Robust controller design for active suspensions using particle swarm optimisation

International Journal of Modelling, Identification and Control

Volumn 5, Issue 1, 2008, Pages 66-76

  Soliman, H M ^a   Awadallah, M A ^b   Emira, M Nadim ^c  

^a CAIRO UNIVERSITY   (Egypt)

^b ZAGAZIG UNIVERSITY   (Egypt)

^c YANBU INDUSTRIAL COLLEGE   (Saudi Arabia)

Author keywords

Active suspension; Particle swarm optimisation; PSO; Robust control

Indexed keywords

ACTIVE SUSPENSION SYSTEMS; CONTROLLERS; DESIGN; NONLINEAR PROGRAMMING; PARTICLE SWARM OPTIMIZATION (PSO); ROBUST CONTROL; ROBUSTNESS (CONTROL SYSTEMS); STIFFNESS; SUSPENSIONS (FLUIDS);

ACTIVE SUSPENSION; ACTUATOR SATURATIONS; CONTROL EFFORT REDUCTION; CONTROLLER PARAMETER; NON-LINEAR OPTIMISATION; PARTICLE SWARM OPTIMISATION; PERFORMANCE OBJECTIVE; ROBUST CONTROLLER DESIGN;

SUSPENSIONS (COMPONENTS);

EID: 57849097724     PISSN: 17466172     EISSN: 17466180     Source Type: Journal    
DOI: 10.1504/IJMIC.2008.021776     Document Type: Article

References (17)

1. Chalasani, R.M. (1986) 'Ride performance potential of active suspension systems, part 2, comprehensive analysis based on a full-car model', Trans. ASME, Vol. 80, pp.205-234.
2. ∞ control of active suspensions: An LMI approach', IEEE Trans. on Control System Technology, Vol. 13, No. 3, pp.412-421.
3. Eberhart, R. and Kennedy, J. (1995) 'A new optimizer using particle swarm theory', in Proc. Sixth Int. Symposium on Micro Machine and Human Science, pp.39-43.
4. El-Metwally, K.A., El-Shafei, A.L. and Soliman, H.M. (2006) 'Robust power system stabilizer design using swarm optimization', Int. Journal of Modelling, Identification, and Control, Vol. 1, No. 4, pp.263-271.
5. Feldkamp, L.A., Puskorius, G.V., Davis, L.I. Jr. and Yuan, F. (1992) 'Neural control systems trained by dynamic gradient methods for automotive applications', in Proc. IEEE Int. Joint Conference on Neural Networks, Vol. 2, pp.798-804.
6. ∞ output feedback control of decoupled automobile active suspension systems', IEEE Trans. on Automatic Control, Vol. 44, No. 2, pp.392-396.
7. Hrovat, D. (1997) 'Survey of advance suspension developments and related optimal control applications', Automatica, Vol. 133, pp.1781-1817.
8. Joo, D.S., Al-Holou, N., Weaver, J.M., Lahhdhir, T. and Al-Abbas, F. (2000) 'Non-linear modelling of vehicle suspension system', in Proc. American Control Conference, Chicago, Illinois, pp.115-119.
9. Karkoub, M.A. and Zribi, M. (2006) 'Active/semi-active suspension control using magnetorheological actuators', Int. Journal of Systems Sciences, Vol. 37, No. 1, pp.35-44.
10. Kennedy, J. and Eberhart, R. (1995) 'Particle swarm optimization', in Proc. IEEE Int. Conference on Neural Networks, Vol. 4, pp.1942-1948.
11. Kennedy, J and Eberhart, R. (2001) Swarm Intelligence, Morgan Kaufmann Publisher, San Francisco.
12. Mendes, R., Kennedy, J. and Neves, J. (2004) 'The fully informed particle swarm: Simpler, maybe better', IEEE Trans. on Evolutionary Computation, Vol. 8, No. 3, pp.204-210.
13. Moran, A. and Nagai, M. (1992) 'Analysis and design of active suspensions by robust control theory', JSME Int. Journal, Series 3, Vol. 35, No. 3, pp.427-437.
14. ∞ controller for active suspensions and its robustness', in Proc. IEEE Int. Conference on Control Applications, pp.445-450.
15. Palkovics, L., Gaspar, P. and Bokor, J. (1993) 'Design of active suspension system in the presence of physical parametric uncertainties', in Proc. ACC, pp.696-700.
16. Ulsoy, G., Hrovat, D. and Tseng, T. (1994) 'Stability robustness of LQ and LQG active suspensions', ASME Journal of Dynamic Systems, Measurement, and Control, Vol. 116, pp.123-131.
17. 1 control to active suspension systems', in Proc. IFAC 12th World Congress Int. Federation of Automatic Control, Sydney, Australia, Vol. 3, pp.143-146.