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EP0647372B1 - Steuerungssystem mit harmonischen filtern - Google Patents

Steuerungssystem mit harmonischen filtern Download PDF

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Publication number
EP0647372B1
EP0647372B1 EP92914435A EP92914435A EP0647372B1 EP 0647372 B1 EP0647372 B1 EP 0647372B1 EP 92914435 A EP92914435 A EP 92914435A EP 92914435 A EP92914435 A EP 92914435A EP 0647372 B1 EP0647372 B1 EP 0647372B1
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Prior art keywords
signal
harmonic
input signal
signals
complex
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French (fr)
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EP0647372A4 (de
EP0647372A1 (de
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Graham Eatwell
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Noise Cancellation Technologies Inc
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Noise Cancellation Technologies Inc
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Priority to AT92914435T priority Critical patent/ATE180604T1/de
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    • 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
    • G10K11/17821—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 input signals only
    • G10K11/17823—Reference signals, e.g. ambient acoustic environment
    • 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
    • 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
    • G10K11/17883—General system configurations using both a reference signal and an error signal the reference signal being derived from a machine operating condition, e.g. engine RPM or vehicle speed
    • 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
    • G10K2210/10—Applications
    • G10K2210/121—Rotating machines, e.g. engines, turbines, motors; Periodic or quasi-periodic signals in general
    • 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
    • G10K2210/3028—Filtering, e.g. Kalman filters or special analogue or digital filters
    • 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
    • G10K2210/3032—Harmonics or sub-harmonics
    • 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
    • G10K2210/3051—Sampling, e.g. variable rate, synchronous, decimated or interpolated
    • 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
    • G10K2210/512—Wide band, e.g. non-recurring signals

