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Event-triggered MPC for Adaptive Cruise Control System with Input Constraints

입력제한 조건을 가지는 순항 제어 시스템을 위한 이벤트-트리거 MPC

  • Lee, Sangmoon (Dept. of Electronic Engineering, Kyungpook National University)
  • Received : 2016.11.23
  • Accepted : 2016.12.05
  • Published : 2017.01.01

Abstract

This paper presents an event-triggered model predictive controller for adaptive cruise control system with sampled and quantized-data. Unlike existing works, a longitudinal continuous-time model is used for the predictive control of the system. To efficiently utilize network resources, event-trigger scheme is employed, which allows limited sensor and actuator signal satisfying the condition that the measurement of errors is over the ratio of a trigger level. The proposed control gain is obtained by solving a convex problem satisfying several linear matrix inequalities at every sampling times. Simulation results are given to show the effectiveness of the proposed design method.

Keywords

References

  1. R. Rajamani, C. Zhu, "Semi-autonomous adaptive cruise control systems", IEEE Transactions on Vehicular Technology, 51(5):1186-1192, 2002. https://doi.org/10.1109/TVT.2002.800617
  2. G. Naus, R. van den Bleek, J. Ploeg, B. Scheepers, R. van de Molengraft, M. Steinbuch, "Explicit MPC Design and Performance Evaluation of an ACC Stop&Go", American Control Conference, p.224-229, 2008.
  3. M.V., Kothare, M.V. Balakrishnan, M. Morari, "Robust constrained model predictive control using linear matrix inequalities", Automatica 32 p.13611379, 1996. https://doi.org/10.1016/0005-1098(96)00063-5
  4. A. Seuret and F. Gouaisbaut, "Wirtinger-based integral inequality: application to time-delay systems," Automatica, vol. 49, no. 8, pp. 2860-2866, Sep. 2013. https://doi.org/10.1016/j.automatica.2013.05.030
  5. M. V. Kothare, V. Balakrishnan, M. Morari, Robust constrained model predictive control using linear matrix inequalities, Automatica, 32(10), 1361-1379, 1996. https://doi.org/10.1016/0005-1098(96)00063-5
  6. J.-H. Park, T. -H. Kim, T. Sugie, Output feedback model predictive control for LPV systems based on quasi-min-max algorithm, Automatica, 47, 2052-2058, 2011. https://doi.org/10.1016/j.automatica.2011.06.015
  7. H. Huang, D. Li, Y. Xi, Mixed H2/$H{\infty}$ robust model predictive control with saturated inputs, Int. J. Syst. Sci., 12, 1-11, 2013.
  8. Y. Lu, Y. Arkun, Quasi-min-max MPC algorithms for LPV systems, Automatica, 36, 527-540, 2000. https://doi.org/10.1016/S0005-1098(99)00176-4
  9. S. M. Lee, Ju H. Park, D. H. Ji, S. C. Won, Robust model predictive control for LPV systems using relaxation matrices, IET. Control Theory Appl., 1(6), 1567-1573, 2007. https://doi.org/10.1049/iet-cta:20060525
  10. M. Farina, R. Scattolini, Tube-based robust sampled-data MPC for linear continuous time systems, Automatica, 48, 1473-1476, 2012. https://doi.org/10.1016/j.automatica.2012.03.026
  11. T. Raff, D. Sinz, F. Allgower, Model predictive control of uncertain continuous-time systems with piecewise constant control input: a convex approach. Proc. American Control Conf., Washington, 1109-1114, 2008.
  12. T. Shi, H. Su, Sampled-data MPC for LPV systems with input saturation, IET. Control Theory Appl., 8(17), 1781-1788, 2014. https://doi.org/10.1049/iet-cta.2014.0205
  13. E. Fridman, M. Dambrine, Control under quantization, saturation and delay: an LMI approach. International Journal of Robust and Nonlinear Control 45, 2258-2264, 2009.
  14. X. Tang, B. Ding, Model predictive control of linear systems over networks with data quantization and packet losses, Automatica, 49, 1333-1339, 2013. https://doi.org/10.1016/j.automatica.2013.02.033
  15. A. Seuret, F. Gouaisbaut, Wirtinger-based integral inequality: application to timedelay systems, Automatica, 49(8), 2860-2866, 2013. https://doi.org/10.1016/j.automatica.2013.05.030
  16. S. Boyd, L. EL Ghaoui, E. Feron, V. Balakrishnan, Linear Matrix Inequalities in System and Control Theory: SIAM, Philadelphia, PA, 1994.