Adaptive Fuzzy Attraction Region in Comparison with Generalized Quantitative Feedback Theory

This paper compares a new type of robust Fuzzy based designing algorithm which is entitled Adaptive Fuzzy Attraction Region (AFAR) with Generalized Quantitative Feedback Theory (GQFT) on MIMO nonlinear systems whose inputs and outputs are differentiable with respect to uncertain parameters of system. Then, an application of both algorithms for a MIMO nonlinear manipulator is presented. To demonstrate the advantages of both methods vast simulations and mathematical criteria for different inputs having parameter uncertainties are considered. The obtained results show the efficiency of both methods beside their disadvantages in comparison to each other.