Definitions

  • the invention relates to a method for obtaining the amplitudes of an input signal with varying fundamental frequency according to claim 1, a method for active cancellation of substantially period disturbances according to claim 6, a harmonic filter means according to claim 8 and an active control system using the harmonic filter means of claim 8.
  • the approaches differ in the way the controller output is obtained and adjusted.
  • the output is generated by filtering reference signals.
  • the amplitude and phase of each signal is adjusted in the time domain by a variable filter as in Swinbanks, while in the other approach the controller output is updated in the frequency domain using the Discrete Fourier Transform of the residual signal as in Chaplin for varying frequencies, and for fixed frequencies in "Adaptive Filtering in the Frequency Domain” by Dentino et al, IEEE Proceedings, Vol 69, No. 12, pages 474-75 (1978).
  • the first approach can be implemented digitally by using a frequency sampling filter followed by a two-coefficient FIR filter or by using a frequency sampling filter followed by a Hilbert transformer and two single coefficient filters.
  • the Fourier Transform approach of Chaplin has the advantage of being able, in the simplest case, to update the coefficients in a single step.
  • the coefficients of the two point filter, described by Bitmead and Anderson and others, are not independent so they cannot be updated in a single step using the simple LMS algorithm.
  • synchronous sampling has two disadvantages. Firstly, the anti-aliasing and smoothing filters must be set to cope with the slowest sampling rate. Since the upper control frequency is fixed, a large number of points may be required per cycle. Secondly, because of the varying sample rate, continuous system identification is complicated.
  • This invention relates to a harmonic filter, and its use as part of a control system.
  • the harmonic filter is shown in Figure 1. It consists of a pair of multipliers and low-pass filters.
  • the input signal is multiplied by sinusoidal signals at the frequency of the harmonic component to be identified.
  • the resulting signals are passed through the low-pass filters.
  • the output from the low-pass filters are estimates of the real and imaginary parts of the desired complex harmonic amplitude.
  • the phase of the sinusoidal signal is determined from a phase signal (from a tachometer or a phase locked loop for example) or from integrating a frequency signal.
  • the bandwidth of the low-pass filter is variable and is determined by the fundamental frequency of the input signal.
  • sensors are used to provide signals indicative of the performance of the system. These signals are sent to harmonic filters and the complex output from the filters are used to adapt the controller output.
  • harmonic filters are combined with output processors and an adaptive controller.
  • the output processor for one harmonic is shown in Figure 2.
  • the real and imaginary parts ofthe complex amplitude of the output are determined by the controller. These are then multiplied by sinusoidal signals and summed to provide one harmonic of the output signal.
  • the sinusoidal signals are the same as those used in the harmonic filters.
  • Each harmonic of the controller output is generated by an output processor (01, 02, 03,.7) which combines a complex amplitude, Y with sine and cosine signals.
  • the controller output is obtained by summing these components. If the controller is to be used as part of an active control system, this output is then converted to the required form and sent to an actuator which produces the canceling disturbance.
  • the input to the controller is a residual or error signal r(t).
  • r(t) is responsive to the combination of the original disturbance and the canceling disturbance as measured by a sensor.
  • the residual signal is then passed to one or more harmonic filters (HF1, HF2, HF3, «).
  • the harmonic components, (R1, R2, R3, Vietnamese), of this residual signal are then used to adjust the complex amplitudes, (Y1, Y2, Y3, across), of the output.
  • a steady state, periodic signal r(t) can be written as a sum of harmonic components where k is the harmonic number, K is the total number of harmonics in the signal, R k is the complex amplitude of the signal at the k-th harmonic, and ⁇ is the fundamental radian frequency.
  • the purpose of the harmonic filter is to determine the complex amplitudes R k .
  • R k is the discrete Fourier Transform of the signal.
  • the integral is calculated over a longer time to give the continuous Fourier transform.
  • the harmonic filter is designed to provide a real-time estimate of the harmonic components of a signal.
  • the basic approach is to multiply the signal by the appropriate cosine and sine values and then to low-pass filter the results.
  • This process shown in Figure 2, is equivalent to multiplying by a complex exponential signal, exp(ik ⁇ t), and then passing the result through a complex low-pass filter. The process is sometimes called heterodyning.
  • the multiplication by the complex exponential acts as demodulator, and the resulting signal has components at d.c. (zero frequency) and at twice the original frequency, for harmonic signals the harmonic frequencies are all shifted by +/- the frequency of the exponential signal, therefore the resulting signal may have components at the fundamental frequency. These must be filtered out to leave only the d.c. component.
  • the bandwidth of the filter With a fixed low-pass filter, the bandwidth of the filter must be set to cope with highest fundamental frequency likely to be encountered. When the system is operating at the lower frequencies, the low-pass filter is then much sharper than necessary, and therefore introduces much more delay than is necessary.
  • the bandwidth of the filter according to the current fundamental frequency it can be ensured that the harmonic filter has minimum delay. This is particularly important for use with control systems where any delay adversely affects the controller performance.
  • One way of implementing the low-pass filter is by a moving average process.
  • the period P is defined as the time taken for the phases to change by 2 ⁇ radians, i.e.
  • the method is complicated by the fact that the period P is not generally an exact number of samples. If the sampling rate is high enough compared to the frequency of the harmonic being identified the truncation error can be neglected and the integral approximated by using the M samples in the current cycle.
