Inverse fuzzy modeling applied to active noise control

Abstract

Active noise control has been developed in the last two decades based on classical linear identification and control tools. As the bounds of application of classical active noise reduction are well defined, the enhancement of this control technique requires the introduction of new features, such as nonlinear modeling and control. Recent research has emphasized the importance of nonlinear model-based controllers, increasing the performance of several types of systems. From the different nonlinear techniques, fuzzy modeling is one of the most appealing. Fuzzy models proved to be very accurate for complex and partly known systems, such as acoustic systems. Inverse models can be identified directly from data, and applied directly as a controller. In this paper, fuzzy modeling is used to identify direct and inverse models of the plant behavior, i.e. the actuator dynamics. The inverse fuzzy control scheme is introduced in active noise control. The performance of the proposed control scheme is compared to classical FIR active noise control in an experimental setup.