EP0665975A1 - Systeme de commande adaptatif - Google Patents

Systeme de commande adaptatif

Info

Publication number
EP0665975A1
EP0665975A1 EP93923590A EP93923590A EP0665975A1 EP 0665975 A1 EP0665975 A1 EP 0665975A1 EP 93923590 A EP93923590 A EP 93923590A EP 93923590 A EP93923590 A EP 93923590A EP 0665975 A1 EP0665975 A1 EP 0665975A1
Authority
EP
European Patent Office
Prior art keywords
signal
residual
signals
estimate
filter coefficients
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Ceased
Application number
EP93923590A
Other languages
German (de)
English (en)
Inventor
Ian Stothers
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Lotus Cars Ltd
Original Assignee
Lotus Cars Ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Lotus Cars Ltd filed Critical Lotus Cars Ltd
Publication of EP0665975A1 publication Critical patent/EP0665975A1/fr
Ceased legal-status Critical Current

Links

Classifications

    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10K—SOUND-PRODUCING DEVICES; METHODS OR DEVICES FOR PROTECTING AGAINST, OR FOR DAMPING, NOISE OR OTHER ACOUSTIC WAVES IN GENERAL; ACOUSTICS NOT OTHERWISE PROVIDED FOR
    • G10K11/00—Methods or devices for transmitting, conducting or directing sound in general; Methods or devices for protecting against, or for damping, noise or other acoustic waves in general
    • G10K11/16—Methods or devices for protecting against, or for damping, noise or other acoustic waves in general
    • G10K11/175—Methods or devices for protecting against, or for damping, noise or other acoustic waves in general using interference effects; Masking sound
    • G10K11/178—Methods or devices for protecting against, or for damping, noise or other acoustic waves in general using interference effects; Masking sound by electro-acoustically regenerating the original acoustic waves in anti-phase
    • G10K11/1785—Methods, e.g. algorithms; Devices
    • G10K11/17855—Methods, e.g. algorithms; Devices for improving speed or power requirements
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10K—SOUND-PRODUCING DEVICES; METHODS OR DEVICES FOR PROTECTING AGAINST, OR FOR DAMPING, NOISE OR OTHER ACOUSTIC WAVES IN GENERAL; ACOUSTICS NOT OTHERWISE PROVIDED FOR
    • G10K11/00—Methods or devices for transmitting, conducting or directing sound in general; Methods or devices for protecting against, or for damping, noise or other acoustic waves in general
    • G10K11/16—Methods or devices for protecting against, or for damping, noise or other acoustic waves in general
    • G10K11/175—Methods or devices for protecting against, or for damping, noise or other acoustic waves in general using interference effects; Masking sound
    • G10K11/178—Methods or devices for protecting against, or for damping, noise or other acoustic waves in general using interference effects; Masking sound by electro-acoustically regenerating the original acoustic waves in anti-phase
    • G10K11/1781—Methods or devices for protecting against, or for damping, noise or other acoustic waves in general using interference effects; Masking sound by electro-acoustically regenerating the original acoustic waves in anti-phase characterised by the analysis of input or output signals, e.g. frequency range, modes, transfer functions
    • G10K11/17813—Methods or devices for protecting against, or for damping, noise or other acoustic waves in general using interference effects; Masking sound by electro-acoustically regenerating the original acoustic waves in anti-phase characterised by the analysis of input or output signals, e.g. frequency range, modes, transfer functions characterised by the analysis of the acoustic paths, e.g. estimating, calibrating or testing of transfer functions or cross-terms
    • G10K11/17817—Methods or devices for protecting against, or for damping, noise or other acoustic waves in general using interference effects; Masking sound by electro-acoustically regenerating the original acoustic waves in anti-phase characterised by the analysis of input or output signals, e.g. frequency range, modes, transfer functions characterised by the analysis of the acoustic paths, e.g. estimating, calibrating or testing of transfer functions or cross-terms between the output signals and the error signals, i.e. secondary path
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10K—SOUND-PRODUCING DEVICES; METHODS OR DEVICES FOR PROTECTING AGAINST, OR FOR DAMPING, NOISE OR OTHER ACOUSTIC WAVES IN GENERAL; ACOUSTICS NOT OTHERWISE PROVIDED FOR
