CN110262243B - Micro-vibration active control method for hybrid parallel adaptive structure - Google Patents
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Abstract
The invention discloses a micro-vibration active control method for a hybrid self-adaptive structure. The method directly utilizes the micro-vibration active control experiment platform to realize the structural vibration control experiment caused by time-varying multi-frequency narrow-band disturbance and wide-frequency noise disturbance; a feedback channel is added on the basis of the traditional parallel FxLMS method, so that the hybrid adaptive structure micro-vibration active control method for multi-frequency narrow-band time-varying disturbance and environment wide-band noise is formed. The method mainly comprises a feedforward parallel channel and a feedback channel, wherein an FxLMS algorithm is independently used in each channel as a self-adaptive vibration control method. And a narrow-band-pass filter corresponding to the disturbance frequency spectrum is arranged in each feed-forward channel, the multi-frequency narrow-band reference signal is split into a plurality of single-frequency narrow-band reference signals, and the structural vibration caused by the frequency spectrum disturbance is respectively inhibited. On the basis of the traditional parallel FxLMS method, the method improves the convergence performance of the algorithm by adding a feedback channel and enhances the robustness to narrow-band disturbance frequency spectrum drift and wide-band noise interference.
Description
Technical Field
The invention belongs to the field of structural vibration active control and vibration reduction, and particularly relates to a micro-vibration active control method for a hybrid parallel self-adaptive structure.
Background
With the continuous development of scientific technology, intelligent materials and intelligent structures are a new direction for research in the 21 st century. The application of intelligent structures in structural vibration suppression shows the advantages that other materials cannot replace, and particularly, the application of piezoelectric material actuators in the field of structural micro-vibration active control is an important research subject in the vibration control field.
Generally, a disturbance source causing vibration in production is not only a single frequency spectrum, but is often a superposition of several or even a plurality of narrow-band spectrum disturbance sources, and a vibration control problem under multi-frequency-line spectrum excitation exists. As an adaptive algorithm commonly used in active vibration control, the FxLMS algorithm does not work well for multi-frequency vibration control as well as for single-spectrum vibration control. In order to improve the controller effect, a scholars proposes an FxLMS algorithm with a parallel structure, namely, an adaptive filter with the same number as the target line spectrum is constructed, a reference signal is decoupled into a plurality of signals with single frequency spectrums, and multi-frequency narrow-band disturbance control is decomposed into a plurality of single-frequency disturbances to be independently suppressed.
However, in some practical systems, there are some broadband vibrations caused by the disturbance of the environmental noise, except the vibrations excited by these multi-frequency spectrum disturbance signals, and the frequency spectrum of the disturbance source in the practical vibration control system is also time-varying. For the above situation, the conventional parallel FxLMS algorithm cannot effectively suppress vibration, and even the vibration suppression effect of the controller may be deteriorated or even failed due to the inconsistency between the reference signal band-pass filter and the target vibration spectrum. Therefore, the control algorithm research for structural vibration suppression aiming at the time variation of multi-frequency narrow-band disturbance and the environment broadband noise has practical significance, and the robustness of a control system can be better met.
Disclosure of Invention
The invention aims to provide a mixed self-adaptive structure micro-vibration active control method for multi-frequency narrow-band time-varying disturbance and environment broadband noise aiming at the defects of the prior art.
In order to achieve the above object, the idea of the present invention is as follows:
a micro-vibration active control method of a mixed self-adaptive structure aiming at multi-frequency narrow-band time-varying disturbance and environment broadband noise is characterized in that a micro-vibration active control experiment platform is directly utilized to realize a structural vibration control experiment caused by the time-varying multi-frequency narrow-band disturbance and the broadband noise disturbance; a feedback channel is added on the basis of the traditional parallel FxLMS method, so that the hybrid adaptive structure micro-vibration active control method for multi-frequency narrow-band time-varying disturbance and environment wide-band noise is formed. The method mainly comprises a feedforward parallel channel and a feedback channel, wherein an FxLMS algorithm is independently used in each channel as a self-adaptive vibration control method.
