/ / Article

Research Article | Open Access

Volume 2019 |Article ID 6048909 | https://doi.org/10.1155/2019/6048909

Yang Peng, Jiang Wu, Limin Zou, Yuming Feng, Zhengwen Tu, "A Generalization of the Cauchy-Schwarz Inequality and Its Application to Stability Analysis of Nonlinear Impulsive Control Systems", Complexity, vol. 2019, Article ID 6048909, 7 pages, 2019. https://doi.org/10.1155/2019/6048909

# A Generalization of the Cauchy-Schwarz Inequality and Its Application to Stability Analysis of Nonlinear Impulsive Control Systems

Revised19 Jan 2019
Accepted12 Feb 2019
Published07 Mar 2019

#### Abstract

In this paper, we first present a generalization of the Cauchy-Schwarz inequality. As an application of our result, we obtain a new sufficient condition for the stability of a class of nonlinear impulsive control systems. We end up this note with a numerical example which shows the effectiveness of our method.

#### 1. Introduction

In this paper, the Euclidean norm of is defined as . We use and to denote the largest and the smallest eigenvalues of a real square matrix with real eigenvalues, respectively. Let be a spectral decomposition with is orthogonal. Then the functional calculus for is defined as where is a continuous real-valued function defined on a real interval and is a real symmetrical matrix with eigenvalues in .

During the last three decades, many people have studied impulsive control method because it is an efficient way in dealing with the stability of complex systems . For example, impulsive control method can be used in the synchronization and stabilization of chaos systems  and neural network systems .

In this paper, we consider a class of nonlinear impulsive control systems as follows:where is the state variable and is output, and , , are constant matrices. The nonlinear part is a continuous function which satisfies and . If , then there will be a jump in the system and , with and . Without loss of generality, we assume that For simplicity, we can rewrite this last system asThe stability problems of nonlinear impulsive control system (5) have been investigated extensively in the literature in the past several decades. For example, a number of sufficient conditions for the stability of nonlinear impulsive control system (5) are derived in . Inequalities play an important role in their research, for instance, by using the Cauchy-Schwarz inequality  and comparison principle , and Yang showed a sufficient condition for the stability of nonlinear impulsive control system (5). For more results on applications of the Cauchy-Schwarz inequality to impulsive control theory, the reader is referred to  and the references therein.

In this paper, we first present a generalization of the Cauchy-Schwarz inequality by using some results of matrix analysis and techniques of inequalities. As an application of our result, we obtain a new sufficient condition for the stability of nonlinear impulsive control system (5). We end up this note with a numerical example which will show the effectiveness of our result.

#### 2. A Generalization of the Cauchy-Schwarz Inequality

In this section, we will give a generalized Cauchy-Schwarz inequality.

Lemma 1. Let be positive definite and suppose that are the largest and the smallest eigenvalues of , respectively. If satisfyfor a certain , thenwhere

Proof. First we assume that . Let and then, we have andSmall calculations show that and are the eigenvalues of . Suppose that are the largest and the smallest eigenvalues of , respectively. Then we haveandIt follows from (12) and (13) that It can easily be seen that the function is decreasing and so which is equivalent towhere Note that and It follows thatMeanwhile, by the Cauchy-Schwarz inequality, we haveOn the other hand, the arithmetic-geometric mean inequality for scalars implies thatIt follows from (21), (22), and (23) thatBy using inequalities (17) and (24), we obtainNow we consider the general situation. For arbitrary , we have By inequality (25), we havewhere Inequality (6) implies that and so Small calculations show that the function is decreasing and soIt follows from (27) and (31) that This completes the proof of our result.

Remark 2. By the Cauchy-Schwarz inequality, we know that condition (6) holds for any if we choose . And so Lemma 1 is a generalization of the Cauchy-Schwarz inequality:

Remark 3. If is orthogonal, then we can choose and Lemma 1 is the well-known Wielandt inequality:

#### 3. An Application of Lemma 1

Let us recall the definition of the angle between two vectors : In the course of experiment, we note that for some systems the state variable and nonlinear part have special relationships. For instance, Lü et al.  presented the following chaotic system: where . Note that , and so . That is, they are orthogonal. So we want to know whether the angle between and has an effect on the stability of systems. And the results showed in  do not take into account this factor. This is the motivation for the present paper.

