APPLICATION OF FUZZY LOGIC TOOLBOX FOR MODELLING FUZZY LOGIC CONTROLLERS

Krzysztof Olesiak

Abstract


Computer technology, which has been developing very fast in the recent years, can be also fruitfully applied in teaching. For example, the software package Matlab is highly useful in teaching students at Bachelor Programs of Electrical Engineering and Automatics and Robotics. Fuzzy Logic Toolbox of the Matlab package can be used for designing and modelling controllers. Thanks to a large number of pre-defined elements available in the libraries, it is possible to create even highly complicated models of systems without much effort. Fuzzy Logic Toolbox is especially useful for exploring the basic rules of designing fuzzy logic controllers. The rules involve selecting input and output membership functions, determining their location with respect to one another and defining their ranges. When the membership functions are introduced, a rule base is defined and a defuzzification method is selected. For any defuzzification method, a control surface is obtained, which can be modified by changing the rule base and/or the input and output parameters of the membership function.

Keywords


defuzzification method; fuzzy logic controller;fuzzy set; linguistic variable; membership function; rule base

Full Text:

PDF

References


Carvajal, J., Chen, G., Ogmen, H. (2000). Fuzzy PID controller: Design, performance evaluation, and stability analysis. Information Sciences, No. 123, pp. 249-270.

Jakubiec, B. (2015). Multiphase permanent magnet synchronous motor drive for electric vehicle. Przeglad Elektrotechniczny (Electrical Review), 91, No. 12, pp. 125-128.

Olesiak, K. (2014). Selected Problems of the Asynchronous Drive Control with the Three-phase Soft-start System. Proceedings of the Conference: Symposium on Mechatronics Systems, Mechanics and Materials, Jastrzebia Gora, Poland, October 09-10 2013, In: Mechatronic Systems, Mechanics And Materials II, Book Series: Solid State Phenomena, Vol. 210, pp 245-251.

Prauzner, T. (2015). Analysis of the results of the pedagogical research and EEG in the aspect of effective modern teaching aids in the technical education. In: Society. Integration. Education, Proceedings of the International Scientific Conference. Volume IV, Latvia, Rezekne, May 22th-23th 2015, pp.480-489.

Prauzner, T. (2016). Interactive computer simulation as a response to contemporary problems of technical education. In: Society. Integration. Education, Proceedings of the International Scientific Conference. Volume II, May 27th – 28th 2016, Rēzekne, Latvia. pp. 579-588.

Ptak, P. (2015). Application of DasyLab in teaching electrical engineering. In: Society, Integration, Education, Proceedings of the International Scientific Conference. Volume IV, Latvia, Rezekne, May 22th-23th 2015, pp. 490-499.

Sivanandam, S.N., Sumathi, S., Deepa, S. N. (2006). Introduction to Fuzzy Logic using MATLAB. Springer-Verlag, Berlin.

The Math Works (2012). Fuzzy Logic Toolbox for use with Matlab - User's Guide. 3 Apple Hill Drive Natick, Massachusetts, USA.

Xu, J. X., Hang, C. C., Liu, C. (2000). Parallel structure and tuning of a fuzzy PID controller. Automatica, Vol. 36 (2000), pp. 673-684.




DOI: http://dx.doi.org/10.17770/sie2017vol3.2398

Refbacks

  • There are currently no refbacks.