International Journal of Control, Automation, and Systems

Institute of Control, Robotics and Systems (제어로봇시스템학회)
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Intelligent Scheduling Control of Networked Control Systems with Networked-induced Delay and Packet Dropout

  • Li, Hongbo (Department of Computer Science and Technology, State Key Laboratory of Intelligent Technology and Systems, Tsinghwa University) ;
  • Sun, Zengqi (Department of Computer Science and Technology, State Key Laboratory of Intelligent Technology and Systems, Tsinghwa University) ;
  • Chen, Badong (Department of Computer Science and Technology, State Key Laboratory of Intelligent Technology and Systems, Tsinghwa University) ;
  • Liu, Huaping (Department of Computer Science and Technology, State Key Laboratory of Intelligent Technology and Systems, Tsinghwa University) ;
  • Sun, Fuchun (Department of Computer Science and Technology, State Key Laboratory of Intelligent Technology and Systems, Tsinghwa University)
  • Published : 2008.12.31
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Abstract

Networked control systems(NCSs) have gained increasing attention in recent years due to their advantages and potential applications. The network Quality-of-Service(QoS) in NCSs always fluctuates due to changes of the traffic load and available network resources. To handle the network QoS variations problem, this paper presents an intelligent scheduling control method for NCSs, where the sampling period and the control parameters are simultaneously scheduled to compensate the effect of QoS variation on NCSs performance. For NCSs with network-induced delays and packet dropouts, a discrete-time switch model is proposed. By defining a sampling-period-dependent Lyapunov function and a common quadratic Lyapunov function, the stability conditions are derived for NCSs in terms of linear matrix inequalities(LMIs). Based on the obtained stability conditions, the corresponding controller design problem is solved and the performance optimization problem is also investigated. Simulation results are given to demonstrate the effectiveness of the proposed approaches.

Keywords

References

  1. S. Chai, G. P. Liu, D. Rees, and Y. Xia, "Design and practical implementation of internet-based predictive control of a servo system," IEEE Trans. on Control Systems Technology, vol. 16, no. 1, pp. 158-168, 2008 https://doi.org/10.1109/TCST.2007.903095
  2. H. Li, Z. Sun, H. Liu, and M.-Y. Chow, "Predictive observer-based control for networked control systems with network-induced delay and packet dropout," Asian Journal of Control, vol. 10, no. 6, pp. 1-3, 2008 https://doi.org/10.1002/asjc.38
  3. Y. Tipsuwan and M.-Y. Chow, "Gain scheduler middleware: A methodology to enable existing controllers for networked control and teleoperation-part II: teleoperation," IEEE Trans. on Industrial Electronics, vol. 51, no. 6, pp. 1228-1237, 2004 https://doi.org/10.1109/TIE.2004.837865
  4. P. Seiler and R. Sengupta, "An $H\infty$ approach to networked control," IEEE Trans. on Automatic Control, vol. 50, no. 3, pp. 356-364, 2005 https://doi.org/10.1109/TAC.2005.844177
  5. M. Gaid, A. Cela, and Y. Hamam, "Optimal integrated control and scheduling of networked control systems with communication constraints: Application to a car suspension system," IEEE Trans. on Control Systems Technology, vol. 14, no. 4, pp. 776-787, 2006 https://doi.org/10.1109/TCST.2006.872504
  6. K. Ji and W.-J. Kim, "Stochastic optimal control and network co-design for networked control systems," International Journal of Control, Automation and Systems, vol. 5, no. 5, pp. 515-525, 2007
  7. K. Ji and W.-J. Kim, "Robust control for networked control systems with admissible parameter uncertainties," International Journal of Control, Automation and Systems, vol. 5, no. 4, pp. 372-378, 2007
  8. L. A. Montestruque and P. J. Antsaklis, "On the model-based control of networked systems," Automatica, vol. 39, no. 10, pp. 1837-1843, 2003 https://doi.org/10.1016/S0005-1098(03)00186-9
  9. P. V. Zhivoglyadov and R. H. Middleton, "Networked control design for linear systems," Automatica, vol. 39, no. 4, pp. 743-750, 2003 https://doi.org/10.1016/S0005-1098(02)00306-0
  10. M.-Y. Chow and Y. Tipsuwan, "Gain adaptation of networked DC motor controllers based on QoS variations," IEEE Trans. on Industrial Electronics, vol. 50, no. 5, pp. 936-943, 2003 https://doi.org/10.1109/TIE.2003.817576
  11. Y. Tipsuwan and M.-Y. Chow, "On the gain scheduling for networked PI controller over IP network," IEEE/ASME Trans. on Mechatronics, vol. 9, no. 3, pp. 491-498, 2004 https://doi.org/10.1109/TMECH.2004.834645
  12. K. Li and J. Baillieul, "Robust quantization for digital finite communication bandwidth (DFCB) control," IEEE Trans. on Automatic Control, vol. 49, no. 9, pp. 1573-1584, 2004 https://doi.org/10.1109/TAC.2004.834106
  13. L. A. Montestruque and P. J. Antsaklis, "Static and dynamic quantization in model-based networked control systems," International Journal of Control, vol. 80, no. 1, pp. 87-101, 2007 https://doi.org/10.1080/00207170600931663
  14. W. Zhang, M. S. Branicky, and S. M. Phillips, "Stability of networked control systems," Control Systems Magazine, vol. 21, no. 1, pp. 84-99, 2001 https://doi.org/10.1109/37.898794
  15. M. Yu, L. Wang, T. G. Chu, and G. M. Xie, "Stabilization of networked control systems with data packet dropout and network delays via switching system approach," Proc. of the 43th IEEE Conference on Decision and Control, pp. 3539-3544, 2004
  16. F. L. Lian, Analysis, Design, Modeling, and Control of Networked Control Systems, Ph.D. Dissertation, University of Michigan, 2001
  17. G. F. Franklin, M. L. Workmann, and J. D. Powell, Digital Control of Dynamic Systems, 3rd edition, Addison-Wseley, 1998
  18. C. Gonzalez, Contributions on Theoretical Aspects of Estimation of Distribution Algorithms, Ph.D. Dissertation, University of the Basque Country, Spain, 2005
  19. Y. Cai, X. Sun, and P. Jia, "Probabilistic modeling for continuous EDA with Boltzmann selection and Kullback-Leibeler divergence," Proc. of the 8th Annual Conf. on Genetic and Evolutionary Computation, pp. 389-396, 2006
  20. P. A Bosman and J. Grahl, "Matching inductive search bias and problem structure in continuous Estimation-of-Distribution algorithms," European Journal of Operational Research, vol. 185, no. 3, pp. 1246-1264, 2008 https://doi.org/10.1016/j.ejor.2006.06.051