Suppose that the disturbance signal contains M narrow-band spectrum components with center frequencies f m M =1. The method for actively controlling the micro-vibration of the mixed self-adaptive structure aiming at the multi-frequency narrow-band time-varying disturbance and the environment broadband noise, provided by the invention, is provided with M feedforward parallel channels and M independent parallel self-adaptive finite impulse response filters W m (FIR). These adaptive finite impulse response filters W m The (FIR) adjusts convergence by a filtered least mean square algorithm (FxLMS). In each feed-forward path, pass through a band-pass filter B m The reference signal x (n) is split into a plurality of narrow-band reference signals x which are the same as the disturbance spectrum i (n), i =1.. M. Adaptive finite impulse response filter W m Adjusting convergence by a filtered least mean square algorithm (FxLMS) and outputting a control signal y of the feed-forward channel m (n) of (a). In the feedback path, the reference signal is output by the control of the feedback path f And (n) is synthesized with the error e (n) of the vibration control system. Adapting an adaptive finite impulse response filter W by a filtered least mean square algorithm (FxLMS) f To converge. The control output y (n) of the controller is the output response y from a plurality of feed-forward channels i (n), i =1.. M and a control output y of the feedback channel f (n) obtained by synthesis. By adding the feedback channel, the hybrid self-adaptive structure micro-vibration active control method provided by the invention has better robustness for multi-frequency narrow-band time-varying disturbance and environment broadband noise.
According to the inventive concept, the invention adopts the following technical scheme:
a micro-vibration control method for a hybrid parallel adaptive structure is characterized by comprising the following operation steps:
(1) Depending on the frequency of the disturbance signal in the particular application of the controllerSpectral characteristics, designing band-pass filter B matched with narrow-band spectrum in disturbing signal m 。
(2) A secondary channel mathematical model of the control system is obtained by identification means.
(3) Designing an adaptive finite impulse response filter W in a feedforward parallel channel according to the frequency spectrum and amplitude characteristics of a disturbance signal in the specific application occasion of a controller m And an adaptive finite impulse response filter W in the feedback path f The order of (2); design and adjustment of adaptive finite impulse response filter W in feedforward parallel path m And adjusting the adaptive finite impulse response filter W in the feedback path f Step size mu of the filtered least mean square algorithm (FxLMS) of (1) m And mu f 。
(4) Acquiring a system reference signal x (n), acquiring a system error e (n), and iterating according to a filtering least mean square algorithm (FxLMS) to obtain a self-adaptive finite impulse response filter W m And an adaptive finite impulse response filter W in the feedback path f The weight coefficient of the controller is calculated to obtain the control output y (n) of the controller and the control output y (n) is output to the actuator.
And the iterative operation of the control method is carried out until the control requirement of the system is met. The specific calculation formula of the control algorithm is as follows:
x m (n)＝x(n)*B m (1)
y m (n)＝W m (n) T x m (n)S(n) (2)
e(n)＝d(n)-S(n) T y(n) (4)
W m (n+1)＝W m (n)+μ m e(n)x′ m (n) (6)
x′ f (n)＝S(n)x f (n) (7)
x f (n)＝y f (n)S(n)+e(n) (8)
W f (n+1)＝W f (n)+μ f e(n)x′ f (n) (9)
wherein S (n) is the identification model of the system secondary channel, x m (n) is the reference signal filtered by the feedforward narrow-band filter, x f And (n) is a reference signal of the feedback channel.
Compared with the prior art, the hybrid adaptive structure micro-vibration active control method for multi-frequency narrow-band time-varying disturbance and environment broadband noise provided by the invention has the following obvious substantial characteristics and remarkable progress:
(1) By adding the feedback channel, the adaptability of the original control algorithm when the frequency spectrum offset occurs in the multi-frequency narrow-band disturbance is improved, and the universality and the robustness of the controller are improved.
(2) The addition of the feedback channel enhances the inhibition capability of the original control algorithm on the structural vibration caused by the broadband noise interference.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the embodiments will be briefly described below.
FIG. 1 is a flow chart of the vibration active control method of the present invention.
Fig. 2 is a schematic diagram of a preferred embodiment of the vibration active control method of the present invention.
Fig. 3 is a control schematic diagram of the active vibration control method of the present invention.
FIG. 4 is a photograph of an experimental system of the active vibration control method of the present invention.
FIG. 5 is a comparison graph of experimental control effects of the active vibration control method of the present invention and the existing control method when the disturbance frequency changes abruptly.
FIG. 6 is a comparison graph of experimental control effects when white noise disturbance is suddenly added in the vibration active control method of the present invention and the existing control method.
