System identification of secondary path dynamics in active noise control by adaptive filter

G. J. Sheu; Shih-Ming Yang; P. R. Huang

System identification of secondary path dynamics in active noise control by adaptive filter

G. J. Sheu, Shih-Ming Yang, P. R. Huang

Research output: Contribution to journal › Article › peer-review

Abstract

Active noise control in real-time is often conducted by feedforward and/or feedback adaptive filter utilizing reference sensor to measure the noise field and error sensor to measure the attenuated noise. The controller design requires the system dynamics of the secondary path including the sensor/actuator dynamics and the acoustics field dynamics to be known both a priori and real-time. A statistical hypothesis test is presented to determine the adaptive filter dimension of system identification model. Experimental results show that the ARX system identification model of order 220 facilitates the adaptive controller design of order 246 to attenuate low-frequency noise effectively. Both identification model and the controller are implemented by digital signal processor for real-time applications.

Original language	English
Pages (from-to)	241-248
Number of pages	8
Journal	Zhongguo Hangkong Taikong Xuehui Huikan/Transactions of the Aeronautical and Astronautical Society of the Republic of China
Volume	36
Issue number	3
Publication status	Published - 2004 Sept

All Science Journal Classification (ASJC) codes

Aerospace Engineering

Cite this

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title = "System identification of secondary path dynamics in active noise control by adaptive filter",

abstract = "Active noise control in real-time is often conducted by feedforward and/or feedback adaptive filter utilizing reference sensor to measure the noise field and error sensor to measure the attenuated noise. The controller design requires the system dynamics of the secondary path including the sensor/actuator dynamics and the acoustics field dynamics to be known both a priori and real-time. A statistical hypothesis test is presented to determine the adaptive filter dimension of system identification model. Experimental results show that the ARX system identification model of order 220 facilitates the adaptive controller design of order 246 to attenuate low-frequency noise effectively. Both identification model and the controller are implemented by digital signal processor for real-time applications.",

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System identification of secondary path dynamics in active noise control by adaptive filter. / Sheu, G. J.; Yang, Shih-Ming; Huang, P. R.
In: Zhongguo Hangkong Taikong Xuehui Huikan/Transactions of the Aeronautical and Astronautical Society of the Republic of China, Vol. 36, No. 3, 09.2004, p. 241-248.

Research output: Contribution to journal › Article › peer-review

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AU - Huang, P. R.

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N2 - Active noise control in real-time is often conducted by feedforward and/or feedback adaptive filter utilizing reference sensor to measure the noise field and error sensor to measure the attenuated noise. The controller design requires the system dynamics of the secondary path including the sensor/actuator dynamics and the acoustics field dynamics to be known both a priori and real-time. A statistical hypothesis test is presented to determine the adaptive filter dimension of system identification model. Experimental results show that the ARX system identification model of order 220 facilitates the adaptive controller design of order 246 to attenuate low-frequency noise effectively. Both identification model and the controller are implemented by digital signal processor for real-time applications.

AB - Active noise control in real-time is often conducted by feedforward and/or feedback adaptive filter utilizing reference sensor to measure the noise field and error sensor to measure the attenuated noise. The controller design requires the system dynamics of the secondary path including the sensor/actuator dynamics and the acoustics field dynamics to be known both a priori and real-time. A statistical hypothesis test is presented to determine the adaptive filter dimension of system identification model. Experimental results show that the ARX system identification model of order 220 facilitates the adaptive controller design of order 246 to attenuate low-frequency noise effectively. Both identification model and the controller are implemented by digital signal processor for real-time applications.

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System identification of secondary path dynamics in active noise control by adaptive filter

Abstract

All Science Journal Classification (ASJC) codes

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