Learning systems in intelligent control: An appraisal of fuzzy, neural and genetic algorithm control applications

IEE Proceedings: Control Theory and Applications

Volumn 143, Issue 4, 1996, Pages 367-386

  Linkens, D A ^a   Nyongesa, H O ^a  

^a UNIVERSITY OF SHEFFIELD   (United Kingdom)

Author keywords

Fiery systems; Fn::y neiircil control systems; Genetic learning; Intelligent control; Neural networks

Indexed keywords

CLOSED LOOP CONTROL SYSTEMS; CONTROL SYSTEM SYNTHESIS; FUZZY CONTROL; FUZZY SETS; GENETIC ALGORITHMS; HEURISTIC METHODS; LARGE SCALE SYSTEMS; LEARNING SYSTEMS; NEURAL NETWORKS;

FUZZY NEURAL CONTROL SYSTEMS; GENETIC LEARNING;

INTELLIGENT CONTROL;

EID: 0030190701     PISSN: 13502379     EISSN: None     Source Type: Journal    
DOI: 10.1049/ip-cta:19960392     Document Type: Article

References (120)

1. ASTROM, K.J., and McAVOY, T.J.: 'Intelligent control: an overview and evaluation' in WHITE, D.A., and SOFGE, D.A.: 'Handbook of intelligent control: neural, fuzzy adaptive approaches' (Van Nostrand Reinhold, NY, 1992), pp. 3-34
2. 'Seeking the essence of intellieent control', IEEE Control Syst. Mag., June 1994
3. 'Intelligence and learning', IEEE Control Syst. Mag., June 1995
4. ANTSAKLIS, P.: 'Defining intelligent control - report of the task force on intelligent control', IEEE Control Syst. Mag., June 1994, pp. 4 et seq
5. WARWICK, K.: 'Neural networks for control: counter arguments'. Proceedings of IEEE international conference on Control, Coventry, UK, 1994, pp. 95-99
6. HARRIS, C.J.: 'Comparative aspects of neural networks and fuzzy logic for real-time control' in WARWICK, K., IRWIN, G.W., and HUNT, K.J. (Eds.): 'Neural networks for control and systems' (Peter Peregrinus, London, 1992), pp. 72-93
7. BAKER, W.L., and FARRELL, J.A.: 'An introduction to connectionist learning control' in WHITE, D.A., and SOFGE, D.A.: 'Handbook of intelligent control: neural, fuzzy adaptive approaches' (Van Nostrand Reinhold, NY, 1992), pp. 35-64
8. FURUHASHI, T., HORIKAWA, S., and UCHIKAWA, Y.: 'On the stability of fuzzy control systems using a fuzzy modelling method'. Proceedings of international conference on Industrial electronics, control, instrumentation and automation, San Diego, 1992, Vol. 2, pp. 982-985
9. WANG, L.X.: 'Adaptive fuzzy systems and control: design and stability analysis' (Prentice-Hall, NJ, USA)
10. BROWN, M., and HARRIS, C.J.: 'Least mean squares learning in associative memory networks'. Proceedings of IEEE international symposium on Intelligent control, 1992, pp. 531-536
11. KELLER, J.M., HAYASHI, Y., and CHEN, Z.: 'Interpretation of nodes in networks for fuzzy logic'. Second IEEE international conference on Fu::y systems, San Francisco, CA, USA, 1993, pp. 1203-1207
12. KONG, S.G., and KOSKO, B.: 'Adaptive fuzzy systems for backing up a truck-and-trailer', IEEE Trans. Neural Netw., 1992, 3, (2), pp. 211-223
13. TAKAGI, H., and HAYASHI, I.: 'NN-driven fuzzy reasoning', Int. J. Approx. Reason., 1991, 5, (3), pp. 191-212
14. JANG, J.S., and SUN, C.T.: 'Functional equivalence between radial basis function networks and fuzzy inference systems', IEEE Trans. Neural Nem:, 1993, 4, (1), pp. 156-158
15. NIE, J., and LINKENS, D.A.: 'Learning control using fuzzified self-organising radial basis function network', IEEE Trans. Fuzzy Syst., 1993, 1, (4), pp. 280-287
