參考文獻 |
[2] T. Takagi and M. Sugeno, “Fuzzy identification of systems and it’s application to modeling and control,” IEEE Trans. on Syst., Man, and Cybern., vol. 15, no. 1, pp. 116–132, 1985.
[3] S. Yasunobu, S. Miyamoto and H. Ihara, “Fuzzy control for automatic train operation system,” in Proc. 4th IFAC/IFIP/IFORS Conference on Control in Transportation System, Baden, April 1983.
[4] E. H. Mamdani, “Application of fuzzy logic to approximate reasoning using linguistic synthesis,” IEEE Trans. on Computers, vol. 26, no. 12, pp. 1182–1191, 1977.
[5] P. M. Larsen, “Industrial application of fuzzy logic control,” International Journal of Man-Machine Studies, Vol. 12, no. 1, pp. 3–10, 1980.
[6] S. G. Foda, “Fuzzy control of a quarter-car suspension system,” in Proc. 12th International Conference on Microelectronics, pp. 231–234, 2000.
[7] M. Appleyard and P. E. Wellstead, “Active suspensions: some background,” Proc. Inst. Elect. Eng. Contr. Theory Application, vol. 142, no.2, pp. 123–128, 1995.
[8] A. G. Thompson, “Optimal and suboptimal linear suspensions for road vehicle,” Vehicle System Dynamics, vol. 13, nos. 1-2, pp. 61–72, 1984.
[9] J. H. Li and T. H. S. Li, “Optimal output feedback stabilization of active suspension control using acceleration measurement,” in Proc. IEEE IECON’95 Orlando, FL, pp. 1100–1111, 1995.
[10] M. A. Salman, A. Y. Lee, and N. M. Boustany, “Reduced order design of active suspension control,” in Proc. 27th IEEE CDC, pp. 1038–1043, 1988.
[11] D. Hrovat, “Optimal active suspension structures for quarter-car vehicle models,” Automatica, vol. 26, no. 5, pp. 845–860, 1990.
[12] Y. J. Lin, Y. Q. Lu, and J. Padovan, “Fuzzy logic control of vehicle suspension system,” Int. J. Vehicle Des., vol. 14, nos. 5/6, pp. 457–470, 1993.
[13] C. S. Ting, T. H. S. Li, and F. C. Kung, “Design of fuzzy controller for active suspension system,” Mechatronics, vol. 5, no. 4, pp. 365–384, 1995.
[14] S. J. Heo, K. Park, and S. H. Hwang, “Performance and design consideration for continuously controlled semi-active suspension systems,” Int. J. Vehicle Des., vol. 23, nos. 3/4, pp. 376–389, 2000.
[15] C. S. Ting, Systematic Design Approach for Fuzzy Logic Control Systems, Ph. D. Dissertation, Department of Electrical Engineering, National Cheng Kung University, Taiwan, R. O. C., 1995.
[16] A. S. Cherry and R. P. Jones, “Fuzzy logic control of an automotive suspension system,” Proc. Inst. Elect. Eng. Contr. Theory Application, vol. 142, no. 2, pp. 149–160, 1995.
[17] E. C. Yeh and Y. J. Tsao, “A fuzzy preview control scheme of active suspension for rough road,” Int. J. Vehicle Des., vol. 15, nos. 1/2, pp. 166–180, 1994.
[18] M. V. C. Rao and V. Prahald, “A tunable fuzzy logic controller for vehicle active suspension systems,” Fuzzy Sets Syst., vol. 85, no. 1, pp. 11–21, 1997.
[19] H. W. Du and H. X. Du, “Discussion on grey theory and grey system predication,” in Proc. 4th Conference on the Grey System and Application, pp. 318–323, 1999.
[20] R. C. Luo, T. M. Chen, and K. L. Su, “Target tracking using hierarchical grey-fuzzy motion decision-making method,” IEEE Trans. on Syst., Man, and Cybern., Part A : Systems and Humans, vol. 31, no. 3, pp. 179–186, 2001.
[21] J. H. Chou and T. M. Chen, “Autonomous mobile target tracking system based on grey-fuzzy control algorithm,” IEEE Transactions on Industrial Electronics, vol. 47, no. 4, pp. 920–931, 2000.
[22] P. Y. Chen and J. M. Jou, “Adaptive arithmetic coding using fuzzy reasoning and grey prediction,” Fuzzy Sets Syst., vol. 114, no. 2, pp. 239–254, 2000.
[23] J. H. Chou, S. H. Chen, and F. Z. Lee, “Grey-fuzzy control for active suspension design,” Int. J. Vehicle Des., vol. 19, no. 1, pp. 65–77, 1998.
[24] C. T. Lin and C. S. George Lee, “Neural-network-based fuzzy logic control and decision system,” IEEE Trans. on Computers, vol. 40, no. 12, pp. 1320–1336, 1991.
[25] J. J. Buckley, Yoichi Hayashi, and Ernest Czogala, “On the equivalence of neural nets and fuzzy expert systems,” Fuzzy Sets Syst., vol. 53, pp. 129–134, 1993.
