Modeling, Identification, and Feedback Control of Noise in an Acoustic Duct

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/57830/1/AcousticDuctTCST1996.pd

Blockwise Subspace Identification for Active Noise Control

In this paper, a subspace identification solution is provided for active noise control (ANC) problems. The solution is related to so-called block updating methods, where instead of updating the (feedforward) controller on a sample by sample base, it is updated each time based on a block of N samples. The use of the subspace identification based ANC methods enables non-iterative derivation and updating of MIMO compact state space models for the controller. The robustness property of subspace identification methods forms the basis of an accurate model updating mechanism, using small size data batches. The design of a feedforward controller via the proposed approach is illustrated for an acoustic duct benchmark problem, supplied by TNO Institute of Applied Physics (TNO-TPD), the Netherlands. We also show how to cope with intrinsic feedback. A comparison study with various ANC schemes, such as block filtered-U, demonstrates the increased robustness of a subspace derived controlle

Multivariable Adaptive Harmonic Steady-State Control for Rejection of Sinusoidal Disturbances Acting on an Unknown System

This paper presents an adaptive harmonic steady-state (AHSS) controller, which addresses the problem of rejecting sinusoids with known frequencies that act on a completely unknown multi-input multi-output linear time-invariant system. We analyze the stability and closed-loop performance of AHSS for single-input single-output systems. In this case, we show that AHSS asymptotically rejects disturbances.Comment: 6 pages, 2016 American Control Conference (ACC). IEEE, 201

Estimation-based synthesis of H∞-optimal adaptive FIR filtersfor filtered-LMS problems

This paper presents a systematic synthesis procedure for H∞-optimal adaptive FIR filters in the context of an active noise cancellation (ANC) problem. An estimation interpretation of the adaptive control problem is introduced first. Based on this interpretation, an H∞ estimation problem is formulated, and its finite horizon prediction (filtering) solution is discussed. The solution minimizes the maximum energy gain from the disturbances to the predicted (filtered) estimation error and serves as the adaptation criterion for the weight vector in the adaptive FIR filter. We refer to this adaptation scheme as estimation-based adaptive filtering (EBAF). We show that the steady-state gain vector in the EBAF algorithm approaches that of the classical (normalized) filtered-X LMS algorithm. The error terms, however, are shown to be different. Thus, these classical algorithms can be considered to be approximations of our algorithm. We examine the performance of the proposed EBAF algorithm (both experimentally and in simulation) in an active noise cancellation problem of a one-dimensional (1-D) acoustic duct for both narrowband and broadband cases. Comparisons to the results from a conventional filtered-LMS (FxLMS) algorithm show faster convergence without compromising steady-state performance and/or robustness of the algorithm to feedback contamination of the reference signal

Program of Research in Aeronautics

A prospectus of the educational and research opportunities available at the Joint Institute for Advancement of Flight Sciences, operated at NASA Langley Research Center in conjunction with George Washington University's School of Engineering and Applied Sciences is presented. Requirements of admission to various degree programs are given as well as the course offerings in the areas of acoustics, aeronautics, environmental modelling, materials science, and structures and dynamics. Research facilities for each field of study are described. Presentations and publications (including dissertations and theses) generated by each program are listed as well as faculty members visting scientists and engineers

Disturbance Rejection Using Self-Tuning ARMARKOV Adaptive Control with Simultaneous Identification

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/57807/1/HarshadSimultIDTCST2001.pd

Aeronautical Engineering. A continuing bibliography with indexes, supplement 156

This bibliography lists 288 reports, articles and other documents introduced into the NASA scientific and technical information system in December 1982