Table of Contents Author Guidelines Submit a Manuscript
Abstract and Applied Analysis
Volume 2014 (2014), Article ID 409819, 9 pages
http://dx.doi.org/10.1155/2014/409819
Research Article

Stability Criteria for Singular Stochastic Hybrid Systems with Mode-Dependent Time-Varying Delay

School of Aeronautics and Astronautics, Shanghai Jiao Tong University, Shanghai 200240, China

Received 31 October 2013; Revised 19 January 2014; Accepted 14 February 2014; Published 23 March 2014

Academic Editor: Daoyi Xu

Copyright © 2014 Ming Zhao et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

This paper provides a delay-dependent criterion for a class of singular stochastic hybrid systems with mode-dependent time-varying delay. In order to reduce conservatism, a new Lyapunov-Krasovskii functional is constructed by decomposing the delay interval into multiple subintervals. Based on the new functional, a stability criterion is derived in terms of strict linear matrix inequality (LMI), which guarantees that the considered system is regular, impulse-free, and mean-square exponentially stable. Numerical examples are presented to illustrate the effectiveness of proposed method.

1. Introduction

Over the past years, a lot of attention has been devoted to singular systems, which are also referred to as descriptor systems, generalized state-space systems, differential-algebraic systems, or semistate systems, because they can better describe physical systems than regular ones. Since the introduction of the first model for a jump system by Krasovskii and Lidskiĭ [1], the Markovian jump systems have become more popular in the area of control and operation research due to the fact that they are more powerful and appropriate to model varieties of systems mainly those with abrupt changes in their structure [26]. Consequently, singular hybrid systems or say singular systems with Markovian switching have been extensively studied in recent years. For more details on this class of systems, we refer the readers to see [710] and the references therein.

As is well known, environmental noise exists and cannot be neglected in many dynamical systems [11]. The systems with noise are called stochastic system. Up to date, some results have been reported on stochastic systems with Markovian switching [1216]. It should be pointed out that the problems of stability and control for singular stochastic systems with Markovian switching or say singular stochastic hybrid systems are more complicated than that for regular ones, because the singular systems usually have three types of modes, namely, finite-dynamic modes, impulsive modes, and nondynamic modes, while the latter two do not appear in state-space systems. That is the reason why only a few results have been reported on this class of systems in the literature. In [17], the stochastic stability and stochastic stabilization for a class of nonlinear singular stochastic hybrid systems were investigated. The problem of sliding mode control for singular stochastic hybrid systems was investigated in [18]. In [19], under an assumption, authors study the problem of mean-square stability for singular stochastic systems with Markovian switching. However, no time delay was considered in [1719], which often causes instability and poor performance of the systems [20]. In addition, the stability conditions in [1719] are difficult to calculate since the equality constraints are used, which are often fragile and usually not met perfectly. To the author’s best knowledge, the problem of delay-dependent mean-square exponential stability for singular stochastic hybrid systems with mode-dependent time-varying delay has not been fully investigated, which remains important and challenging.

This paper will focus on the derivation of delay-dependent mean-square exponential stability for a class of singular stochastic hybrid systems with mode-dependent time-varying delay. Inspired by the discretized Lyapunov functional method proposed by Gu [21], a new Lyapunov-Krasovskii functional is constructed to reduce conservatism. Based on the functional, a delay-dependent stability criterion is proposed, which guarantees that the system is regular, impulse-free, and mean-square exponentially stable. The criterion is formulated in terms of strict LMI, which can be easily solved by standard software. Finally, two examples are given to illustrate the effectiveness of proposed method.

Notation. denotes the -dimensional Euclidean space; is the set of all real matrices. denotes the Banach space of continuous vector functions mapping the interval into with norm . is a probability space, is the sample space, is the -algebra of subsets of the sample space, and is the probability measure on . denotes the expectation operator with respect to some probability measure . The superscript “” denotes the term that is induced by symmetry.

2. Problem Formulation and Preliminaries

Let be a continuous-time Markov process with a right continuous trajectory taking values in a finite set with transition probability matrix given by where , , , and for each .

Fix a probability space and consider the singular stochastic system with Markovian switching as follows: where is the state vector, is a scalar Brownian motion defined on a probability space. may be singular; we assume that rank . , , , and are real constant matrices of appropriate dimensions.

For notational simplicity, in the sequel, for each possible , , a matrix will be denoted by ; for example, is denoted by , is denoted by , and so on.

The mode-dependent time-varying delay is a time-varying continuous function that satisfies where and are constants; is the initial condition of continuous state with .

