Table of Contents Author Guidelines Submit a Manuscript
Journal of Control Science and Engineering
Volume 2011, Article ID 816432, 7 pages
http://dx.doi.org/10.1155/2011/816432
Research Article

Synchronization and Antisynchronization of a Planar Oscillation of Satellite in an Elliptic Orbit via Active Control

Department of Information Technology, Higher College of Technology, Muscat, Oman

Received 6 April 2011; Revised 4 June 2011; Accepted 22 June 2011

Academic Editor: Derong Liu

Copyright © 2011 Mohammad Shahzad. 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

We have investigated the synchronization and antisynchronization behaviour of two identical planar oscillation of a satellite in elliptic orbit evolving from different initial conditions using the active control technique based on the Lyapunov stability theory and the Routh-Hurwitz criteria. The designed controller, with our own choice of the coefficient matrix of the error dynamics that satisfy the Lyapunov stability theory and the Routh-Hurwitz criteria, is found to be effective in the stabilization of the error states at the origin, thereby, achieving synchronization and antisynchronization between the states variables of two nonlinear dynamical systems under consideration. The results are validated by numerical simulations using mathematica.

1. Introduction

In the last two decades, considerable research has been done in nonlinear dynamical systems and their various properties. One of the most important property of nonlinear dynamical systems is synchronization, which classically represents the entrainment of frequencies of oscillators due to weak interactions [13]. Studies in this field are partly motivated by experimental realization in lasers, electronic circuits, plasma discharge, and chemical reactions [24]. Synchronization techniques have been improved in recent years, and many different methods are applied theoretically as well as experimentally to synchronize the chaotic systems. Some of them are nonlinear feedback method [5], adaptive control method [6], antisynchronization method [7], sliding mode control method [8], and chaos synchronization using active control, which is introduced in [9] is one of these methods. Notable among these methods, chaos synchronization using active control scheme has recently been widely accepted as an efficient technique to synchronize the chaotic systems. The reason is because it can be used to synchronize identical as well as nonidentical systems; a feature that gives it an advantage over other synchronizing methods. This method based on the Lyapunov stability theory and the Routh-Hurwitz criteria to active control in order to achieve stable synchronization has been applied to many practical systems such as the electronic circuits, which model a third-order “jerk” equation [10], Lorenz, Chen, and Lü system [11], geophysical systems [12], nonlinear equations of acoustic gravity waves (Lorenz-Stenflo system) [13], Van-der Pol-Duffing oscillator [14], forced damped pendulum [15], nuclear magnetic resonance modeled by the Bloch equations [16], parametrically excited oscillators [17], permanent magnet reluctance machine [18], inertial ratchets [19], RCL-shunted Josephson junction [20], and modified projective synchronization [21].

In this article, we have applied the active control technique based on the Lyapunov stability theory and the Routh-Hurwitz criteria to study the synchronization and antisynchronization behavior of two identical planar oscillation of a satellite in elliptic orbit evolving from different initial conditions. The system under consideration is chaotic for some values of parameter involved in the system. In synchronization, the two systems (master and slave) are synchronized and start with different initial conditions. The same problem may be treated as the design of control laws for full chaotic slave system using the known information of the master system so as to ensure that the controlled receiver synchronizes with the master system. Hence, the slave chaotic system completely traces the dynamics of the master system in the course of time. The aim of this study is to trace the chaotic dynamics of the planar oscillation of a satellite in elliptic orbit based on synchronization and antisynchronization. To the best of my knowledge nobody studied this before.

2. Description of the Model

Elliptically orbiting planar oscillations of satellites in the solar system make an interesting study, and significant contributions to this end can be found [2230], all of which have studied the influence of certain perturbative forces, such as solar radiation pressure, tidal force, and air resistance. In the present work, we consider the planar oscillation of a satellite in elliptic orbit with the spin axis fixed perpendicular to the orbital plane. Let the long axis of the satellite makes an angle with a reference axis that is fixed in inertial space, the long axis of the satellite makes an angle with satellites planet centre line [31], and the satellite to be a triaxial ellipsoid with principal moments of inertia , where is the moment about the spin axis. The orbit is taken to be a fixed ellipse with semimajor axis , eccentricity , true anomaly , and instantaneous radius . The equation of motion of satellite planar oscillation in an elliptic orbit around the earth is Taking , , and , (1) can be written as In order to reduce three variables , and we are taking as independent variable.

Now, Now, from , we have

Using (3) and (4) in (2), we have

Using the binomial expansion for and for very small value of ignoring the higher order terms in , we have

3. Synchronization via Active Control

For a system of two coupled chaotic oscillators, the master system () and the slave system (), where and are the phase space (state variables), and and are the corresponding nonlinear functions, synchronization in a direct sense implies . When this occurs the coupled systems are said to be completely synchronized. Chaos synchronization is related to the observer problem in control theory [32]. The problem may be treated as the design of control laws for full chaotic slave system using the known information of the master system so as to ensure that the controlled receiver synchronizes with the master system. Hence, the slave chaotic system completely traces the dynamics of the master in the course of time.