  • the estimate can be obtained using a Finite Impulse Response (FIR) filter with M+1 coefficients.
  • FIR Finite Impulse Response
  • the filter coefficients, W(n) are all unity except for the last one.
  • Both the length of the filter and the last coefficient of the filter are adjusted as the fundamental frequency of the noise changes.
  • Equation (5) can be calculated recursively, that is, the next estimate can be calculated from the current estimate by adding in the new terms and subtracting off the old terms.
  • R k ((m+1)T) (P m /2) .R k (mT) + X k (m+1) + (a M+1 - 1).
  • the filter is shown in Figure 5. It can be implemented in analog or sampled data form.
  • Another advantage is that a can be varied dynamically to reduce the integration time during transients.
  • the bandwidth of the filter In order to separate out the different harmonic components, the bandwidth of the filter must be adjusted as the fundamental frequency ofthe disturbance varies. Note that the bandwidth of the filter is varied according to the fundamental frequency, not the frequency ofthe harmonic being identified.
  • the low-pass filter is designed to have zeros in its frequency response at multiple fundamental frequency.
  • the exponential terms and sinusoidal terms used in the computation can be stored in a table.
  • the resolution of the table must be chosen carefully to avoid errors.
  • the exponential terms could be calculated at each output time, using interpolation from tabulated values, trigonometric identities or expansion formulae for example.
  • controller output varies on the same time scale as the output from the harmonic filters (see co-pending patent application [13]).
  • the outputs from the harmonic filters are used directly as inputs to a nonlinear control system.
  • controller output In active control systems the controller output must have a particular phase relative to the disturbance to be controlled. In this case some output processing is required, which is effectively an inverse heterodyner. One example of this is now described.
  • a constant rate is used for both input sampling and output.
  • the sampling period is denoted by T.
  • the output at time nT which is calculated by the output processor, is where ⁇ is the fundamental radian frequency, Re denotes the real part and Im denotes the imaginary part, and where k is the harmonic number, K is the total number of harmonics in the signal and Y is the complex amplitude ofthe output at the appropriate harmonic.
  • the values Y k can be stored in memory and the output calculated at each output time, as described by Ziegler.
  • the output processor uses the same sine and cosine terms as the input heterodyner.
  • the algorithms for adjusting the output values Y require knowledge of the harmonic components of the residual or error signal. These are provided by the outputs from the harmonic filters.
  • the known frequency domain adaptive algorithms can be used to update the complex amplitudes of the output.
  • R n -1 k where Y n / k is the vector of outputs at the n-th update and the k-th harmonic, R k is vector of residual components, ⁇ is the convergence step size, ⁇ is a leak applied to the output coefficients and B( ⁇ ) is a complex matrix related to the system transfer function matrix at the current frequency of this harmonic.
  • ⁇ can be a complex matrix related to A( ⁇ ) and B( ⁇ ).
  • a pseudo-inverse form is preferred since it allows the harmonic components to converge at equal rates - which is one of the main advantages of frequency domain algorithms. It is also preferred for multichannel systems since it allows for various spatial modes of the system to converge at a uniform rate.
  • the convergence step sizes for the algorithms which update at every sample are determined by the response time of the whole system. This is the settling time of the physical system (the time taken for the system to reach a substantially steady state) plus a variable delay due to the low-pass filter.
  • the constant ⁇ in (12) must be replaced by frequency dependent parameter, ⁇ ( ⁇ ). This parameter must take account of the effective delay in variable filter.
  • the constant ⁇ can also be replaced by a frequency dependent parameter ⁇ ( ⁇ ). This parameter can be adapted to limit the amplitude of the output.
  • the adaption process is performed every sample interval or at a rate determined by the cycle length (fundamental period) of the noise.
  • the first approach has the disadvantage that the sampling rate and/or the number of harmonics to be controlled is limited by the processing power of the controller.
  • the second approach has the disadvantage the computational requirements vary with the frequency, which may not be known in advance, and also the adaption rate is limited by the fundamental period of the disturbance.
  • the harmonic components are available every sample and the controller output is calculated every sample, but the adaption process can be performed at a slower rate if required.
  • this slower rate is determined in advance to be a fixed fraction of the sampling rate, in another embodiment of the invention the adaption is performed as a background task by the processor. This ensures that optimal use is made of the available processing power.
  • the sampled data control systems described above use constant sampling rates. This facilitates the use of on-line system identification techniques to determine the system impulse response (and hence it transfer function matrix). Some of these techniques are well known for time domain control systems. Tretter describes some techniques for multichannel periodic systems.
  • a random (uncorrelated) test signal is added to the controller output after the output processor but before the Digital to Analog Converter (DAC).
  • the response at each sensor is then measured before the heterodyner, but after the Analog to Digital Converter (ADC).
  • ADC Analog to Digital Converter
  • This response is then correlated with the test signal to determine a change to the relevant impulse response.
  • the correlation is estimated from a single sample.
  • FIG. 6 One embodiment of the scheme is shown in Figure 6. This can be extended to multichannel system by applying the test signal to each actuator in turn or by using a different (uncorrelated) test signals for each actuator and driving all actuators simultaneously.
  • the plant in Figure 6 includes the DAC, smoothing filter, power amplifier, actuator, physical system, sensor, signal conditioning, anti-aliasing filter and ADC.

