Abstract
Control systems are small components that control the behavior of larger systems. In the last years, sophisticated controllers have been widely used in the hardware/software embedded systems contained in a growing number of everyday products and appliances. Therefore, the problem of the automatic synthesis of controllers is extremely important. To this aim, several techniques have been applied, like cell-to-cell mapping, dynamic programming and, more recently, model checking. The controllers generated using these techniques are typically numerical controllers that, however, often have a huge size and not enough robustness. In this paper we present an automatic iterative process, based on genetic algorithms, that can be used to compress the huge information contained in such numerical controllers into smaller and more robust fuzzy control systems.
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
Leu, M.C., Kim, T.Q.: Cell mapping based fuzzy control of car parking. In: ICRA, pp. 2494–2499 (1998)
Kreisselmeier, G., Birkholzer, T.: Numerical nonlinear regulator design. IEEE Transactions on Automatic Control 39(1), 33–46 (1994)
Della Penna, G., Intrigila, B., Magazzeni, D., Melatti, I., Tofani, A., Tronci, E.: Automatic generation of optimal controllers through model checking techniques (To be published in Informatics in Control, Automation and Robotics III, Springer-Verlag, Heidelberg) draft available at the http://www.di.univaq.it/magazzeni/cgmurphi.php
Della Penna, G., Intrigila, B., Magazzeni, D., Melatti, I., Tofani, A., Tronci, E.: Automatic synthesis of robust numerical controllers (To appear in IEEE Proceedings of the Third International Conference on Autonomic and Autonomous Systems) (ICAS 2007), draft available at the http://www.di.univaq.it/magazzeni/tr.php
Papa, M., Wood, J., Shenoi, S.: Evaluating controller robustness using cell mapping. Fuzzy Sets and Systems 121(1), 3–12 (2001)
Kautz, H., Thomas, W., Vardi, M.Y.: 05241 executive summary – synthesis and planning. In: Kautz, H., Thomas, W., Vardi, M.Y. (eds.) Synthesis and Planning. Number 05241 in Dagstuhl Seminar Proceedings (2006)
Kosko, B.: Neural Networks and Fuzzy Systems. Prentice-Hall, Englewood Cliffs (1992)
Sekine, S., Imasaki, N., Tsunekazu, E.: Application of fuzzy neural network control to automatic train operation and tuning of its control rules. In: Proc. IEEE Int. Conf. on Fuzzy Systems 1993, pp. 1741–1746. IEEE Computer Society Press, Los Alamitos (1995)
Mitchell, M.: An Introduction to Genetic Algorithms. MIT Press, Cambridge (1998)
Intrigila, B., Magazzeni, D., Melatti, I., Tofani, A., Tronci, E.: A model checking technique for the verification of fuzzy control systems. In: CIMCA 2005. Proceedings of International Conference on Computational Intelligence for Modelling Control and Automation (2005)
Tan, G.V., Hu, X.: More on design fuzzy controllers using genetic algorithms: Guided constrained optimization. In: Proc. IEEE Int. Conf. on Fuzzy Systems, pp. 497–502. IEEE Computer Society Press, Los Alamitos (1997)
CGMurphi Web Page: http://www.di.univaq.it/magazzeni/cgmurphi.php
Li, H., Gupta, M.: Fuzzy Logic and Intelligent Systems. Kluwer Academic Publishers, Boston, MA (1995)
Jin, J.: Advanced Fuzzy Systems Design and Applications. Physica-Verlag (2003)
Nelles, O., Fischer, M., Muller, B.: Fuzzy rule extraction by a genetic algorithm and constrained nonlinear optimization of membership functions. In: Proceedings of the Fifth IEEE International Conference on Fuzzy Systems, FUZZ–IEEE 1996, vol. 1, pp. 213–219. IEEE Computer Society Press, Los Alamitos (1996)
Jian Wang, L.S., Chao, J.F.: An efficient method of fuzzy rules generation. In: Intelligent Processing Systems. In: ICIPS 1997, vol. 1, pp. 295–299 (1997)
Homaifar, A., McCormick, E.: Simultaneous design of membership functions and rule sets for fuzzy controllers using genetic algorithms. In: IEEE Transactions Fuzzy Systems, vol. 3, pp. 129–139. IEEE Computer Society Press, Los Alamitos (1995)
GAlib Web Page: http://lancet.mit.edu/ga
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2007 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Della Penna, G., Fallucchi, F., Intrigila, B., Magazzeni, D. (2007). A Genetic Approach to the Automatic Generation of Fuzzy Control Systems from Numerical Controllers. In: Basili, R., Pazienza, M.T. (eds) AI*IA 2007: Artificial Intelligence and Human-Oriented Computing. AI*IA 2007. Lecture Notes in Computer Science(), vol 4733. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74782-6_21
Download citation
DOI: https://doi.org/10.1007/978-3-540-74782-6_21
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-74781-9
Online ISBN: 978-3-540-74782-6
eBook Packages: Computer ScienceComputer Science (R0)