KKA 2017: Trends in Advanced Intelligent Control, Optimization and Automation pp 214-223 | Cite as
The clipped LQ control oriented on driving safety of a half-car model with magnetorheological dampers
Abstract
The problem of improving driving safety for vehicles equipped with magnetorheological (MR) dampers is considered. It is proposed to control the MR dampers using the clipped LQ (Linear Quadratic) control which can be regarded as the two-dimensional Skyhook algorithm. The strategy is applied to a half-car model with four degrees of freedom, oriented on roll dynamics. Here, control algorithm optimised with respect to minimisation of roll vibrations is considered. Simulation experiments were performed assuming the model is subjected to impulse excitation generated as a torque applied in the centre of gravity, that is equivalent to a manoeuvre in the form of a sudden turning. The quality of the algorithm was validated using the RMS-based performance index and the results confirm the effectiveness of the proposed solution for the semi-active suspension.
Keywords
Magnetorheological damper driving safety Skyhook control clipped LQ control half-car modelPreview
Unable to display preview. Download preview PDF.
Notes
Acknowledgement
The partial financial support of this research by Polish Ministry of Science and Higher Education is gratefully acknowledged.
References
- 1. Anwar, S.: A predictive control algorithm for a yaw stability management system. SAE paper doi: 10.4271/2003-01-1284, 639–657 (2003)
- 2. Bryson, A.E.J., Ho, Y.C.: Applied optimal control: optimization, estimation and control. Hemisphere Publishing Corporation, USA (1975)Google Scholar
- 3. Caponetto, R., Dimanante, O., Fargione, G., Risitano, A., Tringali, D.: A soft computing approach to fuzzy skyhook control of semiactive suspension. IEEE Transactions on Control Systems Technology 2(6), 786–798 (November 2003)Google Scholar
- 4. Choi, S.B., Han, S.S.: H∞ control of electrorheological suspension system subjected to parameter uncertainties. Mechatronics 13, 639–657 (2003)Google Scholar
- 5. Dyke, S.J., Spencer, B.F., Sain, M.K., Carlson, J.D.: Modeling and control of magnetorheological dampers for seismic response reduction. Smart Materials and Structures 5, 565–575 (1996)Google Scholar
- 6. Guglielmino, E., Sireteanu, T., Stammers, C.W., Ghita, G., Giuclea, M.: Semi-active suspension control, improved vehicle ride and road friendliness. Springer-Verlag London Limited (2008)Google Scholar
- 7. Hong, K.S., Sohn, H.C., Hedrick, K.: Modified Skyhook control of semi-active suspensions: a new model, gain scheduling, and hardware-in-the-loop tuning. Journal of Dynamic systems, Measurement, and Control 124, 158–167 (2002)Google Scholar
- 8. Hrovat, D.: Survey of advanced suspension developments and related optimal control applications. Automatica 33, 1781–1817 (1997)Google Scholar
- 9. Kasprzyk, J., Wyrwał, J., Krauze, P.: Automotive MR damper modeling for semiactive vibration control. Proceedings of the IEEE/ASME International Conference on Advanced Intelligent Mechatronics, AIM2014 pp. 500–505 (8-11 July Besancon, France, 2014)Google Scholar
- 10. Koo, J.H., Goncalves, F.D., Ahmadian, M.: A comprehensive analysis of the response time of MR dampers. Journal of Smart Materials and Sructures 15, 351–358 (2006)Google Scholar
- 11. Krauze, P.: Comparison of control strategies in a semi-active suspension system of the experimental ATV. Journal of Low Frequency Noise, Vibration and Active Control 32(1-2), 67–80 (2013)Google Scholar
- 12. Krid, M., Benamar, F.: Design and control of an active anti-roll system for a fast rover. Proceedings of the 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems (25-30 September San Francisco, CA, USA, 2011)Google Scholar
- 13. Long, C., Li-min, N., Jing-bo, Z., Hao-bin, J.: Application of AMESim and MATLAB simulation on vehicle chassis system dynamics. Proceedings of the Workshop on Intelligent Information Technology Application (2007)Google Scholar
- 14. Savaresi, S.M., Poussot-Vassal, C., Spelta, C., Sename, O., Dugard, L.: Semi-active suspension control design for vehicles. Butterworth-Heinemann, Elsevier (2010)Google Scholar
- 15. Song, X., Ahmadian, M., Southward, S.C.: Modeling magnetorheological dampers with application of nonparametric approach. Journal of Intelligent Material Systems and Structures 16, 421–432 (May 2005)Google Scholar
- 16. Spencer, B.F., Dyke, S.J., Sain, M.K., Carlson, J.D.: Phenomenological model of a magnetorheological damper. ASCE Journal of Engineering Mechanics 123, 230–238 (1997)Google Scholar
- 17. Stone, M., Demetriou, A.: Modelling and simulation of vehicle ride and handling performance. Proceedings of the 15th IEEE International Symposium on Intelligent Control pp. 85–90 (17-19 June 2000)Google Scholar
- 18. Yang, G., Spencer, B.F., Carlson, J.D., Sain, M.K.: Large-scale MR fluid dampers:modelling and dynamic performance considerations. Engineering Structures 24, 309–323 (2002)Google Scholar
- 19. Zehsaz, M., Tahami, F., Paykani, A.: Investigation on the effect of stiffness and damping coefficients of the suspension system of a vehicle on the ride and handling performance. U.P.B Scientific Bulletin, Series D:Mechanical Engineering 76, 55–70 (2014)Google Scholar