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  • Physics & Mathematics (AREA)
  • Engineering & Computer Science (AREA)
  • Acoustics & Sound (AREA)
  • Multimedia (AREA)
  • Soundproofing, Sound Blocking, And Sound Damping (AREA)
  • Networks Using Active Elements (AREA)
  • Feedback Control In General (AREA)

Claims (17)

  1. Verfahren zum Erhalten von Amplituden (Y) eines Eingangssignales (r(t)) mit sich ändernder Fundamentalfrequenz, dadurch gekennzeichnet, daß die komplexen harmonischen Amplituden (Y) eines Eingangssignales (r(t)) bestimmt werden, indem das Eingangssignal mit einem Paar orthogonaler Sinusschwingungssignale (SIN(K,PH1); COS(K,PH1)) bei der Frequenz einer jeden harmonischen Schwingungskomponente, die identifiziert werden soll, multipliziert wird, und daß die resultierenden Signale durch Tiefpaß-Filter (HF) mit variabler Bandbreite gesendet werden, um Abschätzungen für die Real- und Imaginärteile der gewünschten komplexen harmonischen Schwingungsamplitude (Y) bereitzustellen.
  2. Verfahren nach Anspruch 1, dadurch gekennzeichnet, daß die Bandbreiten der Tiefpaß-Filter (HF) von der Fundamentalfrequenz des Signales (r(t)) abhängen.
  3. Verfahren nach Anspruch 2, dadurch gekennzeichnet, daß die Fundamentalfrequenz durch Messen der Fundamentalfrequenz der Quelle des Eingangssignales (r(t)) erhalten wird.
  4. Verfahren nach Anspruch 1, dadurch gekennzeichnet, daß die Phase der Quelle des Eingangssignales (r(t)) gemessen wird und dazu verwendet wird, die Phase der Sinusschwingungssignale zu bestimmen.
  5. Verfahren nach Anspruch 4, bei dem die Phase der Quelle des Eingangssignales (r(t)) erhalten wird, indem ein Signal (w) integriert wird, welches für die Frequenz der Quelle des Eingangssignales (r(t)) repräsentativ ist.
  6. Verfahren zur aktiven Unterdrückung von im wesentlichen periodischen Störungen, welches das Multiplizieren des Eingangssignales (r(t)) mit einem Signal umfaßt, das die Frequenz (w) des zu identifizierenden Signales aufweist, dadurch gekennzeichnet, daß
    die Überlagerung der anfänglichen Störung und der Gegenstörung erfaßt wird, um ein Eingangssignal (r(t)) zu erhalten,
    das Eingangssignal mit Paaren von orthogonalen Sinusschwingungssignalen (SIN(K,PH1);COS(K,PH1)) bei der Frequenz der zu identifizierenden Komponenten multipliziert wird,
    die resultierenden Signale durch Tiefpaß-Filter (HF) mit variabler Bandbreite gesendet werden, um komplexe Restsignale (R) bereitzustellen, welche Abschätzungen für die Real- und Imaginärteile der komplexen harmonischen Amplituden (Y) des Eingangssignales darstellen,
    diese komplexen Restsignale (R) dazu verwendet werden, die komplexen Amplituden eines Ausgangssignales anzupassen,
    die Real- und Imaginärteile der komplexen Amplituden (Y) dieses Ausgangssignales mit den Sinusschwingungssignalen multipliziert und
    aufsummiert werden, um das Ausgangssignal zu erzeugen, was bewirkt, daß das Ausgangssignal eine Gegenstörung hervorruft, welche mit der ursprünglichen Störung überlagert wird.
  7. Verfahren nach Anspruch 6, dadurch gekennzeichnet, daß die Phase der Quelle des Eingangssignales (r(t)) gemessen und dazu verwendet wird, die Phase der Sinusschwingungssignale (SIN(K,PH1);COS(K,PH1)) zu bestimmen.
  8. Harmonisches Filtermittel zum Erzeugen von Sinusschwingungssignalen mit der Frequenz, die der Frequenz des zu identifizierenden Signales entspricht, welches ein Multipliziermittel zum Multiplizieren des Eingangssignales (r(t)) mit den Sinusschwingungssignalen enthält, um ein Signal (R) zu erzeugen, welches gefiltert wird, dadurch gekennzeichnet, daß
    das Filtermittel (HF) ein Tiefpaß-Filtermittel mit variabler Bandbreite umfaßt, das dazu dient, die ersten Signale (R) zu filtern, um zweite Signale bereitzustellen, welche auf die Real- und Imaginärteile der gewünschten komplexen harmonischen Amplituden (Y) bezogen sind,
    das erzeugte Sinusschwingungssignal in einem Paar orthogonaler Sinusschwingungssignale (SIN) (K,PH1);COS(K,PH1)) mit der Frequenz der harmonischen, zu identifizierenden Komponenten besteht,
    die Bandbreiten des Tiefpaß-Filters von der Fundamentalfrequenz (w) des Signals abhängen.
  9. Aktives Steuersystem zum Unterdrücken von im wesentlichen periodischen Störungen mit
