Use of neural fuzzy networks with mixed genetic/gradient algorithm in automated vehicle control

IEEE Transactions on Industrial Electronics

Volumn 46, Issue 6, 1999, Pages 1090-1102

  Huang, Sunan ^a,b,c   Ren, Wei ^a,b,c  

^a IEEE   (United States)

^b UNIVERSITY OF CALIFORNIA   (United States)

^c NATIONAL UNIVERSITY OF SINGAPORE   (Singapore)

Author keywords

[No Author keywords available]

Indexed keywords

ACCELERATION CONTROL; BACKPROPAGATION; BRAKING; COMPUTER SIMULATION; CONVERGENCE OF NUMERICAL METHODS; FUZZY CONTROL; GENETIC ALGORITHMS; INTELLIGENT CONTROL; INTELLIGENT VEHICLE HIGHWAY SYSTEMS; LEARNING ALGORITHMS; LEARNING SYSTEMS; MATHEMATICAL MODELS;

AUTOMATED VEHICLE GUIDANCE CONTROL; NEURAL FUZZY NETWORKS (NFN);

NEURAL NETWORKS;

EID: 0033339376     PISSN: 02780046     EISSN: None     Source Type: Journal    
DOI: 10.1109/41.807993     Document Type: Article

References (28)

1. P. Varaiya and S. E. Shladover, Sketch of an IVHS systems architecture, PATH, Berkeley, CA, Res. Rep. UCB-ITS-PRR-91-3, 1991.
2. P. Varaiya, Smart cars on smart roads: problems for control, IEEE Trans. Automat. Contr., vol. 38, pp. 195-207, Feb. 1993.
3. S. N. Huang and W. Ren, Design of vehicle following control systems with actuator delays, Int. J. Syst. Sci., vol. 28, no. 2, pp. 145-151, 1997.
4. P. loannou, Z. Xu et al., Intelligent cruise control: Theory and experiment, in Proc. 32nd IEEE Conf. Decision and Control, San Antonio, TX, 1993, pp. 1885-1890.
5. P. Ioannou and Z. Xu, Adaptive throttle control for automatic vehicle following, in Proc. 12th Triennial World Congr. Int. Federation of Automatic Control, Sydney, Australia, 1994, pp. 113-116.
6. W. Ren and D. Green, Continuous platooning: A new evolutionary and operating concept for automated highway systems, Dep. Elect. Eng. Comput. Sci., Univ. California, Berkeley, Memo. UCB/ERL M94/24, 1994.
7. J. Forbes, T. Huang, K. Kanazawa, and S. Russell, The BATmobile: Toward a bayesian automated taxi, in Proc. 14th Int. Joint Conf. Artificial Intelligence, Montreal, P. Q., Canada, 1995, pp. 418-423.
8. A. Niehaus and R. F. Stengel, Probability-based decision making for automated highway driving, IEEE Trans. Veh. Technol., vol. 43, pp. 626-634, Aug. 1994.
9. An expert system for automated highway driving, IEEE Contr. Syst. Mag., vol. 11, pp. 53-60, Apr. 1991.
10. F. Eckhard and M. Robert, Nonlinear path control in automated vehicle guidance, IEEE Trans. Robot. Automat., vol. 13, pp. 49-60, Feb. 1997.
11. S. N. Huang and W. Ren, Safety, comfort, and optimal tracking control in AHS applications, IEEE Contr. Syst. Mag., vol. 18, pp. 50-64, Aug. 1998.
12. S. Kikuchi and P. Chakroborty, Car-following model based on fuzzy inference system, National Research Council, Washington, DC, Transportation Research Record 1365, TRB, 1994, pp. 82-91.
13. H. M. Kim, J. Dickerson, and B. Kosko, Fuzzy throttle and brake control for platoons of smart cars, Fuzzy Sets Syst., vol. 84, no. 23, pp. 209-234, Dec. 1996.
14. J. S. R. Jang, ANFLS: Adaptive-network-based fuzzy inference system, IEEE Trans. Syst., Man, Cybern., vol. 23, pp. 665-685, May/June 1993.
15. Self learning fuzzy controller based on temporal back propagation, IEEE Trans. Neural Networks, vol. 3, pp. 156-159, Jan. 1993.
16. J. S. R. Jang, C. T. Sun, and E. Mizutani, Neuro-Fuzzy and Soft Computing: A Computational Approach to Learning and Machine Intelligence. Upper Saddle River, NJ: Prentice-Hall, 1997.
17. L. X. Wang, Adaptive Fuzzy Systems and Control: Design and Stability Analysis. Englewood Cliffs, NJ: PTR Prentice-Hall, 1994.
18. C. T. Lin and C. S. G. Lee, Reinforcement structure/parameter learning for neural-network-based fuzzy logic control systems, IEEE Trans. Fuzzy Syst., vol. 2, pp. 46-63, Jan. 1995.
19. D. E. Goldberg, Genetic Algorithms in Search, Optimization, and Machine Learning. Reading, MA: Addison-Wesley, 1989.
20. D. Park, A. Kandel, and G. Langholz, Genetic-based new fuzzy reasoning models with application to fuzzy control, IEEE Trans. Syst., Man, Cybern., vol. 24, pp. 39-17, Jan. 1994.
21. K. S. Tang, K. F. Man, and C. Y. Chan, Fuzzy control of water pressure using genetic algorithm, in Proc. IFAC Workshop Safety, Reliability, and Applications of Emerging Intelligent Control Technologies, Hong Kong, Dec. 1994, pp. 15-20.
22. C. K. Chiang, H. Y. Chung, and J. J. Lin, Self-learning fuzzy logic controller using genetic algorithms with reinforcements, IEEE Trans. Fuzzy Syst., vol. 5, pp. 460-467, Aug. 1997.
23. S. B. Choi and J. K. Hedrick, Robust throttle control of automotive engines: Theory and experiments, ASME J. Dynam. Syst., Meas., Contr., vol. 118, no. 1, pp. 92-98, 1996.
24. S. W. Wilson, Quasi-Darwinian learning in a classifier system, in Proc. 4th Int. Workshop Machine Learning, 1987, pp. 59-65.
25. A. D. McAulay and J. C. Oh, Improving learning of genetic rulebased classifier systems, IEEE Trans. Syst., Man, Cybern., vol. 24, pp. 152-159, Jan. 1994.
26. S. Shiekholeslam, Control of a class of interconnected nonlinear dynamical systems: the platoon problem, Ph.D. dissertation, Dep. Elect. Eng. Comput. Sci., Univ. California, Berkeley, 1991.
27. F. Eskafi, D. Khorramabadi, and P. Varaiya, Smartpath: An automated highway system simulator, Dep. Elect. Eng. Comput. Sci., Univ. California, Berkeley, Tech. Note 94-3, 1994.
28. F. Eskafi and D. Khorramabadi, Smartpath User's Manual, Dep. Elect. Eng. Comput. Sci., Univ. California, Berkeley, and PATH/ITS, UCB-94, 1994.