Inverse Adaptive Fuzzy model identification of the 2-axes PAM robot arm

In this paper, an Inverse Adaptive Fuzzy model is newly created to simultaneously identify both joints of the prototype 2-axes PAM robot arm. Highly nonlinear features of both joints of the nonlinear manipulator system are identified by the proposed Inverse Adaptive Fuzzy model based on experimental input-output training data. The particle swarm optimization (PSO) algorithm optimally generates the appropriate fuzzy if-then rules and other Adaptive Fuzzy model´s parameters to perfectly characterize the dynamic features of the 2-axes PAM system. For the first time, the novel nonlinear Adaptive Fuzzy Model of the 2-axes PAM robot arm is investigated. The results show that the proposed adaptive Fuzzy Model that is trained by PSO algorithm performs better and has a higher accuracy than the conventional Inverse Fuzzy model.