In order to formulate the active controllers, we write the system (6) in two first-order differential equations as shown below.

Let and , then we have Let us define another system where (7) and (8) are called the master system and the slave system, respectively, and in slave system, and are control functions to be determined. Let and be the synchronization errors such that for . From (7) and (8), we have In order to express (9) as only linear terms in and , we redefine the control functions as follows: From (9) and (10), we have Equation (11) is the error dynamics, which can be interpreted as a control problem where the system to be controlled is a linear system with control inputs and . As long as these feedbacks stabilize the system, for . This simply implies that the two systems (7) and (8) evolving from different initial conditions are synchronized. As functions of and , we choose and as follows: where is a constant feedback matrix to be determined. Hence the error system (11) can be written as where is the coefficient matrix.

According to the Lyapunov stability theory and the Routh-Hurwitz criteria, if then the eigen values of the coefficient matrix of error system (11) must be real or complex with negative real parts and, hence, stable synchronized dynamics between systems (7) and (8) is guaranteed. Let where is a real number which is usually set equal to 1. There are several ways of choosing the constant elements , , , of matrix in order to satisfy the Lyapunov stability theory and the Routh-Hurwitz criteria (14).

4. Numerical Simulation for Synchronization

For the constant elements of feedback matrix, choosing and for the parameters involved in system under investigation, , with the initial conditions , and , we have simulated the system under consideration using mathematica. The results obtained show that the system under consideration achieved synchronization. Phase portraits, time series analysis, and error diagrams are the witness of achieving synchronization between master and slave system. Further, it also has been confirmed by the convergence of the synchronization quality defined by Figures 16 confirms the convergence of the synchronization quality defined by (16).

816432.fig.001
Figure 1: Phase plot of master system.
816432.fig.002
Figure 2: Phase plot of slave system.
816432.fig.003
Figure 3: Time series analysis of master system.
816432.fig.004
Figure 4: Time series analysis of slave system.
816432.fig.005
Figure 5: Time series analysis of .
816432.fig.006
Figure 6: Time series analysis of .

5. Antisynchronization via Active Control

Antisynchronization of two coupled systems (master system) and (slave system) means . This phenomenon has been investigated both experimentally and theoretically in many physical systems [18, 19, 3237]. A recent study of the antisynchronization phenomenon in nonequilibrium systems suggests that it could be used as a technique for particle separation in a mixture of interacting particles [19].

In order to formulate the active controllers for Antisynchronization, we need to redefine the error functions as and , where and are called the antisynchronization errors such that . From (7) and (8), error dynamics can be written as In order to express (17) as only linear terms in and , we redefine the control functions as follows: From (17) and (18), we have Equation (19) is the error dynamics, which can be interpreted as a control problem where the system to be controlled is a linear system with control inputs , and . As long as these feedbacks stabilize the system, for . This simply implies that the two systems (7) and (8) evolving from different initial conditions are synchronized. As functions of and , we choose and as follows: where is a constant feedback matrix to be determined. Hence the error system (19) can be written as where , is the coefficient matrix.

According to the Lyapunov stability theory and the Routh-Hurwitz criteria, if then the eigen values of the coefficient matrix of error system (19) must be real or complex with negative real parts, and, hence, stable synchronized dynamics between systems (7) and (8) is guaranteed. Let where is a real number which is usually set equal to 1. There are several ways of choosing the constant elements , , , of matrix in order to satisfy the Lyapunov stability theory and the Routh-Hurwitz criteria (19).

6. Numerical Simulation for Antisynchronization

For the constant elements of feedback matrix, choosing and for the parameters involved in system under investigation, , with the initial conditions and , we have simulated the system under consideration using mathematica. The results obtained show that the system under consideration achieved synchronization. Phase portraits, time series analysis, and error diagrams are the witness of achieving synchronization between master and slave system. Further, it also has been confirmed by the convergence of the synchronization quality defined by Figures 712 confirms the convergence of the synchronization quality defined by (24).

816432.fig.007
Figure 7: Phase plot of slave system.
816432.fig.008
Figure 8: Time series analysis of slave system.
816432.fig.009
Figure 9: Time series analysis of .
816432.fig.0010
Figure 10: Time series analysis of .
816432.fig.0011
Figure 11: Convergence of errors in synchronization.
816432.fig.0012
Figure 12: Convergence of errors in antisynchronization.