In this section, as an application of Lemma 1, we present a new sufficient condition for the stability of nonlinear impulsive control system (5). Compared with Theorem 3 in  (see also Theorem 3.1.5 in ), if we consider the angle factor, then we will get a larger stable region for some systems.

Lemma 4 (see ). Suppose that is a real symmetrical matrix and let be the largest and smallest eigenvalues of , respectively. Thenfor any .

Theorem 5. Let be positive definite and suppose that are the largest and smallest eigenvalues of , respectively. Let be the largest eigenvalue of with . Suppose that is the largest eigenvalue of . Iffor a certain andwherethen the origin of nonlinear impulsive control system (5) is asymptotically stable.

Proof. Let For , we haveBy Lemma 4 and noting that the matrices and have the same eigenvalues, we obtainBy Lemmas 1 and 4 and , we haveIt follows from (43), (44), and (45) that For , by using Lemma 4 again and noting that the matrices and have the same eigenvalues, we obtain To avoid repetition, we omit the following proof because it is same as that of Theorem 3 in . This completes the proof of our result.

Remark 6. If we choose , then by the Cauchy-Schwarz inequality we know that inequality (38) holds for any and condition of (40) becomes which is the condition of Theorem 3 in  (see also ). So, our result is a generalization of Theorem 3 in .

Remark 7. If , condition of (40) will be replaced by

Remark 8. Let us discuss Lü’s  chaotic system again. Noting that and taking into consideration that we can choose , then inequality (38) holds and condition of (40) becomesFurthermore, if we choose , then this last condition can be simplified as which contains the condition of Theorem 3.2.1 in  (see also ).

Remark 9. Lemma 1 has some other applications in impulsive control theory; for example, by using Lemma 1 and comparison lemmas on the sufficient condition for the stability of nonlinear impulsive differential systems shown in , some results presented in  can be generalized.

#### 4. A Numerical Example

We end up this paper with a numerical example which shows the effectiveness of our method.

In 2005, Qi and Chen et al.  produced a new system which is described by where This system is chaotic whenBy definition of the Euclidean norm, we have By Figure 1, we know that , so we can choose . By the arithmetic-geometric mean inequality for scalars we know that So, we can choose . In this example, we choose the matrices as follows: Simple calculations show that and so we have We choose , and then Putting the simulation results are shown in Figure 2.

On the other hand, by Yang’s  result we know that if then the origin of Qi’s system  is asymptotically stable. Figure 3 shows the stable region for different ’s.

From Figure 3 we know that if we consider the angle factor, then we get a larger stable region for Qi’s system.

#### 5. Conclusion

In this paper, a generalization of the Cauchy-Schwarz inequality is presented. Then we use this inequality to analyze asymptotic stability for a class of nonlinear impulsive control systems. We think that Lemma 1 may have other applications in related fields of control theory.

#### Data Availability

The Matlab code data used to support the findings of this study are available from the corresponding author upon request.

#### Conflicts of Interest

The authors declare that they have no conflicts of interest.

#### Authors’ Contributions

All authors contributed equally to the writing of this paper. All authors read and approved the final version of this paper.

#### Acknowledgments

The authors wish to express their heartfelt thanks to the referees for their detailed and helpful suggestions for revising the manuscript. This work was supported by the Fundamental Research Funds for the Central Universities (No. JBK19072018278) and the Chongqing Research Program of Basic Research and Frontier Technology (No. cstc2017jcyjAX0032).