    • G10K11/00—Methods or devices for transmitting, conducting or directing sound in general; Methods or devices for protecting against, or for damping, noise or other acoustic waves in general
    • G10K11/16—Methods or devices for protecting against, or for damping, noise or other acoustic waves in general
    • G10K11/175—Methods or devices for protecting against, or for damping, noise or other acoustic waves in general using interference effects; Masking sound
    • G10K11/178—Methods or devices for protecting against, or for damping, noise or other acoustic waves in general using interference effects; Masking sound by electro-acoustically regenerating the original acoustic waves in anti-phase
    • G10K11/1785—Methods, e.g. algorithms; Devices
    • G10K11/17853—Methods, e.g. algorithms; Devices of the filter
    • G10K11/17854—Methods, e.g. algorithms; Devices of the filter the filter being an adaptive filter
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10K—SOUND-PRODUCING DEVICES; METHODS OR DEVICES FOR PROTECTING AGAINST, OR FOR DAMPING, NOISE OR OTHER ACOUSTIC WAVES IN GENERAL; ACOUSTICS NOT OTHERWISE PROVIDED FOR
    • G10K11/00—Methods or devices for transmitting, conducting or directing sound in general; Methods or devices for protecting against, or for damping, noise or other acoustic waves in general
    • G10K11/16—Methods or devices for protecting against, or for damping, noise or other acoustic waves in general
    • G10K11/175—Methods or devices for protecting against, or for damping, noise or other acoustic waves in general using interference effects; Masking sound
    • G10K11/178—Methods or devices for protecting against, or for damping, noise or other acoustic waves in general using interference effects; Masking sound by electro-acoustically regenerating the original acoustic waves in anti-phase
    • G10K11/1787—General system configurations
    • G10K11/17879—General system configurations using both a reference signal and an error signal
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10K—SOUND-PRODUCING DEVICES; METHODS OR DEVICES FOR PROTECTING AGAINST, OR FOR DAMPING, NOISE OR OTHER ACOUSTIC WAVES IN GENERAL; ACOUSTICS NOT OTHERWISE PROVIDED FOR
    • G10K2210/00—Details of active noise control [ANC] covered by G10K11/178 but not provided for in any of its subgroups
    • G10K2210/30—Means
    • G10K2210/301—Computational
    • G10K2210/3025—Determination of spectrum characteristics, e.g. FFT
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10K—SOUND-PRODUCING DEVICES; METHODS OR DEVICES FOR PROTECTING AGAINST, OR FOR DAMPING, NOISE OR OTHER ACOUSTIC WAVES IN GENERAL; ACOUSTICS NOT OTHERWISE PROVIDED FOR
    • G10K2210/00—Details of active noise control [ANC] covered by G10K11/178 but not provided for in any of its subgroups
    • G10K2210/30—Means
    • G10K2210/301—Computational
    • G10K2210/3045—Multiple acoustic inputs, single acoustic output
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10K—SOUND-PRODUCING DEVICES; METHODS OR DEVICES FOR PROTECTING AGAINST, OR FOR DAMPING, NOISE OR OTHER ACOUSTIC WAVES IN GENERAL; ACOUSTICS NOT OTHERWISE PROVIDED FOR
    • G10K2210/00—Details of active noise control [ANC] covered by G10K11/178 but not provided for in any of its subgroups
    • G10K2210/30—Means
    • G10K2210/301—Computational
    • G10K2210/3046—Multiple acoustic inputs, multiple acoustic outputs
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10K—SOUND-PRODUCING DEVICES; METHODS OR DEVICES FOR PROTECTING AGAINST, OR FOR DAMPING, NOISE OR OTHER ACOUSTIC WAVES IN GENERAL; ACOUSTICS NOT OTHERWISE PROVIDED FOR
    • G10K2210/00—Details of active noise control [ANC] covered by G10K11/178 but not provided for in any of its subgroups
    • G10K2210/30—Means
    • G10K2210/301—Computational
    • G10K2210/3057—Variation of parameters to test for optimisation
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10K—SOUND-PRODUCING DEVICES; METHODS OR DEVICES FOR PROTECTING AGAINST, OR FOR DAMPING, NOISE OR OTHER ACOUSTIC WAVES IN GENERAL; ACOUSTICS NOT OTHERWISE PROVIDED FOR
    • G10K2210/00—Details of active noise control [ANC] covered by G10K11/178 but not provided for in any of its subgroups
    • G10K2210/50—Miscellaneous
    • G10K2210/503—Diagnostics; Stability; Alarms; Failsafe

