Abstract
Today, the advanced technology is a part of the everyday’s life. As a result, most of the applications used require a more complex system in order to achieve a better performance. These systems have a mathematic background indicating the need of a better mathematical tool to increase the reliability of them. One of the most significant problems coming up against these systems is undoubtedly the non-linearity of the equations governing them. Herein, a linearization method is proposed and studied through intelligent control. The transformation of a non-linear system into a linear is based on fuzzy logic and more specifically on Takagi-Sugeno technique. Firstly, it is analyzed in a theoretical level followed by two examples. The fuzzy model was developed through Matlab program. Finally, the efficiency of the above method was investigated setting up various values for the under study variables and comparing the results of them with the “actual” ones. The square error method was used for a better evaluation indicating that this method is a useful technique except from the applications where the high accuracy is mandatory.
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Giannakis, A., Giannakis, K., Karlis, A. (2017). An Approach of Non-Linear Systems Through Fuzzy Control Based on Takagi-Sugeno Method. In: Vlamos, P. (eds) GeNeDis 2016. Advances in Experimental Medicine and Biology, vol 988. Springer, Cham. https://doi.org/10.1007/978-3-319-56246-9_9
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DOI: https://doi.org/10.1007/978-3-319-56246-9_9
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