1. R. A. Horn and C. R. Johnson, Matrix Analysis, Cambridge University Press, Cambridge, UK, 1985. View at: Publisher Site | MathSciNet
2. R. Goebel, R. G. Sanfelice, and A. R. Teel, Hybrid Dynamical Systems: Modeling, Stability, and Robustness, Princeton University Press, 2012. View at: MathSciNet
3. W. M. Haddad, V. Chellaboina, and S. G. Nersesov, Impulsive and Hybrid Dynamical Systems: Stability, Dissipativity, and Control, Princeton Series in Applied Mathematics, Princeton University Press, Princeton, NJ, USA, 2006. View at: MathSciNet
4. T. Yang, Impulsive Control Theory, Springer, Berlin , Germany, 2001. View at: MathSciNet
5. Z.-H. Guan, R.-Q. Liao, F. Zhou, and H. O. Wang, “On impulsive control and its application to Chen's chaotic system,” International Journal of Bifurcation and Chaos, vol. 12, no. 5, pp. 1191–1197, 2002. View at: Publisher Site | Google Scholar | MathSciNet
6. T. Huang, C. Li, W. Yu, and G. Chen, “Synchronization of delayed chaotic systems with parameter mismatches by using intermittent linear state feedback,” Nonlinearity, vol. 22, no. 3, pp. 569–584, 2009. View at: Publisher Site | Google Scholar | MathSciNet
7. C. Li, X. Liao, X. Yang, and T. Huang, “Impulsive stabilization and synchronization of a class of chaotic delay systems,” Chaos: An Interdisciplinary Journal of Nonlinear Science, vol. 15, no. 4, Article ID 043103, 2005. View at: Publisher Site | Google Scholar | MathSciNet
8. Z. G. Li, C. Y. Wen, Y. C. Soh, and W. X. Xie, “The stabilization and synchronization of Chua's oscillators via impulsive control,” IEEE Transactions on Circuits and Systems I: Fundamental Theory and Applications, vol. 48, no. 11, pp. 1351–1355, 2001. View at: Publisher Site | Google Scholar | MathSciNet
9. J. Sun, Y. Zhang, and Q. Wu, “Impulsive control for the stabilization and synchronization of Lorenz systems,” Physics Letters A, vol. 298, no. 2-3, pp. 153–160, 2002. View at: Publisher Site | Google Scholar | MathSciNet
10. T. Yang, L. B. Yang, and C. M. Yang, “Impulsive control of Lorenz system,” Physica D: Nonlinear Phenomena, vol. 110, no. 1-2, pp. 18–24, 1997. View at: Publisher Site | Google Scholar | MathSciNet
11. X. S. Yang and D. W. C. Ho, “Synchronization of delayed memristive neural networks: robust analysis approach,” IEEE Transactions on Cybernetics, vol. 46, no. 12, pp. 3377–3387, 2016. View at: Publisher Site | Google Scholar
12. H. Bao, J. H. Park, and J. Cao, “Exponential synchronization of coupled stochastic memristor-based neural networks with time-varying probabilistic delay coupling and impulsive delay,” IEEE Transactions on Neural Networks and Learning Systems, vol. 27, no. 1, pp. 190–201, 2016. View at: Publisher Site | Google Scholar | MathSciNet
13. G. Feng and J. Cao, “Stability analysis of impulsive switched singular systems,” IET Control Theory & Applications, vol. 9, no. 6, pp. 863–870, 2015. View at: Publisher Site | Google Scholar | MathSciNet
14. Z.-H. Guan, G.-S. Han, J. Li, D.-X. He, and G. Feng, “Impulsive multiconsensus of second-order multiagent networks using sampled position data,” IEEE Transactions on Neural Networks and Learning Systems, vol. 26, no. 11, pp. 2678–2688, 2015. View at: Publisher Site | Google Scholar | MathSciNet
15. T. Huang, C. Li, S. Duan, and J. A. Starzyk, “Robust exponential stability of uncertain delayed neural networks with stochastic perturbation and impulse effects,” IEEE Transactions on Neural Networks and Learning Systems, vol. 23, no. 6, pp. 866–875, 2012. View at: Publisher Site | Google Scholar
16. C. Li, X. Yu, Z.-W. Liu, and T. Huang, “Asynchronous impulsive containment control in switched multi-agent systems,” Information Sciences, vol. 370, pp. 667–679, 2016. View at: Publisher Site | Google Scholar
