Standard Fuzzy Model Identification using Gradient Methods
Laiq Khan, Shahid Waseem Anjum, Rabiah Badar · 2010
Identification of unknown system by training the parameters adaptively using different fuzzy models has been proven an interesting research area over last few decades. The objective of this paper is to identify a standard fuzzy system using different gradient methods and discuss their characteristics. Approach of this work is to calculate the gradient of the appropriate cost function to minimize the error by updating the parameters and estimate the system perfectly. Results of these methods are compared on the basis of best approximation and fast convergence.