Anfis with Cauchy membership function for robotic arm

An adaptive fuzzy gain scheduling scheme for robotic arm has been proposed. This paper focus on adaptive fuzzy based tracking and gain controller algorithm for obtaining the joints position relative to the desired trajectory, which drives static and different time variations on the environmental changes. We able to estimate them at any point of time, when t >0 or alternatively, starting from the fuzzy initial states, Fuzzy initial states along with system dynamic equations provide us particular fuzzy differential equations (FDEs), referred as fuzzy Cauchy problem, we construct the fuzzy Cauchy problems during the initial time, we introduce two different ways, first we apply the non-fuzzy differential equations with initial conditions of data based. And the second, we apply with anfis with Cauchy membership function for robotic arm to apply with two angles. The proposed adaptive fuzzy based tracking and gain controller algorithm requires much less training patterns than a neural net based adaptive scheme does and hence avoiding excessive training time. Results of simulation show that the proposed adaptive fuzzy controller offers better performance than fixed gain controllers at different operating conditions.