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Automobile Cruise Control System Using PID Controller and Kalman Filter

PID 제어와 Kalman 필터를 이용한 자동차 정속주행 시스템

  • 김수열 (한국공학대학교 IT반도체융합공학과) ;
  • 김평수 (한국공학대학교 전자공학부)
  • Received : 2022.03.03
  • Accepted : 2022.03.11
  • Published : 2022.08.31

Abstract

In this paper, the PID controller and Kalman filter are applied to improve the automobile cruise control in the environment with disturbance and noise, and the performance is verified through diverse simulation. First, a mathematical model for a automobile cruise control system is introduced. Second, the performance degradation due to disturbance in the basic open-loop control based cruise control system is shown and then PID controller-based feedback control system to resolve this problem is verified. Third, to improve the performance degradation due to sensor noise that may occur during the feedback process, a Kalman filter is applied and verified. Ultimately, it is verified that the designed cruise control system with PID controller and Kalman filter not only satisfies all performance conditions but also has the ability for disturbance rejection and noise reduction.

본 논문에서는 외란과 잡음이 있는 환경에서 자동차 정속주행의 개선을 위해 PID 제어기와 Kalman 필터를 적용하고 다양한 시뮬레이션을 통해 성능을 검증한다. 첫 번째로, 자동차 정속주행 시스템을 위한 수학적 모델을 소개한다. 두 번째로, 기본적인 개루프 제어 기반 정속주행 시스템에 외란으로 인한 성능 저하를 확인하고 이를 개선하기 위한 PID 제어기 기반의 피드백 제어 시스템의 성능을 검증한다. 세 번째로, 피드백 과정에서 발생할 수 있는 센서 잡음으로 인한 성능 저하를 확인하고 이를 개선하기 위해 Kalman 필터를 적용하여 성능을 검증한다. 궁극적으로, PID 제어기와 Kalman 필터를 적용하여 설계된 정속주행 시스템이 성능 기준을 모두 만족할 뿐만 아니라 외란과 잡음 제거 능력까지 있음을 확인할 수 있다.

Keywords

References

  1. B. Messner, D. Tilbury, R. Hill, and J. D. Taylor, "DC motor speed: system modeling: Control tutorials for MATLAB and Simulink (CTMS)," University of Michigan, 2017.
  2. C. Wu, Z. Xu, Y. Liu, C. Fu, K. Li, and M. Hu, "Spacing policies for adaptive cruise control: A survey," IEEE Access, Vol.8, pp.50149-50162, 2020. https://doi.org/10.1109/access.2020.2978244
  3. L. Yu and R. Wang, "Researches on adaptive cruise control system: A state of the art review," Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering, Vol.236, No.2-3, pp.211-240, 2022. https://doi.org/10.1177/09544070211019254
  4. Y. Du, W. Cao, J. She, M. Wu, M. Fang, and S. Kawata, "Disturbance rejection and control system design using improved equivalent input disturbance approach," IEEE Transactions on Industrial Electronics, Vol.67, No.4, pp.3013-3023, 2020. https://doi.org/10.1109/tie.2019.2913829
  5. Y. Du, W. Cao, J. She, M. Wu, M. Fang, and S. Kawata, "Disturbance rejection and robustness of improved equivalent-input-disturbance-based System," IEEE Transactions on Cybernetics, Vol.52, No.8, pp.8537-8546, 2022. https://doi.org/10.1109/TCYB.2021.3053597
  6. L. Wang, PID Control System Design and Automatic Tuning using MATLAB/Simulink. Wiley-IEEE Press, 2020.
  7. R. P. Borase, D. K. Maghade, S. Y. Sondkar, and S. N. Pawar, "A review of PID control, tuning methods and applications," International Journal of Dynamics and Control, Vol.9, pp.818-827, 2021. https://doi.org/10.1007/s40435-020-00665-4
  8. C. Z. Sun, B. Zhang, and C. S. Zhang, "Study of PID control system based on Kalman filter," 2021 International Conference on Control Science and Electric Power Systems (CSEPS), pp.5-8, 2021.
  9. M. Grewal, "Applications of Kalman filtering in aerospace 1960 to the present," IEEE Control Systems Magazine, Vol.30, No.3, pp.69-78, 2010. https://doi.org/10.1109/MCS.2010.936465
  10. M. Rhudy, R. Salguero, and K. Holappa, "A Kalman filtering tutorial for undergraduate students," International Journal of Computer Science & Engineering Survey, Vol.8, No.1, pp.1-18, 2017.