The specific implementation mode is as follows:
while the preferred embodiments of the present invention will be described and discussed fully hereinafter with reference to the accompanying drawings, it is to be understood that the drawings are merely illustrative of some embodiments of the invention and that all other embodiments can be made by one skilled in the art without the exercise of inventive faculty.
The invention aims to provide a micro-vibration active control method of a hybrid adaptive structure aiming at multi-frequency narrow-band time-varying disturbance and environment broadband noise, which can effectively enhance the robustness of the traditional parallel FxLMS algorithm.
In order to make the aforementioned objects, features and advantages of the present invention more comprehensible, the present embodiment takes the micro-vibration active control experiment system as an example, and the present invention is further described in detail with reference to the accompanying drawings and specific embodiments.
The first embodiment is as follows:
referring to fig. 1 to 6, the method for actively controlling micro-vibration of a hybrid parallel adaptive structure is characterized by comprising the following operation steps:
(1) Designing a band-pass filter B matched with a narrow-band spectrum in the disturbance signal according to the frequency spectrum characteristics of the disturbance signal in the specific application occasion of the controller m ；
(2) Obtaining a secondary channel mathematical model of the control system through an identification means;
(3) According to the frequency spectrum and amplitude characteristics of the disturbance signal in the specific application occasion of the controller, the self-adaptive finite impulse response filter W in the feedforward parallel channel is designed m And an adaptive finite impulse response filter W in the feedback path f The order of (a); design and adjustment of adaptive finite impulse response filter W in feedforward parallel path m And adjusting the adaptive finite impulse response filter W in the feedback path f Step size mu of filtering least mean square algorithm FxLMS m And mu f ；
(4) Acquiring a system reference signal x (n), acquiring a system error e (n), and iterating according to a filtering least mean square algorithm FxLMS to obtain a self-adaptive finite impulse response filter W m And adaptive finite impulse in feedback channelResponse filter W f Calculating the weight coefficient to obtain the control output y (n) of the controller and outputting the control output y (n) to the actuator; and the iterative operation of the control method is carried out until the control requirement of the system is met.
Example two:
the present embodiment is substantially the same as the first embodiment, and is characterized in that the control method in step (4) has the following calculation formula:
x m (n)＝x(n)*B m (10)
y m (n)＝W m (n) T x m (n)S(n) (11)
e(n)＝d(n)-S(n) T y(n) (13)
W m (n+1)＝W m (n)+μ m e(n)x′ m (n) (15)
x′ f (n)＝S(n)x f (n) (16)
x f (n)＝y f (n)S(n)+e(n) (17)
W f (n+1)＝W f (n)+μ f e(n)x′ f (n) (18)
wherein S (n) is the identification model of the system secondary channel, x m (n) is the reference signal filtered by the feedforward narrow-band filter, x f And (n) is a reference signal of the feedback channel.
Example three:
as shown in fig. 1, fig. 2 and fig. 4, a method for actively controlling micro-vibration of a hybrid adaptive structure for multi-frequency narrow-band time-varying disturbance and environmental wideband noise, specifically a method for actively controlling micro-vibration of a hybrid adaptive structure of a micro-vibration active control experiment system, includes the following steps:
(1) As shown in fig. 4, the host 4 loads the active control algorithm into the target 5, and the target 5 drives the actuation piezo stack of the oscillation starting module 1-2 to actuate through the analog output data conversion card 6 and the piezo stack actuation driver 7, so as to simulate the micro-oscillation caused by external disturbance. The host machine 4 can design different disturbance signals according to actual requirements, such as disturbance signals in an actual application environment, for example, impact disturbance, sine disturbance, noise disturbance and the like.
(2) As shown in fig. 4, the three-axis acceleration sensor 2 respectively collects acceleration signals of the oscillation starting module 1-2 and the oscillation suppressing module 1-3 in three directions perpendicular to each other,
(3) As shown in fig. 4, the acceleration signal is transmitted to the target machine 5 through the analog input data acquisition card 3, the target machine 5 obtains control output according to the operation of the active control algorithm loaded in advance, then the control signal is output to the piezoelectric stack actuation driver 7 through the analog output data conversion card 6, and finally the actuation piezoelectric stack actuation of the vibration suppression module 1-3 is driven, so that the acceleration vibration of the object stage 1-4 reaches the control target.
(4) And storing relevant experimental data in real time and preparing the data for subsequent experimental analysis.