16. NIE, J., and LINKENS, D.A.: 'A fuzzified CMAC self-learning controller'. Proceedings of second IEEE international conference on Fu::y systems, San Francisco, CA, USA, 1993, pp. 500-505
17. BUCKLEY, J.J., and HAYASHI, Y.: 'Hybrid neural nets can be fuzzy controllers and fuzzy expert systems', Fuzzy Sets Syst., 1993, 60, pp. 135-142
18. WHITE, D.A., and SOFGE, D.A.: 'Handbook of intelligent control: neural, fuzzy adaptive approaches' (Van Nostrand Reinhold, NY, 1992)
19. LINKENS, D.A., and NYONGESA, H.O.: 'Genetic algorithms for fuzzy control part 1: Offline system development and application', IEE Proc. Control Theory Appl., 142, (3), pp. 161-176
20. LINKENS, D.A., and NYONGESA, H.O.: 'Genetic algorithms for fuzzy control part 2: Online system development and application', IEE Proc. Control Theory Appl., 142, (3), pp. 177-185
21. LINKENS, D.A., and NYONGESA, H.O.: 'Evolutionary learning in fuzzy neural control systems'. Proceedings of the third European congress on Intelligent techniques and soft computing, EUFIT '95, Aachen, Germany, 28-31 August 1995
22. KARR, C.L., and SCHAFFER, J.: 'Design of an adaptive fuzzy logic using a genetic algorithm'. Proceedings of international conference on Genetic algorithms, 1989, (Morgan Kauffman)
23. KARR, C.L., BELEW, R., and BOOKER, L.: 'Genetic algorithm based fuzzy control of spacecraft autonomous rendezvous'. Proceedings of international conference on Genetic algorithms, 1991, (Morgan Kauffman)
24. MEREDITH, D.L., KARR, C.L., and KUMAR, K.K.: 'The use of genetic algorithms in the design of fuzzy logic controllers'. Third workshop on Neural networks WNN92, Houston, TX, USA, 1993, pp. 549-555
25. FELDMAN, D.S.: 'Fuzzy network synthesis with genetic algorithms'. Proceedings of international conference on Genetic algorithms, 1993, pp. 312-317
26. MACHADO, R.J., and DA ROCHA, A.F.: 'Evolutive neural networks'. IEEE international conference on Fuzzy systems, San Diego, CA, USA, 1992, pp. 493-500
27. ZADEH, L.A.: 'Fuzzy logic, neural networks and soft computing', Commun. ACM, 1994, 37, (3), pp. 77-84
28. HUNT, K.J., SBARBARO, D., ZBIKOWSKI, R., and GAWTHROP, P.J.: 'Neural networks for control systems - a survey', Automata, 28, 1992, (6), pp. 1083-1112
29. WARWICK, K., IRWIN, G.W., and HUNT, K.J. (Eds.): 'Neural networks for control and systems' (Peter Peregrinus, London, 1992)
30. SCHAFFER, J.D., WHITLEY, D., and ESHELMAN, L.J.: 'Combinations of genetic algorithms and neural networks: a survey of the state of the art'. Proceedings of international workshop on Combination of GA and NN, Baltimore, MD, USA, 1992, pp. 1-37
31. TAKAGI, H.: 'Fusion techniques of fuzzy systems and neural networks and fuzzy systems and genetic algorithms', Proc. SPIE Int. Soc. Opt. Eng., 1993, 2061, pp. 402413
32. BUCKLEY, J.J. and HAYASHI Y.: 'Fuzzy neural networks - a survey', Fuzzy Sets Syst., 1994, 66, (1), pp. 1-13
33. ZADEH, L.A.: 'Outline of a new approach to the analysis of complex systems and decision processes', IEEE Trans., 1973, SMC-3, pp. 28-44
34. LEE, C.C.: 'Fuzzy logic in control systems', IEEE Trans., 1990, SMC-20, pp. 40435
35. TAKAGI, T., and SUGENO, M.: 'Fuzzy identification of systems and its application to modeling and control', IEEE Trans., 1985, SMC-15, pp. 116-132
36. PROCYK, T.J., and MAMDANI, E.H.: 'A linguistic self-organising process controller', Automatica, 1977, 15, pp. 15-30
