One-to-one mapping and its application to neural networks based control systems design

REFERENCES

• ALBUS , J. S. , 1975 , A new approach to manipulator control, the cerebellar model articulation controller (CMAC) . Transactions of ASME Journal of Dynamic Systems, Measurement and Control , 63 , 220 – 227 .
   Google Scholar
• BROWN , M. , and HARMS , C. J. , 1994 , Neurofuzzy Adaptive Modelling and Control ( Hcmcl–Hcmpstcad , U.K . Prentice–Hall ).
   Google Scholar
• CHEN , S. , COWAN , C. F. N. , and GRANT , P. M. , 1991 , Orthogonal least squares learning algorithm for radial basis function networks . IEEE Transactions on. Neural Networks , 2 , 302 – 309 .
   PubMed Web of Science ®Google Scholar
• COPSON , E. T. , 1986 , Metric Spaces ( Cambridge , U.K . Cambridge University Press ).
   Google Scholar
• FRANKLIN , G. F. , POWELL , J.D. , and EMAMI-NAEINI , L. , 1988 , Feedback Control of Dynamic Systems ( New York Addison–Wesley ).
   Google Scholar
• GIROSI , F. , and POGGIO , T. , 1990 , Networks and the best approximation property . Biological Cybernetics , 63 , 169 – 176 .
   Web of Science ®Google Scholar
• GOODWIN , G. C. , and SIN , K. S. , 1984 , Adaptive Filtering, Prediction and Control ( Englcwood Cliffs , New Jersey , U.S.A . Prentice–Hall ).
   Google Scholar
• HAGGLUND , T. , 1984 . New estimation techniques for adaptive control . Ph.D. dissertation , Linkoping University , Sweden .
   Google Scholar
• LINKENS , D. A. , and AHROD , M. F. , 1993 , Supervisory intelligent control using a fuzzy logic hierarchy . Transactions of the Institute of Measurement and Control , 15 , 112 – 132 .
   Google Scholar
• LIPPMANN , R. P. , 1987 , An introduction to computing with neural networks . IEEE ASSl Magazine 4 – 22 .
   Google Scholar
• MILLER , W. T. , 1989 , Real-time application of neural networks for sensor based control of robots with vision . IEEE Transactions on Systems, Man and Cybernetics , 19 , 825 – 831 .
   Web of Science ®Google Scholar
• MILLNERT , M. , 1982 , Identification and control of systems subject to abrupt changes . Ph.D. dissertation , Linkoping University , Sweden .
   Google Scholar
• NARENDRA , K. S. , and PARTHASARATHY , K. , 1990 , Identification and control of dynamic systems using neural networks . IEEE Transactions on Neural Networks , 1 , 4 – 27 .
   PubMedGoogle Scholar
• POLYCARPOU , M. M. , and JOANNOU , P. A. , 1992 , Learning and convergence analysis of neural-type structured networks . IEEE Transactions on Neural Networks , 3 , 39 – 50 .
   PubMed Web of Science ®Google Scholar
• RUMELHART , D. E. , HINTON , G. E. , and WILLIAMS , R. J. , 1986 , Leaning internal representations by error propagation , in RUMELHART, D. E., and MCCLELLAND, J. L., (editors) Parallel Processing ( Cambridge , Massachusetts , U.S.A . MIT Press ).
   Google Scholar
• SANNER , R. M. and SLOTINE , J. E. , 1992 , Gaussian networks for direct adaptive control . IEEE Transactions on Neural Networks , 3 .
   PubMedGoogle Scholar
• SARPTURK , S. , ISTEFANOPULOS , Y. , and KAYNAK , O. , 1987 , On the stability of discrete-time sliding mode control systems . IEEE Transactions on Automatic Control , 32 , 930 – 932 .
   Web of Science ®Google Scholar
• SLOTINE , J. E. , 1984 , Sliding controller design for nonlinear systems . Internationa! Journal of Control , 40 , 421 – 439 .
   Web of Science ®Google Scholar
• SUTTON , R. , and JESS , I. M. , 1991 , A design study of a self-organizing fuzzy autopilot for ship control . Proceedings of the Institution of Mechanical Engineers , 205 , 35 – 47 .
   PubMedGoogle Scholar
• TZIRKEL-HANCOCK , E. , and FALLSIDE , F. , 1992 , Stable control of nonlinear systems using neural networks. Internal Report , Cambridge University .
   Google Scholar
• WANG , L. X. , 1993 , Stable adaptive fuzzy control of nonlinear systems . IEEE Transactions on Neural Networks , 1 , 146 – 155 .
   Google Scholar
• WANG , H. , BROWN , M. , and HARRIS , C. J. , 1994 , Fault detection for a class of unknown nonlinear systems via associative memory networks . Proceedings of the Institute of Mechanical Engineers , 208 , 101 – 107 ; 1996, Modelling and control of nonlinear, operating point dependent systems via associative memory networks. International Journal of Dynamics and Control, April, to be published .
   Google Scholar
• WANG , H. , and HARRIS , C. J. , 1992 , Identification of a family of unknown nonlinear systems via fuzzy logic. Internal report TR03/92, Department of Electronics and Computer Science , Southampton University ; 1993, Fuzzy logic based robust servomechanical controller design for nonlinear unknown systems. Proceedings of 9th International Conference on Systems Engineering, University of Nevada, Las Vegas, U.S.A., pp. 435–439 .
   Google Scholar
• WANG , H. , LIU , Y. Q. , and You , D. H. , 1991 , Application of a nonlinear self–tuning controller for regulating the speed of a hydraulic turbine . Transactions of the ASME, Journal of Dynamic Systems, Measurement and Control , 113 , 541 – 544 .
   Google Scholar
• WANG , H. , and WANG , A. P. , 1994 , Towards stable neural network controllers . Proceedings of IEE International Conference on Control '94 , vol. 1 , pp. 510 – 514 .
   Google Scholar
• WIDROW , B. , and LEHR , M. A. , 1990 , 30 years of adaptive neural networks perceptron, madaline, and backpropagation . Proceedings of the Institute of Electrical and Electronics Engineers , 78 , 1415 – 1441 .
   Google Scholar
• WIDROW , B. , WINTER , R. G. , and BAXTER , R. A. , 1988 , Layered neural nets for pattern recognition . IEEE Transactions on Acoustics, Speech and Signal Processing , 36 , 1109 – 1118 .
   Google Scholar
• XIE , X. , and EVANS , R. , 1984 , Discrete–time adaptive control for deterministic lime-varying systems . Automatica , 20 , 309 – 319 .
   Google Scholar