The schematic diagram of the vibration control method is shown in fig. 3, and in order to overcome the defects of the original control method under the conditions of disturbance signal frequency spectrum variation and white noise, the vibration active control method ensures the structural vibration suppression effect by adding the adaptive feedback channel, and improves the robustness of the control algorithm.
In this embodiment, all the feedforward adaptive finite impulse response filters W in the controller m And an adaptive finite impulse response filter W in the feedback path f Is 24, and the step size mu of the filtering least mean square algorithm (FxLMS) of the adaptive finite impulse response filter is adjusted m And mu f Set to 0.0005; the sampling frequency is set to 1000Hz; the mixed self-adaptive active vibration control method respectively verifies the suppression effect of the mixed self-adaptive active vibration control method on disturbance frequency spectrum mutation and broadband white noise in two experiments, wherein the disturbance signals in the first experiment adopt 10Hz and 25Hz sine superposition as the disturbance signals in the first 80s, and the amplitudes are all equal to0.8V; after 80s, the frequency of the disturbing signal is changed to 11Hz and 26Hz, and the amplitude is unchanged. In the second experiment, the disturbance signals adopt 10Hz and 25Hz sine superposition as disturbance signals in the first 80s, and the amplitude values are 0.8V; and after 80s, adding white noise with a certain signal-to-noise ratio to the disturbing signal. FIG. 5 is a comparison graph of experimental control effects of the active vibration control method of the present invention and the existing control method when the disturbance frequency changes abruptly. FIG. 6 is a comparison graph of experimental control effects when white noise disturbance is suddenly added in the vibration active control method of the present invention and the existing control method. After the vibration active control method is applied, the structural vibration response can be well inhibited, and particularly, a better vibration inhibition effect can be obtained under the conditions of multi-frequency narrow-band disturbance signal time variation and broadband white noise, and the vibration inhibition effect is superior to that of the existing method.
Claims (1)
1. A micro-vibration active control method of a hybrid parallel self-adaptive structure is characterized by comprising the following operation steps:
(1) Designing a band-pass filter B matched with a narrow-band spectrum in the disturbance signal according to the frequency spectrum characteristics of the disturbance signal in the specific application occasion of the controller m ；
(2) Obtaining a secondary channel mathematical model of the control system through an identification means;
(3) Designing an adaptive finite impulse response filter W in a feedforward parallel channel according to the frequency spectrum and amplitude characteristics of a disturbance signal in the specific application occasion of a controller m And an adaptive finite impulse response filter W in the feedback path f The order of (2); design and adjustment of adaptive finite impulse response filter W in feedforward parallel path m And adjusting the adaptive finite impulse response filter W in the feedback path f Step size mu of filtering least mean square algorithm FxLMS m And mu f ；
(4) Acquiring a system reference signal x (n), acquiring a system error e (n), and iterating according to a filtering least mean square algorithm FxLMS to obtain a self-adaptive finite impulse response filter W m And an adaptive finite impulse response filter W in the feedback path f The weight coefficient is calculated and controlledThe control output y (n) of the controller is output to the actuator; the iterative operation of the control method is carried out until the control requirement of the system is met; the control method in the step (4) has the following calculation formula:
x m (n)＝x(n)*B m (1)
y m (n)＝W m (n) T x m (n)S(n) (2)
W m (n+1)＝W m (n)+μ m e(n)x′ m (n) (6)
W f (n+1)＝W f (n)+μ f e(n)x′ f (n) (9)
wherein the content of the first and second substances,
is a recognition model of the system secondary channel, x m (n) is the reference signal filtered by the feedforward narrow-band filter, x f And (n) is a reference signal of the feedback channel.
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| CN110794681B (en) * | 2019-11-22 | 2022-05-10 | 西北工业大学 | FxLMS filtering method for narrow-band active vibration system |
| CN111522244A (en) * | 2020-02-14 | 2020-08-11 | 哈尔滨工程大学 | Active control system using leakage FxLMS algorithm |
| CN111722653A (en) * | 2020-07-01 | 2020-09-29 | 中国科学院上海技术物理研究所 | Self-adaptive high-order vibration active control method for mechanical refrigerator |
| CN116232123B (en) * | 2023-05-06 | 2023-08-08 | 太原理工大学 | Energy self-adaptive conversion device and method based on mining air duct vibration spectrum |
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