الفهرس 
IntroductionOnly 14 pages are availabe for public view
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Abstract
Acoustic noise problems in the environment have become more evident as increased numbers of large industrial equipment such as engines, blowers, fans, transformers, and compressors being used. Active noise control (ANC) can produce quieter environments that are safer, more comfortable and more effective in the low frequency range.
Active noise control, in which additional secondary sources are used to cancel noise from (lie original primary source, has received considerable interest and has shown significant promise. The additional secondary sources are used to cancel the primary (unwanted) noise based on the principle of superposition; specifically, an antinoise of equal amplitude and opposite phase is generated and combined with the primary noise, thus resulting in the cancellation of both noises.
In this work, the structure and the mathematical models of the ANC system arc presented. The recursive least square (RLS) algorithm is used for parameter estimation of the primary and the secondary path transfer functions. Then different types of controllers for ANC” system arc developed. First, a fixed stable feedforward controller has been designed using digital model-matching techniques. The interpolation theory, called the Ncvanlinna-Pick problem (NP theory), is used to solve the model-matching problem. The concepts and theories concerning model matching in z-domain are discussed and proved. This controller has good performance for the ANC system in hand. The performance is enhanced by incorporating a certain weighting function in the design process of the fixed feedforward controller.
Second, adaptive controllers are developed for the ANC system to accommodate the effects of system perturbations and to enhance its performance. Therefore, two types of adaptive feedfonvard controllers for ANC system are nested with the lived feedforward controller: KIR feedforward ANC using I’XLMS algorithm and 11R feedforward ANC using filtered-U recursive LMS algorithm. Sianificant performance improvements can be realized using the adaptive hybrid controllers that are designed by adding an adaptive feedback ANC using I’XI.MS algorithm In the adaptive feedfonvard controllers.