On Development of Fuzzy Controller: The Case of Gaussian and Triangular Membership Functions
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Abstract
In recent years, the use of Fuzzy set theory has been popularised for handling overlap domains in control engineering but this has mostly been within the context of triangular membership functions. In actual practice however, such domains are hardly triangular and in fact for most engineering applications the membership functions are usually Gaussian and sometimes cosine. In an earlier paper, we derived explicit Fourier series expressions for systematic and dynamic computation of grade of membership in the overlap and non-overlap regions of triangular Fuzzy sets. In another paper, we extended the methodology to cover cases of cosine, exponential and Gaussian Fuzzy sets by presenting explicit Fourier series representation for encoding fuzziness in the overlap and non-overlap domains of Fuzzy sets. This current paper presents the development of a “Fuzzy Controller” device, which incorporates the formal mathematical representation for computing grade of membership of Gaussian and triangular Fuzzy sets. It is shown that triangular approximation of Gaussian membership function in Fuzzy control can lead to wrong linguistic classification which may have adverse effects on operational and control decisions. The development of the Fuzzy controller demonstrates that the proposed technique can indeed be incorporated in engineering systems for dynamic and systematic computation of grade of membership in the overlap and non-overlap regions of Fuzzy sets; and thus provides a basis for the design of embedded Fuzzy controller for mission critical applications.
- L. A. Zadeh, “Outline of a New Approach to the Analysis of Complex Systems and Decision Processes,” IEEE Transaction on Systems, Man, and Cybernetics, Vol. SMC-3, No. 1, 1973, pp. 28-44. doi:10.1109/TSMC.1973.5408575
- R. E. Bellman and L. A. Zadeh, “Decision-Making in a Fuzzy Environment,” Management Sciences, Vol. 17, No. 4, 1970, pp. 141-164. doi:10.1287/mnsc.17.4.B141
- H. R. Berenji and P. Khedkar, “Clustering in Product Space for Fuzzy Inference,” 2nd IEEE International Conference on Fuzzy Systems, San Francisco, 1993, pp. 1402-1407.
- D. Ruan and P. F. Fantoni (Eds.), “Power Plant Surveillance and Diagnostics—Applied Research with Artificial Intelligence,” Springer, Heidelberg, 2002.
- V. O. S. Olunloyo and A. M. Ajofoyinbo, “Fuzzy-Stochastic Maintenance Model: A Tool for Maintenance Optimization,” International Conference on Stochastic Models in Reliability, Safety, Security and Logistics, Beer Sheva, 15-17 February 2005, pp. 266-271.
- J. E. Araujo, S. A. Sandri and E. E. N Macau, “A New Class of Adaptive Fuzzy Control System Applied in Industrial Thermal Vacuum Process,” Proceedings of 8th IEEE International Conference on Emerging Technologies and Factory Automation, Vol. 1, 2001, pp. 426-431.
- R. Marinke, and E. Araujo, “Neuro-Fuzzy Modeling for Forecasting Future Dynamical Behaviors of Vibration Testing in Satellites Qualification,” 59th International Astronautical Congress, Glasgow, 2008 (pre-print).
- P. C. Moura, L. Rodrigues and E. Araujo, “A Fuzzy System Applied to Sputtering Glass Production,” Proceedings of Simpósio Brasileiro de Automacao Inteligente (SBAI), Florianópolis, 2007, CD (in Portuguese).
- J. B. Savkovic-Stevanovic, “Fuzzy Logic Control Systems Modelling,” International Journal of Mathematical Models and Methods in Applied Sciences, Vol. 3, No. 4, 2009, pp. 327-334.
- X. Ji and W. Wang, “A Neural Fuzzy System for Vibration Control in Flexible Structures,” Intelligent Control and Automation, Vol. 2, 2011, pp. 258-266. doi:10.4236/ica.2011.23031
- V. O. S. Olunloyo, A. M. Ajofoyinbo and A. B. Badiru, “NeuroFuzzy Mathematical Model for Monitoring Flow Parameters of Natural Gas,” Applied Mathematics and Computation, Vol. 149, No. 3, 2004, pp. 747-770. doi:10.1016/S0096-3003(03)00177-2
- V. O. S. Olunloyo and A. M. Ajofoyinbo, “A New Approach for Treating Fuzzy Sets’ Intersection and Union: A Basis for Design of Intelligent Machines,” 5th International Conference on Intelligent Processing and Manufacturing of Materials, California, 19-23 July 2005, Proceedings in CD-ROM.