Page 1004 - The Mechatronics Handbook
P. 1004
0066_frame_Ch33.fm Page 28 Wednesday, January 9, 2002 8:00 PM
39. Kovacic, Z., Balenovic, M., Bogdan, S. Sensitivity-based self-learning fuzzy logic for a servo-system,
IEEE Control Systems, June, 1998.
40. Lippmman, R. An introduction to computing with neural nets, IEEE ASSPMagazine, April 1987, pp.
4–22.
41. MATLAB 5.2. MathWorks Corp, USA. 1998.
42. Miller, Th., Sutton, R., Werbos, P.J. Neural Networks for Control, MIT Press, 1990.
43. Nauck, D., Klawonn, F., Kruse, R. Neuronale Netze und Fuzzy-Systeme. Grundlagen des Konnektion-
ismus, Neuronaler Fuzzy-Systeme und der Kopplung mit wissensbasierten Methoden, Vieweg, 1994,
Germany.
44. Nesterov, Y., Nemirovski, A. Interior Point Polynomial Methods in Convex Programming: Theory and
Applications, SIAM, Philadelphia, 1994.
45. Pedrycz, W. Fuzzy Control and Fuzzy Systems, Wiley, New York, 2nd ed., 1993.
46. Piechnik, M., Feuser, A. Simulation mit Komfort - HYVOS 4.0 und MOSIHS 1.0, Ö & P, 38, 1994.
47. Postlethwaite, B.E. A model-based fuzzy controller, Trans IChemE, Vol. 72, Part A, Jan. 1994.
48. Postlethwaite, B.E. Building a model-based fuzzy controller, Fuzzy Sets and Systems, 79(1996), Elsevier.
49. Rehfeldt, K., Shöne, A., Büngener, N. Einsatz von Fuzzy-Reglern zur Drehzahlregelung einer Hydrau-
likpumpe, Ölhydraulik und Pneumatic, 36, Nr. 6, pp. 397–402, 1992.
50. Ronco, E., Gawthrop, P.J. Neural Networks for Modelling and Control. Technical Report: csc97008,
Centre for System and Control, Dept. of Mechanical Engineering, Univ. of Glasgow, 10 Nov. 1997.
51. Simulink, Dynamic System Simulation for MATLAB, Writing S-functions, The Math Works Inc.,
1998.
52. Sontag, E.D. Mathematical control theory, Deterministic Finite Dimensional Systems. Springer-Verlag,
Berlin, 1990.
53. Takagi, T., Sugeno, M. Fuzzy identification of systems and its applications to modeling and control,
IEEE Trans. Systems, Man, and Cybernetics, Vol SMC-15, No. 1, pp. 116–132, 1985.
54. Tanaka, K., Sugeno, M. Stability analysis and design of fuzzy control systems, Fuzzy Sets and Systems,
Vol. 45, 1992, pp. 135–156.
55. Teodorescu, H.N. Sisteme Fuzzy si Aplicatii. Institutul Politehnic Iasi, Romania,1989.
56. Tertisco, M., Penescu, C., Ionescu, G., Ceanga, E. Identificarea Experimentala a Proceselor Automati-
zate. Editura Tehnica, Bucuresti, 1971.
57. Viersma, T. J. Analysis, Synthesis and Design of Hydraulic Servosystems and Pipelines. Elsevier, Amsterdam-
New York, 1980.
58. Vlad, C.I. Contributions to the Direct Computer Control of Electrohydraulic Axes for Industrial
Robots. Technical University “Politehnica”, Bucharest, Romania, 1998.
59. Wang, L., Liu, G.P., Harris, C.J., Brown, M. Advanced Adaptive Control, Pergamon, 1997.
60. Werbos, B. Overview of Design and Capabilities. In Neural Networks for Control, pp. 59–65, MIT
Press, MA, 1990.
61. Westcott, J.H. The minimum-moment-of-error-squared criterion: a new performance criterion for
servo mechanisms, Proc. of IEE., Measurements Section, pp. 471–480, 1954.
62. Yager, R., Zadeh, L. Fuzzy Sets, Neural Networks and Soft Computing, 1994.
63. Zadeh, Lotfi. Fuzzy sets, Information & Control, No. 8, pp. 338–353, 1965.
64. Zadeh, L., King-Sun Fu, Tanaka, K., Shimura, M. Fuzzy Sets and their Applications to Cognitive and
Decision Processes. Academic Press, 1975.
65. Zimmermann, H.-J. Fuzzy Sets Theory - and Its Applications, Kluwer Academic Publishers, Dordrecht,
The Netherlands, 1990.
©2002 CRC Press LLC

