Neural network-based model predictive control of a servo-hydraulic vehicle suspension system

IEEE AFRICON Conference

Volumn , Issue , 2009, Pages

  Dahunsi, O A ^a   Pedro, J O ^a   Nyandoro, O T ^a  

^a UNIVERSITY OF THE WITWATERSRAND   (South Africa)

Author keywords

Model predictive control PID control; Neural networks; Ride comfort; Servo hydraulics; Suspension system

Indexed keywords

PID CONTROL; RIDE COMFORTS; SERVO-HYDRAULICS; SUSPENSION SYSTEM;

AUTOMOBILE PARTS AND EQUIPMENT; AUTOMOBILE SUSPENSIONS; COMPUTER SIMULATION; CONTROLLERS; FEEDFORWARD NEURAL NETWORKS; HYDRAULICS; MATHEMATICAL MODELS; PREDICTIVE CONTROL SYSTEMS; PROPORTIONAL CONTROL SYSTEMS; ROADS AND STREETS; THREE TERM CONTROL SYSTEMS; TWO TERM CONTROL SYSTEMS; VEHICLE PARTS AND EQUIPMENT; VEHICLE SUSPENSIONS;

MODEL PREDICTIVE CONTROL;

EID: 74349113867     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/AFRCON.2009.5308111     Document Type: Conference Paper

References (27)

1. M.K.Hada, A.Menon, and S.Y.Bhave, "Optimisation of an active suspension force controller using genetic algorithm for random input," Defence Science Journal vol. 57, pp. 691-706, Sept. 2007.
2. Y.He and J.McPhee, "A design methodology for mechatronic vehicles: Application of multidisciplinary optimization, multibody dynamics and genetic algorithms," Vehicle Systems Dynamics, vol. 43, pp. 697-733, Oct. 2005.
3. 2 - LQG/LTR controller design for active suspension systems," R and D Journal of the South African Institution of Mechanical Engineering, vol. 23, pp. 32-41, Nov 2007.
4. D. Hrovat, "Survey of advanced suspension developments and related optimal control applications," Automatica, vol. 33, pp. 1781-1817, Oct. 1997.
5. ∞ control of active vehicle suspensions with actuator time delay," Journal of Sound and Vibration, vol. 301, pp. 236-252, Mar. 2007.
6. M.S.Kumar and S.Vijayarangan, "Analytical and experimental studies on active suspension system of light passenger vehicle to improve ride comfort," Mechanika, vol. 65, pp. 34-41, Jun. 2007.
7. B.Gao, D.G.Tilley, R.A.Williams, A.Bean, and J.Donahue, "Control of hydropneumatic active suspesion based a non-linear quarter-car model," in Proceedings of the Institute of Mechanical Engineers, Part I, vol. 220, no. 1, Jan. 2006, pp. 75-31.
8. 2 static - output feedback controller for vehicle suspensions using linear matrix inequalities and genetic algorithms," Vehicle Systems Dynamics, vol. 46, pp. 385-412, May 2008.
9. X.Shen and H.Peng, "Analysis of active suspension systems with hydraulic actuators," in Proceedings of the 2003 IAVSD Conference, Atsuigi, Japan, Aug. 2003, pp. 1-10.
10. J.Z.Feng, J.Li, and F.Yu, "GA-based PID and fuzzy logic control for active vehicle suspension system," International Journal of Automotive Technology, vol. 4, pp. 181-191, Dec. 2003.
11. S.Chantranuwathana and H.Peng, "Adaptive robust force control for vehicle active suspension," International Journal of Adaptive Control and Signal Processing, vol. 18, pp. 83-102, Mar. 2004.
12. Z.Gao, "From linear to nonlinear control means: A practical progression," ISA Transactions, vol. 41, pp. 177-189, Apr. 2002.
13. Y.Kuo and T.S.Li, "GA-based fuzzy PI/PD controller for automotive active suspension system," IEEE Transactions on Industrial Electronics, vol. 46, pp. 1051-10569, Dec. 1999.
14. P.Gaspar, I.Szaszi, and J.Bokor, "Active suspension design using linear parameter varying control," International Journal of Autonomous Systems (IJVAS), vol. 1, pp. 206-221, Jun. 2003.
15. I.Fiahlo and G.J.Balas, "Road adaptive active suspension using linear parameter-varying gain-scheduling," IEEE Transactions on Control Systems Technology, vol. 10, pp. 43-54, Jan. 2002.
16. 2 control of a half vehicle," in Proceedings of the 10th MINI Conference on Vehicle System Dynamics, Identification and Anomalies, Budapest, Hungary, 2006.
17. N.Al-Holou, T.Lahdhiri, D.S.J00, J.Weaver, and F.Al-Abbas, "Sliding model neural network inference fuzzy logic control for active suspension system," IEEE Transaction on Fuzzy System, vol. 10, pp. 234-245, Apr. 2002.
18. J.Cao, H.Liu, P.Li, and D.Brown, "State of the art in vehicle active suspension adaptive control systems based on intelligent methodologies," IEEE Transactions of Intelligent Transportation Systems, vol. 9, pp. 392-405, Sept. 2008.
19. Y.Jin and D.J.Yu, "Adaptive neuron control using an integrated error approach with application to active suspensions," International Journal of Automotive Technology, vol. 9, pp. 329-335, Jun 2008.
20. I.Eski and S.Yildrim, "Vibration control of vehicle active suspension system using a new robust neural network control system," Simulation Modelling Practice and Theory, vol. 17, pp. 778-793, May 2009.
21. D.L.Yu and J.B.Gomm, "Implementation of neural network predictive control to a multivariable chemical reactor," Control Engineering Practice, vol. 11, pp. 1315-1323, Nov. 2003.
22. M.T.Hagan, H.B.Demuth, and O.Jesus, "An introduction to the use of neural networks in control systems," International Journal of Robust and Non-Linear Control, vol. 12, pp. 959-985, Sept 2002.
23. J.Renn and T.Wu, "Modelling and control of a new 1/4t ervo-hydraulic vehicle active suspension system," Journal of Marine Science and Technology, vol. 15, pp. 265-272, 2007.
24. M.Norgaard, O.Ravn, N.K.Poulsen, and L.K.Hansen, Neural Networks for Modelling and Control of Dynamic Systems - A Practitioner's Handbook. Boston, MA: Springer, 2000.
25. J.M.Galvez, L.E.Zarate, and H.Helman, "A model-based predictive control scheme for steel rolling mills using neural networks," Journal of the Brazillian Society of Mechanical Sciences and Engineering, vol. 25, pp. 85-89, Mar. 2003.
26. M.Norgaard, Neural Networks Based Control System Design ToolKit. Department of Automation, Technical University of Denmark: Tech.Report 00-E-892, 2000.
27. A.O'Dwyer, Handbook of PI and PID Controller Tuning Rules. London: Imperial College Press, 2006.