The following preliminary assumption is made for system (2).

Assumption 1. For singular stochastic hybrid system (2), the following condition is satisfied:
The objective of this paper is to present a criterion for mean-square exponential stability of system (2). It should be pointed out that, for simplicity only, we do not consider uncertainties and disturbance input in our models. The proposed method can also be easily extended to systems with multiple and distributed delays.
The following definition and lemma will be used.

Definition 2 (see [22]). (1) System (2) is said to be regular and impulse-free for any time delay satisfying (3), if the pairs and are regular and impulse-free for each .
(2) System (2) is said to be mean-square exponentially stable, if there exist scalars and such that , .
(3) System (2) is said to be mean-square exponentially admissible, if it is regular, impulse-free, and mean-square exponentially stable.

Lemma 3 (see [23]). Suppose that a positive continuous function satisfies where , , , , and ; then

Lemma 4 (see [24]). For any vectors , scalar , and matrix with appropriate dimension, the following inequality is always satisfied:

3. Stability of Singular Stochastic Hybrid Systems

In this section, we study the mean-square exponential stability of singular hybrid system (2).

Theorem 5. For any delays satisfying (3), the singular stochastic hybrid system (2) is mean-square exponentially admissible for , if there exist symmetric matrices , , , , , , and and matrices , , , , with appropriate dimensions such that for each , wherewith and is any matrix with full rank and satisfying .

Proof. We first show that the system (2) is regular and impulse-free.
Since rank , there exist nonsingular matrices and such that
Then, can be parameterized as , where is any nonsingular matrix.
Define
Premultiplying and postmultiplying by and , respectively, we have and thus is nonsingular. Otherwise, supposing is singular, there must exist a nonzero vector which ensures that . Then, we can conclude that , and this contradicts (15). So is nonsingular, and thus the pair is regular and impulse-free for each . Since , we can easily see that the pair is regular and impulse-free. On the other hand, premultiplying and postmultiplying by and , respectively, we have
This implies that the pair is regular and impulse-free for each according to Theorem 10.1 of [25]. Then, by Definition 2, system (2) is regular and impulse part.
In the following, we will prove the mean-square exponential stability of system (2). Define a new process , by , ; then is a Markov process with initial state . Choose a Lyapunov function candidate as follows: where and is the number of divisions of the interval ,
By Itô’s Lemma, we have where
From (19), for any appropriately dimensioned matrix , , we have where
From Lemma 4, we obtain Thus, it follows from (20)–(23) that Noting for and , then we have
Note
From (9)-(10) and (24)–(26), we have where with
From (8) and using Schur complement lemma, it is easy to see that there exists a scalar such that for each ,
Since is nonsingular for each , we set .
It is easy to see that where and . Define
From , we can deduce that and for each .
Then, for each , system (2) is equivalent to
To prove the mean-square exponential stability, we define a new function as where . By Dynkin’s formula [26], we get that for each ,
By using the similar method of [27], it can be seen from (17), (34), and (35) that, if is chosen small enough, a constant can be found such that
Hence, for any where . Define
Then, from (37), there exists a constant such that when
Define a function as follows:
By premultiplying the second equation of (33) with , we get
Adding (41) to (40) yields that where is any positive scalar. Premultiplying and postmultiplying by and , respectively, we get a constant such that Since can be chosen arbitrarily, is chosen small enough such that . Then, we can always find a scalar such that
From (40), (42), and (43), we get
It is easy to see that the above inequality and (44) imply
Then, from above inequality, we have
Then, from (39) and (47), we deduce that where , ,  and .
Therefore, by Lemma 3, the above inequality yields that which means that the system (2) is mean-square exponentially 10 stable. This completes the proof.

Remark 6. In Theorem 5, a delay-dependent criterion for the mean-square exponential admissibility of system (2) is derived in terms of strict LMI, which can be easily solved by standard software. In order to reduce conservatism, a new Lyapunov-Krasovskii functional is constructed base on the discretized Lyapunov functional method. The functional in (17) allows to take different weighing matrices on different subintervals, which will yield less conservative delay-dependent stability criterion. The conservatism will be reduced with increasing and will be illustrated via examples in the next section. The method can also be applied to this class of systems with interval time-varying delays by decomposing the lower bound of the time delay.

Remark 7. Specially, if there are no stochastic terms, the system (2) becomes a singular Markovian jump system with mode-dependent time-varying delay:
Based on the proof of Theorem 5, we have the following corollary.