Definitions

  • the present invention relates to an adaptive control system and method for reducing undesired primary signals generated by a primary source of signals.
  • the basic principle of adaptive control is to monitor the primary signals and produce a cancelling signal which interfers destructively with the primary signals in order to reduce them.
  • the degree of success in cancelling the primary signals is measured to adapt the cancelling si r gnal to increase the reduction in the undesired primary signals.
  • This idea is thus applicable to any signals such as electrical signals within an electrical circuit in which undesired noise is produced.
  • One particular area which uses such adaptive control is in the reduction of unwanted acoustic vibrations in a region.
  • acoustic vibration applies to any acoustic vibration including sound.
  • WO88/02912 also discloses the operation of a digital filter in the frequency domain.
  • a digital filter has complex filter coefficients and requires the reference signal and error signals to be transformed into the frequency domain and the output drive signal from the adaptive filter to be inverse transformed back to the time domain in order to provide the drive signal.
  • the transform which is conveniently used is the Fourier transform.
  • a number of data points within a window length are transformed and used to adapt the following window of data.
  • Such a discrete Fourier transform provides good control if the length of the window (or number of data points) is long, but this provides a long delay in the update.
  • a short window of data on the other hand provides for a quick adaption but poor control.
  • the present invention provides an adaptive control system for reducing undesired signals, comprising signal means to provide at least one first signal indicative of at least selected undesired signals; processing means adapted to use said at least one first signal to provide at least one secondary signal to interfere with the undesired signals; and residual means to provide for said processing means at least one residual signal indicative of the interference between said undesired and secondary signals; wherein said processing means is adapted to transform said at least one first signal and said at least one residual signal to provide the amplitude and phase of spectral components of said signals, to collate the transformed signals, to inverse transform of the outcome of said collation, and to adjust the or each secondary signal using the inverse transform of the outcome of the collation to reduce said at least one residual signal.
  • said processing means comprises adaptive response filter means having filter coefficients and adapted to adjust the or each secondary signal using said filter coefficients to reduce the or each residual signals, and to modify the filter coefficients using said inverse transform of the outcome of the collation.
  • said processing means is adapted to collate said transformed signals by forming at least one cross spectral estimate, to inverse transform said at least one cross spectral estimate, to form at least one cross correlation estimate and to modify the filter coefficients of said adaptive response filter using said at least one cross correlation estimate.
  • the processing means is adapted to digitally sample said at least one first signal and said at least one residual signal, and to store a plurality of digits for each said signal to form first signal data blocks and residual signal data blocks respectively, said first signal data blocks and said residual signal data blocks being time aligned; said processing means being further adapted to set a number of said digits at the end of each first signal data block to zero to form a modified first signal data block, and to transform the modified first signal data block and the associated residual signal data block to use in the collation.
  • each modified first signal data block which is set to zero depend on the delay between the first signal and the contribution from the first signal in the residual signal.
  • the number of digits set to zero are preferably selected such that the time taken to sample said number is greater than the delay experienced by a signal passing through said adaptive response filter.
  • the cross spectral estimate is formed by multiplying the complex conjugate of the transform of the first signal with the transform of the residual signal.
  • the transform performed on the first signal and the residual signal is the Fourier transform although any transform could be used in which the cross talk between frequencies is minimal or non-existent.
  • the cross spectral estimate is multiplied with a convergence coefficient which is sufficiently small to smooth out the effect of random errors in the cross spectral estimate on the adaption.
  • the cross correlation estimate is multiplied with a convergence coefficient sufficiently small to smooth out the effect of random errors in the cross correlation estimate on the adaption.
  • the processing means includes system response filter means to model the response of the signals from said residual means to at least one secondary signal.
  • said system response filter means preferably comprises complex filter coefficients which are an estimate of the frequency response of said residual signals to at least one said secondary signals, and said processing means is adapted to filter the transform of said at least one first signal using said complex filter coefficients.
