by 10 publications

(6 citation statements)

References 24 publications

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“…Then, pre-and post-multiplying (28) by diag{I, I, I, j∈S ij P j H −T i , S 1 H −T i , S 2 H −T i , I, I, I } and its transpose lead to (13). Similar to the above deduction, we can obtain that (26) can imply (12), respectively.…”

Section: Proofmentioning

confidence: 68%

“…RELIABLE H ∞ FILTERING 555 challenging to study Markovian jumping systems with partly unknown transition probabilities, see [5,9] for some recently available works.In practice, time delays are frequently encountered in dynamical systems because of the finite switching speed of the amplifiers. The existence of time-delays may deteriorate the system performance and even result in the instability of the systems [13][14][15][16][17][18]. Specifically, for Markovian jumping systems with time delays, a great number of results have been reported, see e.g.…”

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confidence: 99%

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Reliable H∞ filtering for discrete time-delay Markovian jump systems with partly unknown transition probabilities

Liu

Wang

2011

Int. J. Adapt. Control Signal Process.

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In this paper, the reliable H ∞ filtering problem is studied for a class of discrete nonlinear Markovian jump systems with sensor failures and time delays. The transition probabilities of the jumping process are assumed to be partly unknown. The failures of sensors are quantified by a variable taking values in a given interval. The time-varying delay is unknown with given lower and upper bounds. The purpose of the addressed reliable H ∞ filtering problem is to design a mode-dependent filter such that the filtering error dynamics is asymptotically mean-square stable and also achieves a prescribed H ∞ performance level. By using a new Lyapunov-Krasovskii functional and delay-partitioning technique, sufficient delay-dependent conditions for the existence of such a filter are obtained. The filter gains are characterized in terms of the solution to a convex optimization problem that can be easily solved by using the semi-definite programme method. A numerical example is provided to demonstrate the effectiveness of the proposed design approach.

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Section: Proofmentioning

confidence: 68%

mentioning

confidence: 99%

Reliable H∞ filtering for discrete time-delay Markovian jump systems with partly unknown transition probabilities

Liu

Wang

2011

Int. J. Adapt. Control Signal Process.

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“…In [14], H ∞ stabilization control for the time-delay Takagi-Sugeno fuzzy systems under nonlinear perturbations and sampled-data input was investigated. By using output feedback, the authors of [15] studied the robust stabilization problem of a class of time-varying time-delay dynamical systems, which were not perfectly known, where the system output was modeled through a nonlinear function depending on the delayed inputs and states. In [16], the state-feedback stability control of switched discrete-time singular systems in the presence of time-varying state delays was presented.…”

Section: Introductionmentioning

confidence: 99%

An LMI Approach to Nonlinear State-Feedback Stability of Uncertain Time-Delay Systems in the Presence of Lipschitzian Nonlinearities

et al. 2020

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This article proposes a new nonlinear state-feedback stability controller utilizing linear matrix inequality (LMI) for time-delay nonlinear systems in the presence of Lipschitz nonlinearities and subject to parametric uncertainties. Following the Lyapunov–Krasovskii stabilization scheme, the asymptotic stability criterion resulted in the LMI form and the nonlinear state-feedback control technique was determined. Due to their significant contributions to the system stability, time delays and system uncertainties were taken into account while the suggested scheme was designed so that the system’s stabilization was satisfied in spite of time delays and system uncertainties. The benefit of the proposed method is that not only is the control scheme independent of the system order, but it is also fairly simple. Hence, there is no complexity in using the proposed technique. Finally, to justify the proficiency and performance of the suggested technique, a numerical system and a rotational inverted pendulum were studied. Numerical simulations and experimental achievements prove the efficiency of the suggested control technique.

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“…Note that the time-delay has long been a focus in systems modeling and control, see e.g. [Lu and Ho 2010;Lu et al 2009;Meng et al 2009;Karimi and Gao 2010;Goodall and Postoyan 2010]. Moreover, δ(t) is a Bernoulli distributed variable defined by…”

Section: Problem Formulation and Preliminariesmentioning

confidence: 99%

Distributed state estimation in sensor networks with randomly occurring nonlinearities subject to time delays

Liang

Wang

Shen

et al. 2012

ACM Trans. Sen. Netw.

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This paper is concerned with a new distributed state estimation problem for a class of dynamical systems in sensor networks. The target plant is described by a set of differential equations disturbed by a Brownian motion and randomly occurring nonlinearities (RONs) subject to timedelays. The RONs are investigated here to reflect network-induced randomly occurring regulation of the delayed states on the current ones. Through available measurement output transmitted from the sensors, a distributed state estimator is designed to estimate the states of the target system, where each sensor can communicate with the neighboring sensors according to the given topology by means of a directed graph. The state estimation is carried out in a distributed way and is therefore applicable to online application. By resorting to the Lyapunov functional combined with stochastic analysis techniques, several delay-dependent criteria are established that not only ensure the estimation error to be globally asymptotically stable in the mean square, but also guarantee the existence of the desired estimator gains that can then be explicitly expressed when certain matrix inequalities are solved. A numerical example is given to verify the designed distributed state estimators.

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Output feedback stabilisation for uncertain nonlinear time-delay systems subject to input constraints

Cited by 10 publications

References 24 publications

Reliable H∞ filtering for discrete time-delay Markovian jump systems with partly unknown transition probabilities

Reliable H∞ filtering for discrete time-delay Markovian jump systems with partly unknown transition probabilities

An LMI Approach to Nonlinear State-Feedback Stability of Uncertain Time-Delay Systems in the Presence of Lipschitzian Nonlinearities

Distributed state estimation in sensor networks with randomly occurring nonlinearities subject to time delays

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