Abstract
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.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