  • the processing means includes system response filter means which comprises complex filter coefficients which are an estimate of the amplitude and an estimate of the inverse of the phase of the frequency response of said residual signals to at least one secondary signal, and said processing means is adapted to filter the transform of said at least one residual signal using said complex filter coefficients.
  • the processing means is adapted to modify said filter coefficients to reduce the amplitude of portions of the or each drive signal by a predetermined amount.
  • This action on the filter coefficients can be termed "effort weighting" and is used to control the stability of the adaptive response filter.
  • said residual means provides a plurality of residual signals and said processing means is adapted to modify said filter coefficients of said adaptive response filter to reduce the sum of the mean of the square of the residual signals.
  • said adaptive control system comprises at least one secondary vibration source responsive to said at least one secondary signal to provide secondary vibrations to interfere with said undesired acoustic vibrations; said residual means comprising at least one sensor means to sense the residual vibrations resulting from the interference between said undesired acoustic vibrations and said secondary vibrations and to provide said at least one residual signal.
  • the present invention also provides a method of actively reducing undesired signals, comprising the steps of providing at least one signal indicative of at least selected undesired signals using said at least one first signal to provide at least one secondary signal to interfere with said undesired signals; providing at least one residual signal indicative of the interference between said undesired and secondary signals; transforming said at least one first signal and said at least one residual signal to provide the amplitude and phase of spectral components of said signals, collating the transformed signals; inverse transforming the outcome of the collation and using the inverse transform of the output of the collation to adapt the or each secondary signal to reduce the residual signals.
  • the present invention provides an adaptive control system for reducing undesired signals, comprising signal means to provide at least one first signal indicative of at least selected undesired signals; processing means adapted to use said at least one first signal to provide at least one secondary signal to interfere with the undesired signals; and residual means to provide for said processing means at least one residual signal indicative of the interference between said undesired and secondary signals; wherein said processing means is adapted to digitally sample said at least one first signal and said at least one residual signal; to store a plurality of digits for each said signal to form first signal and residual signal data blocks respectively, said first signal data blocks and said residual signal data blocks being time aligned; to set a number of said digits at the end of each first signal data block to zero to form a modified first signal data block, to transform the modified first signal data block and the residual signal data block to provide the amplitude and phase of spectral components of said signals, and to adjust the amplitude and phase of spectral components of said at least one secondary signal using said transformed signals to
  • the present invention provides a method of actively reducing undesired signals comprising the steps of providing at least one first signal indicative of at least selected undesired signals; using said at least one first signal to provide at least one secondary signal to interfere with said undesired signals; providing at least one residual signal indicative of the interference between said undesired and secondary signals; digitally sampling said at least one first signal and said at least one residual signal; storing a plurality of digits for each said signal to form first signal and residual signal data blocks, said first signal and residual signal data blocks being time aligned; setting a number of said digits at the end of each first signal data block to zero to form a modified first signal data block, transforming the modified first signal data block to provide the amplitude and phase of spectral components of said signals, and adjusting the amplitude and phase of spectral components of said at least one secondary signal using said transformed signals to reduce said at least one residual signal.
  • FIGS. la and lb illustrate schematically alternative adaptive control systems according to embodiments of the present invention.
  • Figure lc illustrates an expansion of the arrangement shown in Figure la for two reference signals
  • Figure Id illustrates an expansion of the arrangement shown in Figure la for two error sensors
  • Figure le illustrates an expansion of the arrangement shown in Figure la for two secondary vibration sources
  • Figure 2 illustrates the blocks of reference and error signal data used for the transform to form the cross spectral estimate
  • FIG. 3 is a schematic drawing of an active vibration control system for practical implementation.
  • FIGS 4a and 4b illustrate schematically frequency domain adaptive control systems in accordance with embodiments of the present invention.
  • FIGS. la and lb illustrate alternative adaptive control systems which can be used in accordance with the present invention.
  • FIGs la and lb illustrate a single channel system having a single reference signal x(n) which represents the signal from a sensor, and a single output y(n) from the w filter which represents the drive signal to a secondary vibration source.