17. Q. Song, H. Yan, Z. Zhao, and Y. Liu, “Global exponential stability of impulsive complex-valued neural networks with both asynchronous time-varying and continuously distributed delays,” Neural Networks, vol. 81, pp. 1–10, 2016. View at: Publisher Site | Google Scholar
18. Q. Song, H. Yan, Z. Zhao, and Y. Liu, “Global exponential stability of complex-valued neural networks with both time-varying delays and impulsive effects,” Neural Networks, vol. 79, pp. 108–116, 2016. View at: Publisher Site | Google Scholar
19. X. Yang, J. Cao, and Z. Yang, “Synchronization of coupled reaction-diffusion neural networks with time-varying delays via pinning-impulsive controller,” SIAM Journal on Control and Optimization, vol. 51, no. 5, pp. 3486–3510, 2013. View at: Publisher Site | Google Scholar | MathSciNet
20. X. Yang and J. Lu, “Finite-time synchronization of coupled networks with Markovian topology and impulsive effects,” IEEE Transactions on Automatic Control, vol. 61, no. 8, pp. 2256–2261, 2016. View at: Publisher Site | Google Scholar
21. X. Yang, J. Lam, D. W. C. Ho, and Z. Feng, “Fixed-time synchronization of complex networks with impulsive effects via nonchattering control,” IEEE Transactions on Automatic Control, vol. 62, no. 11, pp. 5511–5521, 2017. View at: Publisher Site | Google Scholar
22. X. Yang, J. Lu, D. W. Ho, and Q. Song, “Synchronization of uncertain hybrid switching and impulsive complex networks,” Applied Mathematical Modelling: Simulation and Computation for Engineering and Environmental Systems, vol. 59, pp. 379–392, 2018. View at: Publisher Site | Google Scholar | MathSciNet
23. L. Zhang, X. Yang, C. Xu, and J. Feng, “Exponential synchronization of complex-valued complex networks with time-varying delays and stochastic perturbations via time-delayed impulsive control,” Applied Mathematics and Computation, vol. 306, pp. 22–30, 2017. View at: Publisher Site | Google Scholar
24. Z. Ai and C. Chen, “Asymptotic stability analysis and design of nonlinear impulsive control systems,” Nonlinear Analysis: Hybrid Systems, vol. 24, pp. 244–252, 2017. View at: Publisher Site | Google Scholar | MathSciNet
25. Z. G. Li, C. Y. Wen, and Y. C. Soh, “Analysis and design of impulsive control systems,” IEEE Transactions on Automatic Control, vol. 46, no. 6, pp. 894–897, 2001. View at: Publisher Site | Google Scholar | MathSciNet
26. J. Sun, Y. Zhang, and Q. Wu, “Less conservative conditions for asymptotic stability of implusive control systems,” Institute of Electrical and Electronics Engineers Transactions on Automatic Control, vol. 48, no. 5, pp. 829–831, 2003. View at: Publisher Site | Google Scholar | MathSciNet
27. T. Yang, “Impulsive control,” IEEE Transactions on Automatic Control, vol. 44, no. 5, pp. 1081–1083, 1999. View at: Publisher Site | Google Scholar | MathSciNet
28. J. H. Lü, G. R. Chen, D. Z. Cheng et al., “Bridge the gap between the Lorenz system and the Chen system,” International Journal of Bifurcation and Chaos, vol. 12, no. 12, pp. 2917–2926, 2002. View at: Publisher Site | Google Scholar | MathSciNet
29. G. Qi, G. Chen, S. Du, Z. Chen, and Z. Yuan, “Analysis of a new chaotic system,” Physica A: Statistical Mechanics and its Applications, vol. 352, no. 2–4, pp. 295–308, 2005. View at: Publisher Site | Google Scholar

#### More related articles

We are committed to sharing findings related to COVID-19 as quickly as possible. We will be providing unlimited waivers of publication charges for accepted research articles as well as case reports and case series related to COVID-19. Review articles are excluded from this waiver policy. Sign up here as a reviewer to help fast-track new submissions.