Stochastic model predictive control with driver behavior learning for improved powertrain control

Proceedings of the IEEE Conference on Decision and Control

Volumn , Issue , 2010, Pages 6077-6082

  Bichi, M ^a   Ripaccioli, G ^a   Di Cairano, S ^b   Bernardini, D ^a   Bemporad, A ^c   Kolmanovsky, I V ^d  

^a UNIVERSITY OF SIENA   (Italy)

^b Powertrain Control R and A   (Italy)

^c UNIVERSITY OF TRENTO   (Italy)

^d UNIVERSITY OF MICHIGAN   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ADAPTIVE CRUISE CONTROL; DYNAMICS; MODEL PREDICTIVE CONTROL; OPTIMIZATION; POWERTRAINS; PREDICTIVE CONTROL SYSTEMS; STOCHASTIC CONTROL SYSTEMS; STOCHASTIC SYSTEMS;

BEHAVIORAL MODEL; DETERMINISTIC COMPONENT; DRIVER BEHAVIOR; DRIVER MODELING; LEADING VEHICLE; NUMERICAL OPTIMIZATIONS; SERIES HYBRID ELECTRIC VEHICLES; VEHICLE DYNAMICS;

STOCHASTIC MODELS;

EID: 79953146438     PISSN: 07431546     EISSN: 25762370     Source Type: Conference Proceeding    
DOI: 10.1109/CDC.2010.5717791     Document Type: Conference Paper

References (15)

1. C. Garcia, D. Prett, and M. Morari, "Model predictive control: theory and practice-a survey," Automatica(Oxford), vol. 25, no. 3, pp. 335-348, 1989.
2. L. Guzzella and C. Onder, Introduction to modeling and control of internal combustion engine systems. Springer, 2004.
3. C. Lin, H. Peng, and J. Grizzle, "A stochastic control strategy for hybrid electric vehicles," in Proc. American Contr. Conf., vol. 5, no. 30, 2004, pp. 4710-4715.
4. L. Johannesson, M. Asbogard, and B. Egardt, "Assessing the potential of predictive control for hybrid vehicle powertrains using stochastic dynamic programming," IEEE Transactions on Intelligent Transportation Systems, vol. 8, no. 1, p. 71, 2007.
5. I. Kolmanovsky, I. Siverguina, and B. Lygoe, "Optimization of powertrain operating policy for feasibility assessment and calibration: stochastic dynamic programming approach," in Proc. American Contr. Conf., vol. 2, Anchorage, AK, 2002.
6. D. Wilson, R. Sharp, and S. Hassan, "The application of linear optimal control theory to the design of active automotive suspensions." Vehicle Syst. Dyn., vol. 15, no. 2, pp. 105-118, 1986.
7. A. Bemporad and S. Di Cairano, "Optimal control of discrete hybrid stochastic automata," in Hybrid Systems: Computation and Control, ser. Lecture Notes in Computer Science, M. Morari and L. Thiele, Eds., no. 3414. Springer-Verlag, 2005, pp. 151-167.
8. P. Couchman, M. Cannon, and B. Kouvaritakis, "Stochastic MPC with inequality stability constraints," Automatica, vol. 42, pp. 2169-2174, 2006.
9. J. Primbs, "Stochastic receding horizon control of constrained linear systems with state and control multiplicative noise," in Proc. American Contr. Conf., New York, NY, 2007, pp. 4470-4475.
10. B. D. O. Anderson, "FromWiener to Hidden Markov Models," Control Systems Magazine, vol. 19, no. 3, pp. 41-51, 1999.
11. L. Rabiner, "A tutorial on hidden Markov models and selected applications in speech recognition," Proc. of the IEEE, vol. 77, no. 2, pp. 257-286, 1989.
12. D. Bernardini and A. Bemporad, "Scenario-based model predictive control of stochastic constrained linear systems," in Proc. 48th IEEE Conf. on Decision and Control, Shanghai, China, 2009, pp. 6333-6338.
13. C. Liang and H. Peng, "Optimal adaptive cruise control with guaranteed string stability," Vehicle system dynamics, vol. 32, no. 4-5, pp. 313-330, 1999.
14. L. Guzzella and A. Amstutz, "QSS-Toolbox Manual," Institut für Mess-und Regeltechnik, Eidgenössische Technische Hochschule Zürich. Zürich, 2005.
15. G. Ripaccioli, D. Bernardini, S. Di Cairano, A. Bemporad, and I. Kolmanovsky, "A stochastic model predictive control approach for series hybrid electric vehicle power management," in Proc. American Contr. Conf., Baltimore, MD, 2010, pp. 5844-5849.