[26] C. T. Chao and C. C. Teng, “Implementation of a fuzzy inference system using a normalized fuzzy neural network,” Fuzzy Sets Syst., vol. 75, pp. 17–31, 1995.
[27] J. J. Buckley and Y. Hayashi, “Neural nets for fuzzy systems,” Fuzzy Sets Syst., vol. 71, pp. 265–276, 1995.
[28] C. T. Lin and C. S. George Lee, “Reinforcement structure/parameter learning for neural-network-based fuzzy logic control systems,” IEEE Trans. on Fuzzy Systems, vol. 2, no. 1, pp. 46–63, 1994.
[29] H. R. Berenji and Pratap Khedkar, “Learning and tuning fuzzy logic controllers through reinforcements,” IEEE Trans. on Neural Networks, vol. 3, no. 5, pp. 724–740, 1992.
[30] C. T. Lin, C. Jian, and C. S. George Lee, “Fuzzy adaptive learning control network with on-line neural learning,” Fuzzy Sets Syst., vol. 71, pp. 25–45, 1995.
[31] J. S. Roger Jang, “ANFIS: Adaptive-network-based fuzzy inference system,” IEEE Trans. on Syst., Man, and Cybern., vol. 23, no. 3, pp. 665–685, 1993.
[32] C. T. Lin, “A neural fuzzy control system with structure and parameter learning,” Fuzzy Sets Syst., vol. 70, pp. 183–212, 1995.
[33] H. Ishibuchi, K. Kwon, and H. Tanaka, “A learning algorithm of fuzzy neural networks with triangular fuzzy weights,” Fuzzy Sets Syst., vol. 71, pp. 277–293, 1995.
[34] H. Ishigami, T. Fukuda, T. Shibata, and F. Arai, “Structure optimization of fuzzy neural network by genetic algorithm,” Fuzzy Sets Syst., vol. 71, pp. 257–264, 1995.
[35] C. C. Wong and S. M. Feng, “Switching-type fuzzy controller design by genetic algorithms,” Fuzzy Sets Syst., vol. 74, pp. 175–185, 1995.
[36] A. Blanco, M. Delgado, and I. Requena, “A learning procedure to identify weighted rules by neural networks,” Fuzzy Sets Syst., vol. 69, pp. 29–36, 1995.
[37] Y. F. Yam, Tommy W. S. Chow, and C. T. Leung, “A new method in determining initial weights of feedforward neural networks for training enhancement,” Neurocomputing, vol. 16, pp. 23–32, 1995.
[38] Z. Cao, A. Kandel, and L. Li, “A new model of fuzzy reasoning,” Fuzzy Sets Syst., vol. 36, pp. 311–325, 1995.
[39] J. C. Lo and S. C. Chen, “Fuzzy modeling using hybrid neural networks,” in Proc. 13th Chinese Society of Mechanical Engineering Conference, Taipei, 1996.
[40] K. Nozaki, H. Ishibuchi, and H. Tanaka, “A simple but powerful heuristic method for generating fuzzy rules from numerical data,” Fuzzy Sets Syst., vol. 86, pp. 251–270, 1995.
[41] J. F. Shepanski, “Fast learning in artificial neural systems: multilayer perceptron training using optimal estimation,” in Proc. IEEE International Conference on Neural Networks, New York, pp. 465–472, 1988.
[42] D. Nguyen and B. Widrow, “Improving the learning speed of 2-layer neural networks by choosing initial values of the adaptive weights,” in Proc. International Joint Conference on Neural Networks, San Diego, CA., pp. 313–315, 1988.
[43] S. Osowski, “New approach to selection of initial values of weights in neural function approximation,” Electron Letters, vol. 29, 1993.
[44] Y. F. Yam and T. W. S. Chow, “Determining initial weights of feedforward neural networks based on least squares method,” Neural Process Letters, vol. 2, 1995.
[45] Y. F. Yam and T. W. S. Chow, “A weight initialization method for improving training training speed in feedforward neural network,” Neurocomputing, vol. 30, pp. 219–232, 1988.
[46] J. Deng, “Introduction to grey system theory,” The Journal of Grey System, vol. 1, pp. 1–24, 1988,
[47] J. Luo and B. Zhang, “A study of grey forecasting and its control analysis of grain yield,” The Journal of Grey System, vol. 1, pp. 91–98, 1989.
[48] Z. Li, “Primary applications of grey system theory in the study of earthquake forecasting,” Journal of Seismology, vol. 4, pp. 27–31, 1986. (in Chinese)
[49] Y. Tamura and D. Zhang, U. Umeda, and K. Sakashita, “Load forecasting using grey dynamic model,” The Journal of Grey System, vol. 4, pp. 45–58, 1992.
[50] D. Yi and R. Yang, “Grey predictor controller for DC speed control system,” The Journal of Grey System, vol. 2, pp. 189–215, 1990.
[51] J. L. Deng, “Control problems of grey systems,” Systems Control Letters, vol. 5, pp. 288–294, 1982.