  • e(n) represents the error signal indicative of the residual vibrations after interference between the primary and secondary vibrations.
  • the single channel system is shown for simplicity although the present invention is equally applicable to the multichannel system where the Fourier transform of each reference signal x(n) must be taken as well as the Fourier transform of each error signal e(n) .
  • A represents the acoustic response of the pathway from the primary source of vibrations (represented by the reference signal x(n)) and the location of interference with the drive signal (y(n) from the adaptive filter w) .
  • the reference signal x(n) is input into the adaptive response filter w and this signal is modified by filter coefficients of the w filter to provide the drive signal y(n) .
  • an estimate of C is used to modify the reference signal x(n) before it is input into the LMS algorithm.
  • the C coefficients provide a model of the delay and reverberant response of the system.
  • the coefficients of the adaptive response filter w should be adjusted at every sample in the time domain according to the following equation:
  • w mi (n+l) Hmi(n) + ⁇ ⁇ e (n)r . (n-i)
  • £ 1 x ⁇
  • ⁇ is a convergence coefficient e ⁇ (n) is the sampled output from the £ sensor r m (n) is a sequence formed by filtering the reference signal x(n) by C which models the response of the £ sensor to the output of the m secondary vibration source.
  • each reference signal to be filtered by a filter which has coefficients for all the paths between the secondary vibrations sources and the sensors.
  • the update required for the w coefficients is determined in the frequency domain and implemented in the time domain. This is achieved by taking the Fourier transform of the reference signal x(n) and the error signal e(n). The Fourier transform of the error signal E v is then convolved with the complex conjugate of the Fourier transform of the reference signal X. to form a cross spectral estimate. The inverse Fourier transform of this cross spectral estimate is then taken to form a cross correlation estimate. The causal part of the cross correlation estimate is then used to update the coefficients of the adaptive response filter w.
  • X. represents a vector of complex values of the
  • the C matrix contains the transfer functions or a model of the amplitude and phase change applied to each drive signal as detected by each sensor, whereas the conjugate of the C matrix represents a model of the amplitude and the inverse of the phase.
  • Figure lb illustrates an alternative active vibration control system according to one embodiment of the present invention.
  • the only difference is in the position of the estimate of C.
  • the Fourier transform of the reference signal is multiplied by the matrix of transfer functions C.
  • the cross spectral estimate is then formed by taking the complex conjugate of the result of passing the Fourier transform of the reference signal through the C filter and multiplying this complex conjugate with the Fourier transform of the error signal.
  • the cross correlation estimate is multiplied by a convergence coefficient ⁇ in order to compensate for random errors.
  • the computational efficiency for the single channel system is the same as that of the arrangement shown in Figure la.
  • This control system also benefits from forming the cross correlation estimate by firstly forming the cross spectral estimate.
  • the arrangement shown in Figure lb is equally as computationally efficient as the arrangement shown in Figure la.
  • the computational efficiency of the arrangement shown in lb compared to the arrangement shown in Figure la decreases since it is approximately proportional to (log 2 N x N) x (No. of references x No. of error sensors x No. of secondary vibration sources) .
  • the number of filtering operations that must be carried out by the transfer function C is increased by a factor which is the number of reference signals.
  • FIGS. lc, d and e are multichannel versions of the single channel system shown in Figure la.
  • a multichannel system of the model shown in Figure lb can be built up in a like manner to that shown in Figures lc, d and e as would be evident to a skilled person in the art.
  • the algorithm reduces the noise by reducing the sum of the mean of the square of the error signals in a similar manner to that disclosed in WO88/02912.
  • the filter coefficients can be modified to reduce the amplitude of portions of the drive signals by a predetermined amount. This is termed "effort weighting" and can increase the stability of the algorithm as well as allow for selection of the effort taken to converge for signals of different delays or different frequencies dependent upon whether the filter coefficients are weighted in the time or frequency domain.
  • the delay contributions from the n data point in the reference signal would not be measured. This reduces the possibility of convergence of the algorithm.
  • This problem is overcome by taking a block or window of data having n data points where the last few p data points are set to zero.
  • the block of data has a length of 0 to n but only the data points 0 to n-p contain actual reference signal data.
  • the number p of data points which are set to zero is dependent on the number of tap delays of the w filter.
  • the number p should be set to be at least the same number if not greater than the number of taps in the w filter.
  • Figure 2 illustrates the two data blocks for the reference and error signals. These blocks of data are used for the fast Fourier transform and this method ensures that all contributions from the reference signal data points are found in the error signal data block.
