Robust predictive control of lambda in internal combustion engines using neural networks

Archives of Civil and Mechanical Engineering

Volumn 13, Issue 4, 2013, Pages 432-443

  Sardarmehni, T ^a   Keighobadi, J ^a   Menhaj, M B ^b   Rahmani, H ^a  

^a UNIVERSITY OF TABRIZ   (Iran)

^b AMIRKABIR UNIVERSITY OF TECHNOLOGY   (Iran)

Author keywords

Air to fuel ratio control; Mean Value Engine Model; MLP; MPC; SMC

Indexed keywords

AIR-TO-FUEL RATIO CONTROL; MEAN VALUE ENGINE MODELING; MLP; MPC; SMC;

COMPUTER SIMULATION; ENGINES; INTERNAL COMBUSTION ENGINES; NEURAL NETWORKS; PREDICTIVE CONTROL SYSTEMS; ROBUST CONTROL; UNCERTAINTY ANALYSIS;

MODEL PREDICTIVE CONTROL;

EID: 84884589833     PISSN: 16449665     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.acme.2013.05.003     Document Type: Article

References (14)

1. Kiencke U., Nielsen L. Automotive Control System for Engine, Driveline, and Vehicle 2004, Springer, Berlin.
2. Zhai Y.J., Yu D.L. Neural network model-based automotive engine air/fuel ratio control and robustness evaluation. Engineering Applications of Artificial Intelligence 2009, 22:171-180.
3. E. Hendricks, S.C. Sorenson, Mean value modeling of spark ignition engines. SAE Technical Paper Series, 900616, 1990.
4. E. Hendricks, A. Chevalier, M. Jensen, S.C. Sorenson, Modeling of intake manifold filling dynamics. SAE Technical Paper Series, 960037, 1996.
5. Wang S.W., Yu D.L. Adaptive air-fuel ratio with MLP network. International Journal of Automation and Computing 2005, 2:125-133.
6. Wang S.W., Yu D.L., Gomm J.B., Page G.F., Douglas S.S. Adaptive neural network model based predictive control for air-fuel ratio of SI engines. Engineering Applications of Artificial Intelligence 2006, 19:189-200.
7. Zhai Y.J., Yu D.W, Guo H.Y., Yu D.L. Robust air/fuel ratio control with adaptive DRNN model and AD tuning. Engineering Applications of Artificial Intelligence 2010, 23:283-289.
8. E. Hendricks, J. Luther, Model and observer based control of internal combustion engines, in: Proceedings of the 1st International Workshop on Modeling Emissions and Control in Automotive Engines, 2001, pp. 9-20.
9. P. Kaidantzis, P. Rasmussen, M. Jensen, T. Vesterholm E. Hendricks, Robust, self-calibrating lambda feedback for SI engines. SAE Technical Paper 930860, 1993.
10. C. Carnevale, D. Coin, M. Secco, P. Tubetti, A/F ratio control with sliding mode technique. SAE Technical Paper 950838, 1995.
11. Wang S.W., Yu D.L. Adaptive neural network for parameter estimation and stable air-fuel ratio control. Neural Networks 2008, 21:102-112.
12. M.B. Menhaj, Computational intelligence (Vol. 1): Fundamentals of Neural Networks, Tehran Polytechnic, Tehran, 2009.
13. Haykin S. Neural Networks: A Comprehensive Foundation 1999, Prentice Hall International Inc., Upper Saddle River, New Jersey 07458.
14. J. Keighobadi, S.M. Shahidi, K. Alioghli, Dynamic sliding mode controller for trajectory tracking of nonholonomic mobile robots, in: Proceedings of the 18th IFAC World Congress, Milano, Italy, August 28-September 2, 2011, pp. 962-967.