37. DALEY, S., and GILL, K.F.: 'A design study of a self-organising controller', Proc. Inst. Mech. Eng. C, 1986, 200, pp. 59-69
38. LINKENS, D.A., and ABBOD, M.F.: 'Self-organizing fuzzy logic controllers for real-time processes'. Proceedings of IEE Control '91, 1991, Paper 332, pp. 971-976
39. LAYNE, J.R., PASSING, K.M., and YURKOVICH, S.: 'Fuzzy learning control for antiskid braking system', IEEE Trans. Control Syst. Teclinol., 1993, 1, (2), pp. 122-129
40. WANG, L.X.: 'Stable adaptive fuzzy control of non-linear systems', IEEE Trans. Fu:zy Syst., 1993, 1, (2), pp. 146-155
41. RUMELHART, D.E., HINTON, G.E., and WILLIAMS, R.J.: 'Learning internal representations by error backpropagation' in RUMELHART and McCLELLAND (Eds.): 'Parallel distributed processing (MIT Press, 1986)
42. ALDUS, J.S.: 'A new appraoch to manipulator control: the cerebellar model articulation controller', Trans ASME, G, J. Dyn. Syst., Meas. Control, 1975, 97, pp. 220-227
43. ALBUS, J.S.: 'Data storage in the cerebellar model articulation controller', Trans. ASME, G, J. Dyn. Syst., Meas. Control, 1975, 97, pp. 228-233
44. AN, P.E., ASLAM-MIR, S., BROWN, M., HARRIS, C.J., and MCLEAN, D.: Theoretical aspects of the CMAC and its application to high-dimensional aerospace modelling problems'. Proceedings of IEE international conference on Control, Coventry, UK, 1994, pp. 1466-1471
45. AN, P.E., BROWN, M., and HARRIS, C.J.: 'Aspects of instantaneous on-line learning rules'. Proceedings of IEE international conference on Control, Coventry, UK, 1994, pp. 646-651
46. HECHT-NELSON, R.: 'Neurocomputing' (Addison-Wesley, 1987)
47. KOHONEN, T.: 'Slef-organization and associative memory' (Springer-Verlag, Berlin, 1987)
48. GROSSBERG, S.: 'Competitive learning: From interactive activation to adaptive resonance', Cognitive Sei., 1987, 11, pp. 23-63
49. BARNDEN, J.A., and SRINIVAS, K.: Temporal winner-takeall networks', IEEE Trans. Neural Netw., 1993, 4, (5), pp. 844853
50. MOODY, J., and DARKEN, C.J.: 'Fast learning in networks of locally tuned processing units', Neural Coinput, 1989, 1, pp. 281294
51. HOPFIELD, J.J., and TANK, D.W.: 'Computing with neural circuits: A model', Science, 1986, 233, pp. 625-633
52. WILLIAMS, R.J., and ZIPSER, D.: 'A learning algorithm for continually running fully recurrent neural networks', Neural Cornput., 1994, 1, pp. 270-280
53. TSOI, A.C., and BACK, A.: 'Locally recurrent globally feedforward networks: a critical review of architectures', IEEE Trans. Neural Netw., 1994, 5, (2), pp. 229-239
54. FRANSCONI, P., GORI, M., and SODA, G.: 'Local feedback multilayered networks', Neural Comput., 1992, 4, pp. 120-130
55. BACK, A., and TSOI, A.C.: 'FIR and IIR synapses, a new neural network architecture for time series modelling', Neural Cornput., 1991, 3, (3), pp. 375-385
56. SASTRY, P.S., SANTHARAM, G., and UNNIKRISHNAN, K.P.: 'Memory neuron networks for identification and control of dynamical systems', IEEE Trans. Neural Netw., 1994, 5, (2), pp. 306-319
57. OLUROTIMI, O.: 'Recurrent neural network training with feedforward complexity', IEEE Trans. Neural Netw., 1994, 5, (2), pp. 185-197
58. NARENDRA, K., and PARTHASARATHY, K.: 'Identification and control of dynamical systems using neural networks', IEEE Trans. Neural Netw., 1990, 1, pp. 4-27
59. NARENDRA, K., and PARTHASARATHY, K.: 'Gradient methods for optimisation of dynamical systems containing neural networks', IEEE Trans. Neural Netw., 1991, 2, (2), pp. 252-262