  • the data blocks or windows represent "snap shots" in time of the reference and error signals. There is no requirement for these data blocks to be taken end to end. Blocks of data can be taken at intervals of time. If the intervals between the acquisition of the data blocks is large then clearly the adaption of the coefficients of the w filter will be slow in response to rapidly changing conditions. However, for many practical applications the update of the coefficients of the w filter need not take place rapidly.
  • the output drive signals to provide the secondary vibrations are not delayed. Only the modification of the filter coefficients of the w filter are delayed.
  • Figure 3 illustrates the construction of a practical active vibration control system for use in a motor vehicle.
  • Figure 3 illustrates a multichannel system with four reference signal generators 31, four error sensors 42 and two secondary vibration sources 37.
  • the present invention is particularly suited to a multichannel system having more than one reference signal since this provides for the greatest computational saving.
  • the reference signal generators 31 comprise four transducers such as accelerometers placed on the suspension of the vehicle. These transducers provide signals indicative of the vibrational noise transmitted from the road wheel to the vehicle cabin.
  • the outputs of the transducers 31 are amplified by the amplifiers 32 and low pass filtered by the filters 33 in order to avoid aliasing.
  • the reference signals are then multiplexed by the multiplexer 34 and digitised using the analogue digital converter 35. This provides reference signals x.(n) to the processor 36 which is provided with memory 61.
  • Four error sensors 42 are provided within the vehicle cabin at space locations such as around the headlining. These microphones 42. through 42. detect the noise within the cabin.
  • the output of the microphones 42 is then amplified by the amplifiers 43 and low pass filtered by the low pass filters 44 in order to avoid aliasing.
  • the output of the low pass filters 44 is then multiplexed by the multiplexer 45 before being digitised by the analogue to digital converter 46.
  • the output of the analogue digital converter e, (n) is then input into the processor 36.
  • Drive signals y_(n) are output from the processor 36 and converted to an analogue signal by the digital to analogue converter 41.
  • the output of the analogue to digital converter 41 is then demultiplexed by the demultiplexer 38.
  • the demultiplexer 38 separates the drive signals into separate drive signals for passage through low pass filters 39 in order to remove high frequency digital sampling noise.
  • the signal is then amplified by the amplifiers 40 and output to the secondary vibration sources 37- and 37 which comprise loudspeakers provided within the cabin of the vehicle.
  • the loudspeakers can comprise the loudspeakers of the in-car entertainment system of the vehicle. In such an arrangement the drive signals are mixed with the in-car entertainment signals for output by the loudspeakers, as is disclosed in GB 2252657.
  • the processor is provided with the reference signals x ⁇ n) and the error signals e, (n) and outputs the drive signals Y m (n) and is adapted to perform the algorithm as hereinbefore described.
  • FIG 3 shows the processor receiving a clock signal 60 from a sample rate oscillator 47.
  • the processor thus operates at a fixed frequency related to the frequencies of the vibrations to be reduced only by the requirement to meet Nyquist's criterion.
  • the processor 36 can be a fixed point processor such as the TMS 320 C50 processor available from Texas Instruments. Alternatively, the floating point processor TMS 320 C30 also available from Texas Instruments can be used to perform the algorithm.
  • the system shown in Figure 3 illustrates a system for cancelling road noise transmitted from the road wheel of a vehicle
  • the system can also be used for cancelling engine noise where a reference signal is provided indicative of the noise generated by the engine of a vehicle.
  • a reference signal is provided indicative of the noise generated by the engine of a vehicle.
  • only a single reference signal is required and although the full potential computational saving of the algorithm is not utilised, the computational requirement is still reduced compared to the conventional time domain algorithm.
  • Figures 4a and 4b illustrate other embodiments of the present invention. In these embodiments adaption is performed in the frequency domain.
  • Figures 4a and 4b differ from Figures la and lb in that the w filter coefficients are complex and require the input to the w filter to be the transform of the reference signal. Also, there is no need to inverse transform the cross spectral estimate to modify the complex filter coefficients. The output of the w filter must be inverse transformed to generate the drive signal y(n) since the w filter acts on the amplitude and phase of spectral components.
  • the present invention applies to the reduction of any undesired signals.
  • a signal indicative of at least selected undesired vibrations from a vibration source is used to provide a drive signal to cancel the undesired vibrations at a location.
  • the degree of success in reducing the undesired vibrations is measured to provide a residual signal and this is used to adjust the drive signal to provide better cancellation.
  • the undesired signals being cancelled could be electrical or acoustic.

