1996
DOI: 10.1121/1.414877
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Control effort weighting in feedforward adaptive control systems

Abstract: Active control of noise and vibration in large dimensional complex systems is generally accomplished with adaptive feedforward control algorithms based on the steepest descent optimization approach. This paper examines the effects of incorporating control effort weighting into the cost function that is minimized by an adaptive control algorithm. When the plant matrix is rank-deficient, the least-squares solution to which the control algorithm converges is nonunique. In such situations, the control signals can … Show more

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Cited by 20 publications
(16 citation statements)
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“…Active noise control is implemented using the leaky "ltered-x LMS algorithm [33,34]. The transfer functions from each actuator to each error sensor are represented at a given frequency as FIR "lters with two coe$cients.…”
Section: Active Noise Control Systemmentioning
confidence: 99%
“…Active noise control is implemented using the leaky "ltered-x LMS algorithm [33,34]. The transfer functions from each actuator to each error sensor are represented at a given frequency as FIR "lters with two coe$cients.…”
Section: Active Noise Control Systemmentioning
confidence: 99%
“…The cost function that minimizes the sum of the squared complex pressures with a uniform, quadratic control effort weighting [27] can be written as…”
Section: Control System Designmentioning
confidence: 99%
“…Usinga methoddescribed by Rossetti [11],the penalty matrix,R, is assumed to bea uniformscalarmultipleof the identitymatrix:…”
Section: Force Limitsmentioning
confidence: 99%