id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
work_q6hwg6uubffdvieyd3xnivrg3e	E. Sivaraman	Modeling of an inverted pendulum based on fuzzy clustering techniques	2011	9	.pdf	application/pdf	5255	1033	77	Modeling of an Inverted Pendulum based on Fuzzy Clustering Techniques Modeling of an Inverted Pendulum based on Fuzzy Takagi-Sugeno (T-S) fuzzy modeling based on clustering model is proposed for an inverted pendulum based on fuzzy cNonlinear, Clustering, Fuzzy, Inverted Pendulum, Takagi-Sugeno. fuzzy membership function and rules from measured input Fuzzy clustering can be used as tool to partition the data where Yasukawa [6] uses the fuzzy c-means algorithm to cluster the output data points to determine the fuzzy rules, and use some cluster serves as a local linear model of the system, the fuzzy cfuzzy c-means , G-K clustering and Gath Geva algorithms are Cluster validity refers to the problem whether a given fuzzy It measures the fuzziness of the cluster partition only, which is 3.3 Fuzzy C-means Clustering Algorithm Initialization parameters of fuzzy c-means algorithm are given as: of inverted pendulum using fuzzy c-means algorithm is shown in 	./cache/work_q6hwg6uubffdvieyd3xnivrg3e.pdf	./txt/work_q6hwg6uubffdvieyd3xnivrg3e.txt