Abstract
Observing the current state of commercial and industrial AI, control and hybrid systems are said to have the highest potentials for massive practical applications of rough set theory. After a brief description of the control problem and fuzzy systems, the principles of rough control and a scenario of fine temperature control are discussed.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
S. Khasnabis, T. Arciszewski, S.K. Hoda, and W. Ziarko, “Urban rail corridor control through machine learning: an IVHS approach,” in B.H.V. Topping, (Ed.), Knowledge Based Systems for Civil and Structural Engineering, Aug. 1993, Civil-Comp Press, Edinburgh, UK, pp.97–104.
W. Ziarko, J.D. Katzberg, “Rough sets approach to system modelling and control algorithm acquisition,” IEEE WESCANEX 93. Communications, Computers and Power in the Modern Environment Conference Proceedings (Cat. No.93CH3317–5), May, 1993, pp. 154–64.
W. Ziarko, “Generation of control algorithms for computerized controllers by operator supervised training,” in Hamza, M.H. (Ed.), Proceedings of the Eleventh IASTED International Conference. Modelling, Identification and Control, Innsbruck, Austria, Feb., 1992, pp.510–13.
R. Nowicki, R. Slowinski, and J. Stefanowski, “Evaluation of vibroacoustic diagnostic symptoms by means of the rough sets theory,” Computers in Industry, Vol.20, No.2, 1992, pp.141–152.
E. Czogala, A. Mr??zek, Z. Pawlak, “The Idea of a Rough Fuzzy Controller and its Application to the Stabilization of a Pendulum-Car System,” Institute of Computer Science Reports, Warsaw University of Technology, February 1994.
A. Mrozek and L. Plonka, “Rough sets for controller synthesis,” Institute of Computer Science Reports, Warsaw University of Technology, October, 1994.
RSSC’94: The Third International Workshop on Rough Sets and Soft Computing, San Jose, CA, Nov., 1994.
T. Munakata (Guest Ed.), “Commercial and Industrial AI,” Communications of the ACM, Vol. 37, No. 3, March, 1994, pp. 23–119.
T. Munakata (Guest Ed.), “New Horizons of Commercial and Industrial AI,” Communications of the ACM, Vol. 38, No. 11, Nov. 1995.
Z. Pawlak, J. Grzymala-Busse, R. Slowinski and W. Ziarko, “Rough sets,” Communications of the ACM, Vol. 38, No. 11, Nov. 1995.
T. Munakata, “Commercial and Industrial AI and Future Perspective on Rough Sets,” Proc. RSSC’94: The Third International Workshop on Rough Sets and Soft Computing, San Jose, CA, Nov., 1994.
T. Munakata and Y. Jani, “Fuzzy Systems: An Overview,” Communications of the ACM, Vol. 37, No. 3, March, 1994, pp. 69–76.
W. Ditto and T. Munakata, “Chaos Systems: Principles and Applications,” Communications of the ACM, forthcoming.
B. Widrow, D.E. Rumelhart, and M.A. Lehr, “Neural Networks: Applications in Industry, Business and Science,” Communications of the ACM, Vol. 37, No. 3, March, 1994, pp. 93–105.
Lee, C.C. Fuzzy logic in control systems: fuzzy logic controller, Parts I and II. IEEE Trans. Sys. Man. Cyb., 20, 2 (March/April, 1990) 404–435.
Author information
Authors and Affiliations
Rights and permissions
Copyright information
© 1997 Kluwer Academic Publishers
About this chapter
Cite this chapter
Munakata, T. (1997). Rough Control: A Perspective. In: Rough Sets and Data Mining. Springer, Boston, MA. https://doi.org/10.1007/978-1-4613-1461-5_4
Download citation
DOI: https://doi.org/10.1007/978-1-4613-1461-5_4
Publisher Name: Springer, Boston, MA
Print ISBN: 978-1-4612-8637-0
Online ISBN: 978-1-4613-1461-5
eBook Packages: Springer Book Archive