7. Conclusion

In this paper, we have investigated the synchronization and antisynchronization behaviour of the two identical planar oscillation of a satellite in elliptic orbit evolving from different initial conditions via the active control technique based on the Lyapunov stability theory and the Routh-Hurwitz criteria. The results were validated by numerical simulations using mathematica. For the errors in synchronization and antisynchronization behavior of the system under study, we have observed that the rate of convergence of errors is faster in antisynchronization. Figures 112 are proof of it.

References

  1. L. M. Pecora and T. L. Carroll, “Synchronization in chaotic systems,” Physical Review Letters, vol. 64, no. 8, pp. 821–824, 1990. View at Publisher · View at Google Scholar · View at Scopus
  2. M. Lakshmanan and K. Murali, Chaos in Nonlinear Oscillators: Controlling and Synchronizing, World Scientist, Singapore, 1996.
  3. A. Pikovsky, M. Rosenblum, and J. Kurths, Synchronization. A Unified Approach to Nonlinear Science, Cambridge University Press, Cambridge, UK, 2001.
  4. C. M. Ticos, E. Rosa Jr., W. B. Pardo, J. A. Walkenstein, and M. Monti, “Experimental real-time phase synchronization of a paced chaotic plasma discharge,” Physical Review Letters, vol. 85, no. 14, pp. 2929–2932, 2000. View at Publisher · View at Google Scholar · View at Scopus
  5. L. Lu, C. Zhang, and Z. A. Guo, “Synchronization between two different chaotic systems with nonlinear feedback control,” Chinese Physics, vol. 16, no. 6, pp. 1603–1607, 2007. View at Publisher · View at Google Scholar · View at Scopus
  6. Y. Wang, Z. H. Guan, and H. O. Wang, “Feedback and adaptive control for the synchronization of Chen system via a single variable,” Physics Letters, Section A, vol. 312, no. 1-2, pp. 34–40, 2003. View at Publisher · View at Google Scholar · View at Scopus
  7. J. H. Park, “Chaos synchronization between two different chaotic dynamical systems,” Chaos, Solitons and Fractals, vol. 27, no. 2, pp. 549–554, 2006. View at Publisher · View at Google Scholar · View at Scopus
  8. M. Haeri and A. Emadzadeh, “Synchronizing different chaotic systems using active sliding mode control,” Chaos, Solitons and Fractals, vol. 31, no. 1, pp. 119–129, 2007. View at Publisher · View at Google Scholar · View at Scopus
  9. E. W. Bai and K. E. Lonngren, “Synchronization of two Lorenz systems using active control,” Chaos, Solitons & Fractals, vol. 9, pp. 1555–1561, 1998. View at Google Scholar
  10. E. W. Bai, K. E. Lonngren, and J. C. Sprott, “On the synchronization of a class of electronic circuits that exhibit chaos,” Chaos, Solitons & Fractals, vol. 13, no. 7, pp. 1515–1521, 2002. View at Publisher · View at Google Scholar · View at Scopus
  11. H. K. Chen, “Synchronization of two different chaotic systems: a new system and each of the dynamical systems Lorenz, Chen and Lü,” Chaos, Solitons & Fractals, vol. 25, no. 5, pp. 1049–1056, 2005. View at Publisher · View at Google Scholar · View at Scopus
  12. U. E. Vincent, “Synchronization of Rikitake chaotic attractor using active control,” Physics Letters, Section A, vol. 343, no. 1–3, pp. 133–138, 2005. View at Publisher · View at Google Scholar · View at Scopus
  13. U. E. Vincent, “Synchronization of identical and non-identical 4-D chaotic systems using active control,” Chaos, Solitons & Fractals, vol. 37, no. 4, pp. 1065–1075, 2008. View at Publisher · View at Google Scholar · View at Scopus
  14. A. N. Njah and U. E. Vincent, “Synchronization and anti-synchronization of chaos in an extended Bonhöffer-van der Pol oscillator using active control,” Journal of Sound and Vibration, vol. 319, no. 1-2, pp. 41–49, 2009. View at Publisher · View at Google Scholar · View at Scopus
  15. A. N. Njah, “Synchronization of forced damped pendulum via active control,” Journal of the Nigerian Association of Mathematical Physics, vol. 10, pp. 143–148, 2006. View at Google Scholar
  16. A. Ucar, E. W. Bai, and K. E. Lonngren, “Synchronization of chaotic behavior in nonlinear Bloch equations,” Physics Letters, Section A, vol. 314, no. 1-2, pp. 96–101, 2003. View at Publisher · View at Google Scholar · View at Scopus
