Fast self-learning multivariable fuzzy controllers constructed from a modified CPN network

REFERENCES

• BARTO , A. G. , 1990 , Connectionist learning for control an overview. Neural Networks for Control , edited by W. T. Miller , R. S. Sutton and C. W. Anderson ( Cambridge , Mass: MIT Press ), pp. 5 – 58 .
   Google Scholar
• CAUDILL , M. , 1991 , Expert network. Byte , 16 , 108 – 112 .
   Google Scholar
• GALLANT , S. , 1988 , Connectionist expert systems. Communications of the ACM , 31 , 152 – 169 .
   Web of Science ®Google Scholar
• HECHT-NIELSEN , R. , 1987 , Counterpropagation network. Applied Optics , 26 , 4979 – 4984 ; 1988, Applications of counterpropagation network. Neural Networks, 1, 131–139; 1990, Neurocomputing (Reading, Mass Addison-Wesley) .
   PubMed Web of Science ®Google Scholar
• JORDAN , M. , 1989 , Generic constraints on underspecified target trajectories . Proceedings of International Joint Conference on Neural Networks , Washington DC , 18 – 22 June 1989 ( IEEE Press ), pp. 217 – 225 .
   Google Scholar
• KONG , S. G. , and KOSKO , B. , 1992 , Adaptive fuzzy systems for backing up a truck-and-trailer. IEEE Transactions on Neural Networks , 3 , 211 – 233 .
   PubMed Web of Science ®Google Scholar
• KOSKO , B. , 1991, Stochastic competitive learning. IEEE Transactions on Neural Networks , 2 , 522–529.
   PubMed Web of Science ®Google Scholar
• KELLER , J. , YAGER , R. , and TAHANI , H. , 1992 , Neural network implementation of fuzzy logic. Fuzzy Sets and Systems , 45 , 1 – 12 .
   Web of Science ®Google Scholar
• LINKENS , D. A. , and NIE , JUNHONG , 1992 a, A unified real time approximate reasoning approach for use in intelligent control—Part 1 Theoretical development. International Journal of Control , 56 , 347 – 364 ; 1992 b, A unified real time approximate reasoning approach for use in intelligent control —Part 2 Application to multivariable blood pressure control. Ibid., 56, 365–398; 1993 a, Constructing rule-bases for multivariable fuzzy control by self-learning—Part 1 System structure and learning algorithms. International Journal of System Science, 24, 111–127; 1993 b, Constructing rule-bases for multivariable fuzzy control by self-learning—Part 2 Rule-base formation and blood pressure control application. Ibid., 24, 129–157; 1994, Back-propagation neural-network based fuzzy controller with a self-learning teacher. International Journal of Control, 60, 17–39 .
   Web of Science ®Google Scholar
• MANSOUR , N.-E. , and LINKENS , D. A. , 1990 , Self-tuning pole-placement multivariable control of blood pressure for post-operative patients a model-based study. Proceedings of the Institution of Electrical Engineers , Pt D , 137 , 13 – 29 .
   Google Scholar
• NARENDRA , K. S. , and PARTHASARTHY , K. , 1990 , Identification and control of dynamical systems using neural networks. IEEE Transactions on Neural Networks , 1 , 4 – 27 .
   PubMedGoogle Scholar
• NGUYEN , D. H. , and WIDROW , B. , 1990 , Neural networks for self-learning control systems. IEEE Control Systems Magazine , 10 ( 3 ), 18 – 23 .
   Google Scholar
• NIE , JUNHONG , 1987 , Expert fuzzy control systems. MS thesis , Xidian University , Xi'an , People's Republic of China ; 1989, A class of new fuzzy control algorithms. Proceedings of IEEE International Conference on Control and Applications, Israel .
   Google Scholar
• NIE , JUNHONG , and LINKENS , D. A. 1992 , Neural Network-based Approximate Reasoning Principles and Implementation. International Journal of Control , 56 , 399 – 414 ; 1994, A hybrid neural-network-based self-organizing controller. Ibid., 60, 197–222 .
   Web of Science ®Google Scholar
• PROCYK , T. J. , and MAMDANI , E. H. , 1979 , A linguistic self-organizing process controller. Automatica , 15 , 15 – 30 .
   Web of Science ®Google Scholar
• TAKAGI , H. , and HAVASHI , A. , 1991 , NN-driven fuzzy reasoning. International Journal of Approximate Reasoning , 5 , 191 – 212 .
   Google Scholar
• TAKAGI , T. , and SUGENO , M. , 1985 , Fuzzy identification of systems and its application to modeling and control. IEEE Transactions on Systems, Man and Cybernetics , 15 , 116 – 132 .
   Web of Science ®Google Scholar
• WERBOS , P. J. , 1990 , Back-propagation through time what it does and how to do it. Proceedings of the Institute of Electrical and Electronics Engineers , 78 , 1550 – 1560 .
   Web of Science ®Google Scholar