60. CLIFF, D., HARVEY, I., and HUSBANDS, P.: 'Incremental evolution of neural network architectures for adaptive behaviour'. Proceedings of European symposium on Artificial neural networks, 1993, pp. 39-44
61. JANSEN, M.: 'From fuzzy to neuro: Neural nets for statistical modelling of processes'. Proceedings of 8th international colloquium on Approximate reason, Duisburg, 1994
62. BERENJI, H.R., and KHEDKAR, P.: 'Learning and tuning fuzzy logic controllers through reinforcements', IEEE Trans. Neural Netw., 1992, 3, (5), pp. 724-740
63. ANDERSON, C.W.: 'Learning to control an inverted pendulum using neural networks', IEEE Control Syst. Mag., April 1989, pp. 31-37
64. MILLER, W.T., SUTTON, R., and WERBOS, P.J.: 'Neural networks for control' (MIT Press, Cambridge, MA, USA, 1990)
65. WERBOS, P.J.: 'Neurocontrol and supervised learning: an over view and evaluation' in WHITE, D.A., and SOFGE, D.A.: 'Handbook of intelligent control: neural, fuzzy adaptive approaches' (Van Nostrand Reinhold, NY, 1992), pp. 65-89
66. AGARWAL, M.: 'A systematic classification of neural-networkbased control'. Proceedings of 3rd IEEE conference on Control applications, Strathclyde, UK, 1994, pp. 149-160
67. NGUYEN, D.H., and WIDROW, B.: 'Neural networks for selflearning control systems', Int. J. Control, 1991, 54, (6), pp. 14391452
68. SORENSEN, O.: 'Neural networks for non-linear control'. Proceedings of IEEE international conference on Control applications, Strathclyde, UK, 1994, pp. 161-166
69. CHEN, S., BILLINGS, S.A., COWAN, C.F.N., and GRANT, P.M.: 'Non-linear systems identification using radial basis functions', Int. J. Syst. Sei., I990, 21, (12), pp. 2513-2539
70. HINDE, R.F., and COOPER, D.J.: Proceedings of American Control conference, 1993, pp. 74-78
71. HOLLAND, J.H.: 'Genetic algorithms and the optimal allocation of trials', SIAM J. Comput., 1973, 2, (2), pp. 89-104
72. HOLLAND, J.H.: 'Adaptation in natural and artificial systems' (Addison-Wesley, 1975)
73. GOLDBERG, D.E.: 'Genetic algorithms in search, optimization and machine learning' (Addison-Wesley, 1989)
74. DA VIS, L.: 'A handbook of genetic algorithms' (Van Nostrand Reinhold, 1990)
75. KOSKO, B.: 'Neural networks and fuzzy systems' (Prentice-Hall, Englevvood Cliffs, NJ, USA, 1992)
76. JOINKEN, P.A.: 'On the relations between radial basis function networks and fuzzy systems'. Proceedings of international joint conference on Neural networks, 1992, Vol. 1, pp. 220-225
77. PARK, J., and SANDBERG, I.W.: 'Universal approximation using radial basis function networks', Neural Comput., 1991, 3, pp. 245-257
78. OSAWA, J., HAYASHI, I., and WAKAMI, N.: 'Formulation of CMAC-fuzzy system'. Proceedings of IEEE international conference on Fuzzy systems, 1992, pp. 1179-1186
79. JOU, C.C.: 'A fuzzy cerebellar model articulation controller', Proceedings of IEEE international conference on Fuzzy systems, 1992, pp. 1171-1178
80. NIE, J., and LINKENS, D.A.: 'FCMAC: A fuzzified cerebellar model articulation controller with self-organising capacity', Automatica, 1994, 30, (4), pp. 655-664
81. NIE, J., and LINKENS, D.A.: 'Counter-propagation networkbased fuzzy controller: explicit representation and self-constructing of rule-bases'. Proceedings of international conference on Artificial neural networks, 1992, Vol. 1, pp. 463-466
