The design of active noise control has been developed in the last two decades based on linear identification and control tools. However, acoustic processes present nonlinearities coming both from the characteristics of the actuator and from the nature of the process. Recent research has emphasized the importance of nonlinear model-based controllers, which increase the performance of several types of systems. Direct and inverse multivariable fuzzy models can be identified directly from data using fuzzy clustering. Inverse models can then be applied directly as controllers, which can be included in an active noise control scheme. This paper proposes the use of fuzzy techniques in active noise control. The performance of the proposed control schemes is compared to classical FIR active noise control in an experimental setup. Model-based fuzzy controllers clearly outperform classical active noise controllers. Keywords: active noise control, fuzzy modeling, fuzzy control, multivariable control, control algorithms.