Corollary 8. For any delays satisfying (3), the singular Markovian jump system (50) is mean-square exponentially admissible for , if there exist matrices , , , , , , ,  and and matrix with appropriate dimensions such that for each ,

Remark 9. Corollary 8 provides a new exponential stability criterion for continuous-time singular Markovian jump systems with mode-dependent time delays, which has only been studied by Balasubramiam et al. [28]. It should be pointed out that, even in the case , our criterion still has less conservatism than the results in [28], which will be illustrated via a numerical example. The reduced conservatism of Corollary 8 comes from the matrices and , which are selected to be mode dependent in our paper.

4. Numerical Examples

Example 1. Consider the system (50) with two modes and the parameters as follows:
For given , , and , the comparison results of the maximum upper bounds of the time delay are given in Table 1. From Table 1, we can see that our results still have less conservatism than the results obtained in [28] even with the case .

tab1
Table 1: Maximum allowed delay bound via different method.

Example 2. Consider the following singular stochastic hybrid system with mode-dependent time-varying delay:
By Theorem 5, for given and , the maximum allowable upper bound of to guarantee the system is mean-square exponentially stable for different is listed in Table 2.
From Table 2, we can see that the conservatism will be reduced with increasing.

tab2
Table 2: Maximum allowed via different .

5. Conclusions

In this paper, the problem of delay-dependent stability problem for a class of singular hybrid systems with mode-dependent time delay has been investigated. Based on the discretized Lyapunov functional method, a criterion which guarantees the systems is regular, impulse-free, and mean-square exponentially stable has been derived in terms of strict LMI. Two numerical examples have been given to show the effectiveness of proposed method.

Conflict of Interests

The authors declare that there is no conflict of interests regarding the publication of this paper.

Acknowledgment

This study was supported by the National Natural Science Foundation of China (Grant nos. 51205253 and 11272205).