82. CHOI, J.J., ARABSHAHI, P., MARKS, R.J., and CAUDELL, T.P.: 'Fuzzy parameter adaption in neural systems'. Proceedings of international joint conference on Neural networks, 1992, pp. 232-235
83. WANG, L.X., and MENDEL, J.M.: 'Fuzzy basis functions, universal approximation and orthogonal least squares', IEEE Trans. Neural Netw., 1992, pp. 807-814
84. HORIKAWA, S., FURUHASHI, T., OUMA, S., and UCHIKAWA, Y.: 'A fuzzy controller using a neural network and its capability to learn expert's control rules'. Proceedings of international conference on Fuzzy logic and neural networks, 1990, Vol. 1, pp. 103-106
85. TAKAGI, H., SUZUKI, N., KODA, T., and KOJIMA, Y.: 'Neural networks designed on approximate reasoning architecture and their applications', IEEE Trans. Neural Netw., 1992, 3, (5), pp.752-760
86. LIN, C.T., and LEE, C.S.G.: 'Neural network based fuzzy logic control and decision system', IEEE Trans., 1991, C-tO, (12), pp. 1320-1326
87. BOUSLAMA, F., and ICHIKAWA, A.: 'Application of neural networks to fuzzy control', Neural Netw., 1993, 6, pp. 791-799
88. KHALID, M., OMATU, S., and YUSOF, R.: 'Adaptive fuzzyneuro control with application to a water bath process'. Proceedings of IEEE international conference on Control applications, Strathclyde, UK, 1994, pp. 173-178
89. HIGGINS, C.M., and GOODMAN, R.M.: 'Fuzzy rule-based networks for control', IEEE Trans. Fuzzy Syst., 1994, 2, (1), pp. 82-88
90. NAUCK, D., and KRUSE, R.: 'Interpreting changes in the fuzzy sets of a self-adaptive neural fuzzy controller'. Second international workshop on Industrial fuzzy control and intelligent systems, College Station, TX, USA, 1992, pp. 146-152
91. SHU, S.Y., and HWANG, C.M.: 'Implementation of fuzzy inference with neural network - NNFI structure', Proc. SPIE Int. Soc. Opt. Eng., 1993, 2061, pp. 536-46
92. LIN, C.T., and LEE, C.S.G.: 'Reinforcement structure/parameter learning for neural network based fuzzy logic control systems'. Proceedings of IEEE international conference on Fuzzy systems, San Francisco, CA, USA, 1993, pp. 88-93
93. BARTO, A.G., SUTTON, R.S., and ANDERSON, C.W.: 'Neuronlike adaptive elements that can solve difficult learning control problems', IEEE Trans., 1983, SMC-13, (5), pp. 834-846
94. LIN, C.T., and LEE, C.S.G.: 'Reinforcement structure/parameter learning for neural network based fuzzy logic control systems', IEEE Trans. Fuzzy Syst., 1994, 2, (1), pp. 46-63
95. ESOGBUE, A.O., and MURRELL, J.A.: 'A fuzzy adaptive controller using reinforcement learning neural networks'. Ilicfs, 1993, San Francisco, CA, USA, pp. 178-183
96. ARIMOTO, S., KAWAMURA, S., and MIYASAKI, F. : 'Bettering operation of robots by learning', J. Robot. Syst., 1984, 1, pp. 123-140
97. KYUNG, K.H., and LEE, B.H.: 'Fuzzy data-base derivation using neural network based fuzzy logic controller by self-learning'. Proceedings of IECON, 1993, pp. 435-440 (part 1)
98. GUPTA, M.M., and KNOPF, G.K.: 'Dynamic neural networks for fuzzy inference', Proc. SPIE Int. Soc. Opt. Eng., 1993, 2061, pp. 488-501
99. 1SHIBUCHI, H., NOZAKI, K., YAMAMOTO, N., and TANAKA, H.: 'Construction of fuzzy classification systems with rectangular fuzzy rules using genetic algorithms', Fuzzy Sets Syst., 1994, 65, (2,3), pp. 237-253
100. ISHIBUCH1, H., YAMAMOTO, N., MURATA, T., and TANAKA, H.: 'Genetic algorithms and neighbourhood search algorithms for fuzzy flowshop scheduling problems', Fu:zy Sels Syst., 1994, 67, (1), pp. 81-100
