Comparative study of type-1 and type-2 fuzzy systems for the three-tank water control problem

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 7630 LNAI, Issue PART 2, 2013, Pages 362-373

  Cervantes, Leticia ^a   Castillo, Oscar ^a   Melin, Patricia ^a   Valdez, Fevrier ^a  

^a TIJUANA INSTITUTE OF TECHNOLOGY   (Mexico)

Author keywords

Fuzzy control; Granular computing; Type 2 fuzzy logic

Indexed keywords

COMPARATIVE STUDIES; GRANULAR SYSTEM; TYPE-2 FUZZY; TYPE-2 FUZZY LOGIC; TYPE-2 FUZZY SYSTEMS; WATER CONTROL; WATER CONTROL PROBLEMS;

FUZZY CONTROL; FUZZY LOGIC; GRANULAR COMPUTING; INTELLIGENT CONTROL; TANKS (CONTAINERS); WATER LEVELS;

FUZZY SYSTEMS;

EID: 84875869683     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-37798-3_32     Document Type: Conference Paper

References (25)

1. Bargiela, A., Pedrycz, W.: Granular Computing: An Introduction. Kluwer Academic Publishers, Dordercht (2003)
2. Bargiela, A., Pedrycz, W.: The roots of Granular Computing. In: GrC 2006, pp. 806-809. IEEE (2006)
3. Castillo, O., Martinez-Marroquín, R., Melin, P., Valdez, F., Soria, J.: Comparative study of bio-inspired algorithms applied to the optimization of type-1 and type-2 fuzzy controllers for an autonomous mobile robot. Information Sciences 192, 19-38 (2012)
4. Castro, J.R., Castillo, O., Melin, P., Rodríguez-Díaz, A.: Building Fuzzy Inference Systems with a New Interval Type-2 Fuzzy Logic Toolbox. In: Gavrilova, M.L., Tan, C.J.K. (eds.) Trans. on Comput. Sci. I. LNCS, vol. 4750, pp. 104-114. Springer, Heidelberg (2008)
5. Castro, J.R., Castillo, O., Melin, P., Rodriguez, A., Mendoza, O.: Universal Approximation of a Class of Interval Type-2 Fuzzy Neural Networks Illustrated with the Case of Nonlinear Identification. In: IFSA/EUSFLAT Conf., pp. 1382-1387 (2009)
6. Castro, J.R.: Tutorial type-2 fuzzy logic theory and applications. In: 3rd International Seminar on Computational Intelligence. IEEE Computational Intelligence Society, Mexico (2006)
7. Cervantes, L., Castillo, O.: Design of a Fuzzy System for the Longitudinal Control of an F-14 Airplane. SCI, vol. 318, pp. 213-224 (2011)
8. Cervantes, L., Castillo, O.: Hierarchical Genetic Algorithms for Optimal Type-2 Fuzzy System Design. In: Annual Meeting of the North American Fuzzy Information Processing Society, pp. 324-329 (2011)
9. Cervantes, L., Castillo, O.: Automatic Design of Fuzzy Systems for Control of Aircraft Dynamic Systems with Genetic Optimization. In: World Congress and AFSS International Conference, pp. OS-413-1-OS-413-7 (2011)
10. Computer Society, The 2011 IEEE Internaional Confenrece on Granular Computing Sapporo, Japan, August 11-13, 2011. IEEE GrC 2011 Indexed by EI (GrC 2005, 2006, 2007, 2008, 2009 are indexed by EI). Call for Papers
11. Dongrui, W., Mendel, J.: On the Continuity of Type-1 and Interval Type-2 Fuzzy Logic Systems. IEEE T. Fuzzy Systems 19(1), 179-192 (2011)
12. Dongrui, W.: A Brief Tutorial on Interval Type-2 Fuzzy Sets and Systems (July 22, 2010)
13. Karnik, N., Mendel, J.: Centroid of a type-2 fuzzy set. Information Sciences 132, 195-220 (2001)
14. Melin, P., Castillo, O.: Intelligent control of aircraft dynamic systems with a new hybrid neuro- fuzzy-fractal Approach. Journal 142(1), 161-175 (2002)
15. Melin, P., Castillo, O.: Adaptive intelligent control of aircraft system with a hybrid approach combining neural network, fuzzy logic and fractal theory. Appl. Soft Comput. 3(4), 363-378 (2003)
16. Mendel, J.: Uncertain Rule-Based Fuzzy Logic Systems: Introduction and New Directions. Prentice-Hall, Upper Saddle River (2001)
17. Niemann, H., Stoustrup, J.: Passive fault tolerant control of a double inverted pendulum a case study. Control Engineering Practice 13(8), 1047-1059 (2005)
18. No, T.S., Mina, B.M., Stone, R.H., Wong, K.C.: Control and simulation of arbitrary flight trajectory-tracking. Department of Aerospace Engineering, Chonbuk National University, Deokjin Dong, Chonju NSW, pp. 560-756 (2006)
19. No, T.S., Kim, J.E., Moon, J.H., Kim, S.J.: Modeling, control, and simulation of dual rotor wind turbine generator system. Renewable Energy 34(10), 2124-2132 (2009)
20. Pedrycz, W., Chen, S.: Granular Computing and Intelligent Systems. Springer, Heidelberg (2011) ISBN 978-3-642-19819-9
21. Pedrycz, W., Skowron, A., Kreinovich, V.: Handbook granular computing. Wiley-Interscience, New York (2008) ISBN:0470035544 9780470035542 2008
22. Sepulveda, R., Castillo, O., Melin, P., Montiel, O.: An Efficient Computational Method to Implement Type-2 Fuzzy Logic in Control Application. In: Melin, P., Castillo, O., Ramírez, E.G., Kacprzyk, J., Pedrycz, W. (eds.) Anal. and Des. of Intell. Sys. using SC Tech. ASC, vol. 41, pp. 45-52. Springer, Heidelberg (2007)
23. Yu, Y., Chen, L., Sun, F., Wu, C.: Matlab/Simulink-based simulation for digital-control system of marine three-shaft gas-turbine. Applied Energy 80(1), 1-10 (2005)
24. Zadeh, L.A.: Some reflections on soft computing, granular computing and their roles in the conception, design and utilization of information/intelligent systems. Soft Comput. 2, 23-25 (1998)
25. Zadeh, L.A.: Outline of a new approach to the analysis of complex systems and decision processes. IEEE Trans.Syst. Man Cybern. SMC-3, 28-44 (1973)