Abstract

Un système de commande adaptatif destiné à réduire des signaux de commande non désirés comporte des détecteurs (31) afin de générer des signaux, et un processeur (36) qui traite le premier signal pour envoyer un signal secondaire vers les sources (37) afin d'interférer avec les signaux non désirés. Des détecteurs (42) sont prévus pour détecter les signaux résiduels indicateurs de l'interférence entre les signaux non désirés et les signaux secondaires. A l'intérieur de l'unité de traitement, les signaux indicateurs des signaux non désirés et des signaux résiduels sont transformés dans le domaine de fréquence et interclassés. On calcule la transformée inverse du résultat de l'interclassement et le processeur règle le signal secondaire à l'aide de cette transformée inverse afin de réduire le signal résiduel émis par les détecteurs (42).
EP93923590A 1992-10-21 1993-10-21 Systeme de commande adaptatif Ceased EP0665975A1 (fr)

Applications Claiming Priority (3)

Application Number Priority Date Filing Date Title
GB9222102 1992-10-21
GB9222102A GB2271908B (en) 1992-10-21 1992-10-21 Adaptive control system
PCT/GB1993/002170 WO1994009481A1 (fr) 1992-10-21 1993-10-21 Systeme de commande adaptatif

Publications (1)

Publication Number Publication Date
EP0665975A1 true EP0665975A1 (fr) 1995-08-09

Family

ID=10723808

Family Applications (1)

Application Number Title Priority Date Filing Date
EP93923590A Ceased EP0665975A1 (fr) 1992-10-21 1993-10-21 Systeme de commande adaptatif

Country Status (4)

Country Link
EP (1) EP0665975A1 (fr)
JP (1) JPH08502594A (fr)
GB (1) GB2271908B (fr)
WO (1) WO1994009481A1 (fr)

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GB9414484D0 (en) * 1994-07-18 1994-09-21 Marconi Gec Ltd An apparatus for cancelling vibrations
DE4432532A1 (de) * 1994-09-13 1996-03-14 Stn Atlas Elektronik Gmbh Verfahren zur Befreiung von Körperschallstörungen
GB2293898B (en) * 1994-10-03 1998-10-14 Lotus Car Adaptive control system for controlling repetitive phenomena
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GB2271908A (en) 1994-04-27
GB2271908B (en) 1996-05-15
GB9222102D0 (en) 1992-12-02
JPH08502594A (ja) 1996-03-19
WO1994009481A1 (fr) 1994-04-28

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