  17. Y. Lei, W. Xu, J. Shen, and T. Fang, “Global synchronization of two parametrically excited systems using active control,” Chaos, Solitons & Fractals, vol. 28, no. 2, pp. 428–436, 2006. View at Publisher · View at Google Scholar · View at Scopus
  18. U. E. Vincent and A. Ucar, “Synchronization and anti-synchronization of chaos in permanent magnet reluctance machine,” Far East Journal of Dynamical Systems, vol. 9, pp. 211–221, 2007. View at Google Scholar
  19. U. E. Vincent and J. A. Laoye, “Synchronization, anti-synchronization and current transports in non-identical chaotic ratchets,” Physica A, vol. 384, no. 2, pp. 230–240, 2007. View at Publisher · View at Google Scholar · View at Scopus
  20. A. Ucar, K. E. Lonngren, and E. W. Bai, “Chaos synchronization in RCL-shunted Josephson junction via active control,” Chaos, Solitons & Fractals, vol. 31, no. 1, pp. 105–111, 2007. View at Publisher · View at Google Scholar · View at Scopus
  21. H. Zhu and X. Zhang, “Modified projective synchronization of different hyperchaotic systems,” Journal of Information and Computing Science, vol. 4, pp. 33–40, 2009. View at Google Scholar
  22. V. V. Beletskii, Motion of an Artificial Satellite about Its Center of Mass, 1966, Jerusalem: Israel Program Science Translation.
  23. V. V. Beletskii, M. L. Pivovarov, and E. L. Starostin, “Regular and chaotic motions in applied dynamics of a rigid body,” Chaos, vol. 6, no. 2, pp. 155–166, 1996. View at Google Scholar · View at Scopus
  24. R. B. Singh and V. G. Demin, “About the motion of a heavy flexible string attached to the satellite in the central field of attraction,” Celestial Mechanics & Dynamical Astronomy, vol. 6, no. 3, pp. 268–277, 1972. View at Publisher · View at Google Scholar · View at Scopus
  25. C. Soto-Trevino and T. J. Kaper, “Higher-order Melnikov theory for adiabatic systems,” Journal of Mathematical Physics, vol. 37, no. 12, pp. 6220–6249, 1996. View at Publisher · View at Google Scholar · View at Scopus
  26. L. S. Wang, P. S. Krishnaprasad, and J. H. Maddocks, “Hamiltonian dynamics of a rigid body in a central gravitational field,” Celestial Mechanics & Dynamical Astronomy, vol. 50, no. 4, pp. 349–386, 1991. View at Publisher · View at Google Scholar
  27. J. Wisdom, “Rotational dynamics of irregularly shaped natural satellites,” The Astronomical Journal, vol. 94, pp. 1350–1360, 1987. View at Google Scholar
  28. J. Wisdom, S. J. Peale, and F. Mignard, “The chaotic rotation of Hyperion,” Icarus, vol. 58, no. 2, pp. 137–152, 1984. View at Google Scholar · View at Scopus
  29. P. Goldreich and S. Peale, “Spin-orbit coupling in the solar system,” The Astronomical Journal, vol. 71, pp. 425–438, 1966. View at Google Scholar
  30. A. Khan, R. Sharma, and L. M. Saha, “Chaotic motion of an ellipsoidal satellite I,” The Astronomical Journal, vol. 116, no. 4, pp. 2058–2066, 1998. View at Google Scholar · View at Scopus
  31. C. D. Murray and S. F. Dermott, Solar System Dynamics, Cambridge, UK, Cambridge University Press, 1999.
  32. H. Nijmeijer and M. Y. Mareels, “An observer looks at synchronization,” IEEE Transactions on Circuits and Systems, vol. 44, no. 10, pp. 882–890, 1997. View at Google Scholar · View at Scopus
  33. C. M. Kim, S. Rim, W. H. Kye, J. W. Ryu, and Y. J. Park, “Anti-synchronization of chaotic oscillators,” Physics Letters, Section A, vol. 320, no. 1, pp. 39–46, 2003. View at Publisher · View at Google Scholar · View at Scopus
  34. A. A. Emadzadeh and M. Haeri, “Anti-synchronization of two different chaotic systems via active control,” in Proceedings of the 4th World Enformatika Conference, (WEC '05), pp. 62–65, June 2005. View at Scopus
  35. C. Li and X. Liao, “Anti-synchronization of a class of coupled chaotic systems via linear feedback control,” International Journal of Bifurcation & Chaos, vol. 16, no. 4, pp. 1041–1047, 2006. View at Publisher · View at Google Scholar · View at Scopus
  36. S. Nakata, T. Miyata, N. Ojima, and K. Yoshikawa, “Self-synchronization in coupled salt-water oscillators,” Physica D, vol. 115, no. 3-4, pp. 313–320, 1998. View at Google Scholar · View at Scopus
  37. G. Cai and S. Zheng, “Anti-synchronization in different hyperchaotic systems,” Journal of Information and Computing Science, vol. 3, pp. 181–188, 2008. View at Google Scholar