In this paper, a tuning strategy for the design of fractional-order proportional-integral-derivative ((PID mu)-D-lambda) controllers is proposed. First, a (PID mu)-D-lambda controller is designed with genetic algorithm in order to obtain the training data. Then, three Adaptive Network Fuzzy Inference System (ANFIS) structures, related to K-p, K-i and K-d parameters of the (PID mu)-D-lambda controller, are formed by using the training data. These ANFIS structures are used in the (PID mu)-D-lambda controller instead of K-p, K-i and K-d parameters, and they are capable of self-tuning during the simulation based on the input signal of the adaptive (PID mu)-D-lambda controller (ANFIS-(PID mu)-D-lambda). Finally, in order to show the control performance and robustness of the proposed parameters adjustment method with ANFIS, simulation results are obtained by using the MATLAB-Simulink program for two different systems and the results obtained from ANFIS-(PID mu)-D-lambda controller are compared with the results of (PID mu)-D-lambda and fuzzy logic controller.