ACTIVE NOISE CONTROL BASED ON FUZZY MODELS

Key words:Active noise control, fuzzy model-based control, fuzzy clustering.Abstract. This paper presents a new approach to acoustic noise control, by introducing a fuzzymodel-based control strategy. Classical linear identification and control tools have been ap-plied to active noise control in the last two decades. In this type of control, the limitations oftheir applicability are well defined. Therefore, new techniques must be developed in order toincrease the performance of active noise controllers. Recent research in control has emphasizedthe importance of nonlinear model-based control, increasing the performance of several typesof systems. From the different nonlinear techniques, fuzzy modeling is one of the most appeal-ing. Fuzzy clustering can be used to identify models directly from data. These models proved tobe accurate for complex and partly known systems, and can represent highly nonlinear systemsin an effective way due to their function approximation properties. This paper applied fuzzyand classical modeling to real-time noise data. The fuzzy model revealed to be more accuratethan the linear model. An inverse model is derived which is applied in the proposed model-based control scheme. The paper presents control results derived from an experimental setup,revealing best performance than classical control methods.1