    Sensormitteln um die Überlagerung der ursprünglichen Störung und der Gegenstörung zu erfassen, um ein Eingangssignal (r(t)) zu erhalten, dadurch gekennzeichnet, daß
    es zusätzlich dem Anspruch 8 entsprechende harmonische Filtermittel enthält, um komplexe Restsignale (R) zu erzeugen, welche Abschätzungen für die Real- und Imaginärteile der komplexen harmonischen Amplituden (Y) des Eingangssignales (r(t)) bei den zu steuernden Frequenzen darstellen,
    in ihm ein Anpassungsmittel vorgesehen ist, welches die komplexen Restsignale (R) dazu verwendet, die komplexen Amplituden (Y) eines Ausgangssignales an Ausgangssignalverarbeitungsmittel (01, 02, 03) anzupassen, welche dazu dienen, die Real- und Imaginärteile dieser komplexen Amplituden (Y) mit Sinusschwingungssignalen (SIN(K,PH1);COS(K,PH1)) zu multiplizieren und aufzuaddieren, um die Ausgangssignale bereitzustellen,
    in ihm ein Gebermittel vorgesehen ist, um eine Gegenstörung zu erzeugen, welche der ursprünglichen Störung überlagert wird.
  10. Steuersystem nach Anspruch 9, dadurch gekennzeichnet, daß es ein zweites Sensormittel zum Bestimmen eines Phasensignales enthält, welches mit der Phase der Quelle des Eingangssignales (r(t)) verknüpft ist und in dem das Phasensignal dazu verwendet wird, die Phase der Sinusschwingungssignale (SIN(K,PH1);COS(K,PH1)) zu bestimmen.
  11. Steuersystem nach Anspruch 9, dadurch gekennzeichnet, daß von dem harmonischen Filtermittel (HF), dem Anpassungsmittel oder den Mitteln zum Erzeugen von Ausgangssignalen (01, 02, 03) wenigstens eines ein System für abgetastete Daten (sampled data system) darstellt.
  12. Steuersystem nach Anspruch 9, dadurch gekennzeichnet, daß von dem harmonischen Filtermittel (HF), dem Anpassungsmittel oder den Mitteln zum Erzeugen von Ausgangssignalen (01, 02, 03) wenigstens eines einen analogen Schaltkreis darstellt.
  13. Steuersystem nach Anspruch 9, dadurch gekennzeichnet, daß das Anpassungsmittel einen digitalen Prozessor darstellt, in dem die Schrittweite des Anpassungs-Algorithmus wenigstens teilweise durch die Fundamentalfrequenz der Störung bestimmt wird.
  14. Steuersystem nach Anspruch 9, dadurch gekennzeichnet, daß das Anpassungsmittel einen analogen Schaltkreis darstellt, welcher eine Rückkopplungsschleife bildet und in dem die Verstärkung der Rückkopplungsschleife wenigstens teilweise durch die Fundamentalfrequenz der Störung bestimmt wird.
  15. Steuersystem nach Anspruch 9, dadurch gekennzeichnet, daß das harmonische Filtermittel (HF) und die Anpassungsmittel (01, 02, 03) von einem oder mehreren digitalen Prozessoren gebildet werden und daß in diesen der Anpassungsvorgang als ein Hintergrund-Rechenvorgang durchgeführt wird.
  16. Steuersystem nach Anspruch 9, dadurch gekennzeichnet, daß es eine Mehrzahl von Sensor- und/oder Gebermitteln enthält und daß das Anpassungsmittel jegliche Wechselwirkung zwischen den Gebermitteln und den Sensormitteln berücksichtigt.
  17. Steuersystem nach Anspruch 9, dadurch gekennzeichnet, daß es Mittel zur Online-Systemidentifikation enthält (siehe Fig. 6).
EP92914435A 1992-06-25 1992-06-25 Steuerungssystem mit harmonischen filtern Expired - Lifetime EP0647372B1 (de)

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US5361303A (en) * 1993-04-01 1994-11-01 Noise Cancellation Technologies, Inc. Frequency domain adaptive control system
JP3572486B2 (ja) * 1994-03-25 2004-10-06 本田技研工業株式会社 振動騒音制御装置
US5713438A (en) * 1996-03-25 1998-02-03 Lord Corporation Method and apparatus for non-model based decentralized adaptive feedforward active vibration control
CN112504616A (zh) * 2020-11-18 2021-03-16 中国空气动力研究与发展中心 一种天平动态力谐波抑制方法及装置
CN119179954B (zh) * 2024-11-26 2025-02-11 中国电力科学研究院有限公司 一种筛选次同步振荡曲线的方法和系统

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US4713782A (en) * 1984-08-23 1987-12-15 Hewlett-Packard Company Method and apparatus for measuring a transfer function
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DK0647372T3 (da) 1999-12-06
WO1994000911A1 (en) 1994-01-06
CA2138552A1 (en) 1994-01-06
EP0647372A1 (de) 1995-04-12
CA2138552C (en) 1998-07-07
DE69229282T2 (de) 2000-02-24
DE69229282D1 (de) 1999-07-01

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