References

  1. N. N. Krasovskii and È. A. Lidskiĭ, “Analytical design of controllers in systems with random attributes. I. Statement of the problem, method of solving,” Automation and Remote Control, vol. 22, pp. 1021–1025, 1961. View at Google Scholar · View at MathSciNet
  2. P. Shi, Y. Xia, G. P. Liu, and D. Rees, “On designing of sliding-mode control for stochastic jump systems,” IEEE Transactions on Automatic Control, vol. 51, no. 1, pp. 97–103, 2006. View at Publisher · View at Google Scholar · View at MathSciNet
  3. Z. Shu, J. Lam, and S. Xu, “Robust stabilization of Markovian delay systems with delay-dependent exponential estimates,” Automatica, vol. 42, no. 11, pp. 2001–2008, 2006. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at MathSciNet
  4. H. J. Gao, Z. Y. Fei, J. Lam, and B. Z. Du, “Further results on exponential estimates of Markovian jump systems with mode-dependent time-varying delays,” IEEE Transactions on Automatic Control, vol. 56, no. 1, pp. 223–229, 2011. View at Publisher · View at Google Scholar · View at MathSciNet
  5. Z. G. Wu, P. Shi, H. Y. Su, and J. Chu, “Stochastic synchronization of Markovian jump neural netwroks with time-varying delay using sampled-data,” IEEE Transactions on Cybernetics, vol. 43, no. 6, pp. 1796–1896, 2013. View at Publisher · View at Google Scholar
  6. Z. G. Wu, P. Shi, H. Y. Su, and J. Chu, “Passivity analysis for discrete-time stochastic markovian jump neural networks with mixed time delays,” IEEE Transactions on Neural Networks, vol. 22, no. 10, pp. 1566–1575, 2011. View at Publisher · View at Google Scholar · View at Scopus
  7. Y. Xia, E. K. Boukas, P. Shi, and J. Zhang, “Stability and stabilization of continuous-time singular hybrid systems,” Automatica, vol. 45, no. 6, pp. 1504–1509, 2009. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at MathSciNet
  8. Z. G. Wu, H. Y. Su, and J. Chu, “Delay-dependent H control for singular Markovian jump systems with time delay,” Optimal Control Applications & Methods, vol. 30, no. 5, pp. 443–461, 2009. View at Publisher · View at Google Scholar · View at MathSciNet
  9. L. G. Wu, P. Shi, and H. J. Gao, “State estimation and sliding-mode control of Markovian jump singular systems,” IEEE Transactions on Automatic Control, vol. 55, no. 5, pp. 1213–1219, 2010. View at Publisher · View at Google Scholar · View at MathSciNet
  10. J. Zhang, Y. Xia, and E. K. Boukas, “New approach to H control for Markovian jump singular systems,” IET Control Theory & Applications, vol. 4, no. 11, pp. 2273–2284, 2010. View at Publisher · View at Google Scholar · View at MathSciNet
  11. X. Mao and C. Yuan, Stochastic Differential Equations with Markovian Switching, Imperial College Press, London, UK, 2006. View at MathSciNet
  12. X. Mao, “Exponential stability of stochastic delay interval systems with Markovian switching,” IEEE Transactions on Automatic Control, vol. 47, no. 10, pp. 1604–1612, 2002. View at Publisher · View at Google Scholar · View at MathSciNet
  13. D. Yue and Q. L. Han, “Delay-dependent exponential stability of stochastic systems with time-varying delay, nonlinearity, and Markovian switching,” IEEE Transactions on Automatic Control, vol. 50, no. 2, pp. 217–222, 2005. View at Publisher · View at Google Scholar · View at MathSciNet
  14. X. Mao and L. Shaikhet, “Delay-dependent stability criteria for stochastic differential delay equations with Markovian switching,” Stability and Control, vol. 3, no. 2, pp. 88–102, 2000. View at Google Scholar · View at MathSciNet
  15. D. Yue, J. Fang, and S. Won, “Delay-dependent robust stability of stochastic uncertain systems with time delay and Markovian jump parameters,” Circuits, Systems, and Signal Processing, vol. 22, no. 4, pp. 351–365, 2003. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at MathSciNet
  16. Z. D. Wang, Y. R. Liu, and X. H. Liu, “Exponential stabilization of a class of stochastic system with Markovian jump parameters and mode-dependent mixed time-delays,” IEEE Transactions on Automatic Control, vol. 55, no. 7, pp. 1656–1662, 2010. View at Publisher · View at Google Scholar · View at MathSciNet
  17. E. K. Boukas, “Stabilization of stochastic singular nonlinear hybrid systems,” Nonlinear Analysis. Theory, Methods & Applications A, vol. 64, no. 2, pp. 217–228, 2006. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at MathSciNet
  18. L. G. Wu and D. W. C. Ho, “Sliding mode control of singular stochastic hybrid systems,” Automatica, vol. 46, no. 4, pp. 779–783, 2010. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at MathSciNet
  19. L. R. Huang and X. R. Mao, “Stability of singular stochastic systems with Markovian switching,” IEEE Transactions on Automatic Control, vol. 56, no. 2, pp. 424–429, 2011. View at Publisher · View at Google Scholar · View at MathSciNet
  20. J. K. Hale, Theory of Functional Differential Equations, Springer, New York, NY, USA, 1977. View at MathSciNet
  21. K. Gu, “further refinement of discretized Lyapunov functional method for the stability of time-delay systems,” International Journal of Control, vol. 74, no. 7, pp. 737–744, 2001. View at Publisher · View at Google Scholar
  22. D. Yue and Q. L. Han, “Robust H filter design of uncertain descriptor systems with discrete and distributed delays,” IEEE Transactions on Signal Processing, vol. 52, no. 11, pp. 3200–3212, 2004. View at Publisher · View at Google Scholar · View at MathSciNet
  23. Z. Shu and J. Lam, “Exponential estimates and stabilization of uncertain singular systems with discrete and distributed delays,” International Journal of Control, vol. 81, no. 6, pp. 865–882, 2008. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at MathSciNet
  24. Y. Wang, L. Xie, and C. E. de Souza, “Robust control of a class of uncertain nonlinear systems,” Systems & Control Letters, vol. 19, no. 2, pp. 139–149, 1992. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at MathSciNet
  25. S. Xu and J. Lam, Robust Control and Filtering of Singular Systems, Springer, Berlin, Germany, 2006. View at MathSciNet
  26. E. K. Boukas, Stochastic Hybrid Systems: Analysis and Design, Birkhäuser Boston, Boston, Mass, USA, 2005. View at MathSciNet
  27. X. Mao, N. Koroleva, and A. Rodkina, “Robust stability of uncertain stochastic differential delay equations,” Systems & Control Letters, vol. 35, no. 5, pp. 325–336, 1998. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at MathSciNet
  28. P. Balasubramaniam, R. Krishnasamy, and R. Rakkiyappan, “Delay-dependent stability criterion for a class of non-linear singular Markovian jump systems with mode-dependent interval time-varying delays,” Communications in Nonlinear Science and Numerical Simulation, vol. 17, no. 9, pp. 3612–3627, 2012. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at MathSciNet