Passenger Seat Vibration Control in Active Quarter Car Model Using Bat Algorithm Based PID Controller

Authors:

Devdutt (Manav Rachna International University, Faridabad)

Keywords: Active quarter car model, PID controller, Bat algorithm, Passenger ride comfort.

Abstract:

Present paper is related to improving the passenger ride comfort and safety in an active quarter car model. For this purpose, a quarter car model with passenger seat is considered to capture the dynamic behaviour of a real car system. To achieve the desired target, PID controller is applied in main suspenson of active quarter car model. The parameters of PID controller in first case are manually selected while in second case, optimized parameters of PID controller are used based on bat algorithm technique. The simulation results of active quarter car model are compared with passive one taking random road excitation. The parameters for comparison purpose are passenger seat acceleration and displacement response. Simulation results show the succesful application and desired performance provided by PID controller tuned by bat algorithm compared to manually tuned PID controller and passive one.

References:

[1] Devdutt and M. L. Aggarwal, Fuzzy control of passenger ride performance using MR shock absorber suspension in quarter car model, International Journal of Dynamics and Control, Vol. 3,Nno. 4, pp. 463-469, 2015.

[2] Devdutt and M. L. Aggarwal, Passenger seat vibration control of a semi-active quarter car system with hybrid Fuzzy – PID approach, International Journal of Dynamics and Control, Vol. 5, No. 2, pp. 287-296, 2017.

[3] J. Cao, P. Li, and H. Liu, An interval fuzzy controller for vehicle active suspension systems, IEEE Trans. on Intelligent Transportation Systems, Vol. 11, pp. 885-895, 2010.

[4] H. P. Du, N. Zhang, control of active vehicle suspensions with actuator time delay. Journal of Sound and Vibration, Vol. 301, pp. 236–252, 2007.

[5] I. Fialho, G. J. Balas, Road adaptive active suspension design using linear parameter-varying gain-scheduling. IEEE Transactions on Control System Technology, Vol. 10, No. 1, pp. 43–54, 2003.

[6] S. J. Huang, W. C. Lin, A neural network sliding controller for active vehicle suspension, Materials Science Forum, Vol. 440-441, pp. 119-126, 2003.

[7] Devdutt, Self-Tuning Fuzzy Control of Seat Vibrations of Active Quarter Car Model, World Academy of Science, Engineering and Technology, Vol. 11, No. 5, pp. 1053-1059, 2017.

[8] M. S. Kumar, S. Vijayarangan, Design of LQR controller for active suspension system, Indian Journal of Engineering & Materials Sciences, Vol. 13, pp. 173-179, 2006.

[9] W. Sun, H. Gao, O. Kaynak, Finite frequency H∞ control for vehicle active suspension systems. IEEE Trans. Control Syst. Technol., Vol. 19, pp. 416–22, 2011.

[10] M. Heidari, H. Homaei, Design a PID Controller for Suspension System by Back Propagation Neural Network. Hindawi Publishing Corporation Journal of Engineering Volume 2013, Article ID 421543, 9 pages.

[11] R. Kalaivani, K. Sudhagar, P. Lakshmi, Neural Network based Vibration Control for Vehicle Active Suspension System. Indian Journal of Science and Technology, Vol. 9, No. 1, DOI:10.17485/ijst/2016/v9i1/83806, 2016.

[12] Devdutt and M. L. Aggarwa, Active Vibration Control of Passenger Seat with HFPIDCR Controlled Suspension Alternatives, World Academy of Science, Engineering and Technology, Vol. 10, No. 5, pp. 916-23, 2016.

[13] X. Yang, A New Metaheuristic Bat-Inspired Algorithm, Proceedings of Nature Inspired Cooperative Strategies for Optimization (NICSO 2010), pp. 65–74, 2010.

[14] D. K. Sambariya, H. Manohar, Model order reduction by integral squared error minimization using bat algorithm, in: Proceedings of 2015 RAECS UIET Panjab University Chandigarh, 21–22nd December 2015, pp. 1–7, 2015.

[15] ISO: 2631-1, Mechanical vibration and shock – evaluation of human exposure to whole – body vibration; 1997.