101. JOU, C.C.: 'Supervised learning in fuzzy systems: algorithms and computational capabilities'. Proceedings of IEEE international conference on Fuzzy systems, San Francisco, CA, USA, 1993, pp. 1-6
102. PEDRYCZ, W.: 'Fuzzy neural networks and neurocomputations', Fuzzy Sets Syst., 1993, 56, pp. 1-28
103. PEDRYCZ, W. and, ROCHA, A.F.: 'Fuzzy set based models of neurons and knowledge-based networks', IEEE Trans. Fuzzy Syst., 19941, (4), pp. 254-266
104. GUPTA, M.M., and RAO ,D.H.: 'On the principles of fuzzy neural networks', Fuzzy Sets Syst., 1994, 61, pp. 1-18
105. GUPTA, M.M., and RAO, D.H.: 'Foundations of fuzzy-neural networks', Proc. SPIE Int. Soc. Opt. Eng., 1993, 2061, pp. 436451
106. PEDRYCZ, W.: 'Neural structures of fuzzy decision making', J. Intell. Fuzzy Syst., 1994, 2, pp. 161-178
107. HAYASHI, Y., BUCKLEY, J., and CZOGALA, E.: 'Fuzzy neural network with fuzzy signals and weights'. Proceedings of international joint conference on Neural networks, Baltimore, MD, USA, 1992, pp. 696-701
108. HIROTA, K., and PEDRYCZ, W.: 'Logic based neural networks', Inf. Sei., 1993, 71, pp. 99-130
109. KARR, C.L., and GENTRY, E.J.: 'Fuzzy control of pH using genetic algorithms', IEEE Trans. Fuz:y Syst., 1993, 1, (1), pp. 46-53
110. LEE, M.A., and TAKAGI, H.: 'Integrating design stage of fuzzy systems using genetic algorithms'. Proceedings of IEEE international conference on Fu::y systems, San Francisco, CA, USA, 1993, pp. 612-617
111. SHIBATA.T., and FUKUDA, T.: 'Coordinative behaviour by genetic algorithm and fuzzy in evolutionary multi-agent system'. Proceedings of IEEE international conference on Robotics and automation, Atlanta, GA, USA, May 1993, pp. 760-765
112. LINKENS.D.A., and NYONGESA, H.O.: 'Real-time acquisition fuzzy rules using genetic algorithms'. Proceedings of 1992 IFAC symposium on Artificial intelligence in real-time control, 1993, pp. 335-339
113. VALUENZA-RENDON, M.: The fuzzy classifier system motivation and first resultd' in 'Lecture notes in computer science, vol. 496' Sprinser-Verlae, Berlin, 1991), pp. 338-342
114. PETRIDIS, V., KAZARLIS.X PAPAIKONOMOU, A., and FILELIS, A.: 'A hybrid genetic algorithm for training neural networks'. Proceedincs of international conference on Artificial neural networks, Brighton, UK, 1992, pp. 953-956
115. LYUNG, S.L., and ADELI, H.: 'A parallel genetic/neural network learning algorithm for MIMD shared-memory machines', IEEE Trans. Neural Nein., 1994, 5, (6),'pp. 900-909
116. KOZA, J.R., and RICE, J.P.: 'Genetic generation of both the weights and architecture of a neural network". Proceedings of international joint conference on Neural networks, Seattle, WA, USA, 1991, Vol. 2, pp. 397-404
117. DASGUPTA, D., and MCGREGOR, D.R.: 'Designing neural networks using the structured genetic algorithm'. Proceedings of international conference on Articial neural networks, Brighton, UK, 1992, pp. 263-268
118. HARRIS, C.J., MOORE, C.G., and BROWN, M.: 'Intelligent control; aspects of fuzzy logic and neural networks' (World Scientific, 1993)
119. ROMANIUK, S.G.: 'Evolutionary growth perceptrons'. Proceedings of international conference on Genetic algorithms, 1993, pp. 334-341
120. HORIKAWA, S., FURUHASHI, T., UCHIKAWA, Y., and TAGAWA, T.: 'A study on fuzzy modelling using fuzzy neural networks'. Proceedings of international symposium on Ftczy engineering, 1991