[52] J. Deng, Grey System Control, Huazhong University of Science and Technology Press, Wuhan, 1997.
[53] H. Z. Zhang and H. X. Wu, “The relationship study between adjusting factors and grey prediction,” in Proc. 5th Conference on the Grey System Theory and Application, pp. 289–298, 2000.
[54] J. Deng, Elements on Grey Theory, Huazhong University of Science and Technology Press, 2002(in Chinese)
[55] M. Mitchell, An Introduction to Genetic Algorithms, MIT press, 1996.
[56] C. H. Chen and S. H. Chen, “Adaptive genetic-neural control based on grey prediction,” in Proc. 4th Conference on the Grey System Theory and Application, pp. 45–49, 1999.
[57] Z. X. Chi, Strategic Study of Developing Intelligent Control System in Genetic Algorithm, Master Thesis, Chung Cheng Institute of Technology, Department of System Engineering, 1999.
[58] K. D. Jong, “On using genetic algorithms to search program space,” in Proc. 2nd International Conference on Genetic Algorithm and Their Application, pp. 210–216, 1999.
[59] K. D. Jong, “Adaptive system design: a genetic approach,” IEEE Trans. on Syst., Man, and Cybern., vol. SMC-10, no.9, pp. 566–574, 1980.
[60] Q. Hong, J. Hong, and Z. M. Chen, “Discussion on grey theory and grey system prediction,” in Proc. 4th Conference on the Grey System Theory and Application, pp. 65–69, 1999.
[61] C. S. Cheng, Y. T. Hsu, and C. C. Wu, “Grey neural networks,” IEICE Transactions on Fundamentals Electronics, Communication and Computer Sciences, E81-A, no.11, pp. 2433–2442, 1998.
[62] Q. Song and B. S. Chissom, “Forecasting enrollments with fuzzy time series – part 2,” Fuzzy Sets Syst., vol. 62, pp. 1–8, 1994.
[63] S. M. Chen, “Forecasting enrollments based on fuzzy time series,” Fuzzy Sets Syst., vol. 81, pp. 311–319, 1996.
[64] Q. Song and B. S. Chissom, “Forecasting enrollments with fuzzy time series – part 1,” Fuzzy Sets Syst., vol. 54, pp. 1–9, 1993.
[65] Y. Wu and B. Xu, “Study on the damping fuzzy control of semi-active suspension,” in Proc. Vehicle Electronics Conference, vol. 1, pp. 66–69, 1999.
[66] J. D. Robson, “Road surface description and vehicle response,” Int. J. Vehicle Des., vol. 1, no. 1, pp. 25–35, 1979.
[67] Y. P. Kuo and T. H. S. Li, “GA-based fuzzy PI/PD controller for automotive active suspension system,” IEEE Trans. on Industrial Electrics, vol. 46, no. 6, pp. 1051–1056, 1999.
[68] R. C. Redfield, “Performance of low-bandwidth semi-active damping concepts for suspension control,” Vehicle System Dynamics, vol.20, pp. 245–267, 1991.
[69] K. B. Todd, Development and Performance Evaluation of Active Suspensions for Road Vehicle Handling, Ph.D. Dissertation, Pennsylvania State University, U.S., 1990.
[70] D. E. Rumelhart and J. L. McClelland, Parallel Distributed Processing, vol. 1, MIT Press, Cambridge, MA, 1986.
[71] M. S. Bazaraa, H. D. Sherali, and C. M. Shetty, Nonlinear Programming-Theory and Algorithms, Wiley, New York, 1993.
[72] F. Salehi, R. Lacroix, and K. M. Wade, “Effects of learning parameters and data presentation on the performance of back-propagation networks for milk yield prediction,” Transactions of the ASAE(American Society of Agricultural Engineers), vol. 41, no. 1, pp. 253–259, 1998.
[73] T. J. Sejnowski and C. R. Rosenberg, “Parallel networks that learn to pronounce english text,” Complex Systems, vol. 1, no. 1, pp. 145–168, 1987.
[74] Y. P. Huang and C. H. Huang, “Real-valued genetic algorithms for fuzzy grey prediction system,” Fuzzy Sets Syst., vol. 87, no. 3, pp. 265–276, 1997.
[75] Y. T. Hsu and C. M. Chen, “A novel fuzzy logic system based on N-version programming,” IEEE Trans. on Fuzzy Systems, vol. 8, no. 2, pp. 155–170, 2000.
[76] K. Q. Shi, G. W. Wu, and Y. P. Hwang, Theory of Grey Information Relation, Chuan Hwa, Taiwan, 1994.
[77] Y. C. Hu, R. S. Chen, Y. T. Hsu, and G. H. Tzeng, “Grey self-organizing feature maps,” Neurocomputing, vol. 48, pp. 863–877, 2002.
[78] H. Zhang, X. Ma, and W. Xu, “Design fuzzy controllers for complex systems with an application to 3-stage inverted pendulums,” Information Sciences, vol. 72, pp. 271–284, 1993. |