CN107991882A - The design method and accuracy control system of piezoelectric ceramic actuator precision control device - Google Patents
The design method and accuracy control system of piezoelectric ceramic actuator precision control device Download PDFInfo
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Abstract
The invention discloses a kind of design method and accuracy control system of piezoelectric ceramic actuator precision control device, which includes the Hysteresis Nonlinear model using Bouc wen model construction piezoelectric ceramic actuators；Its inverse function is asked to Hysteresis Nonlinear model, obtains hysteresis compensation device；The parameter alpha gone out using the ARX Function identifications of Matlab System Identification Toolboxes1,α2,…anAnd b0,b1,…bmBuild the linear kinetic model of piezoelectric ceramic actuator；Learning filters is chosen using the phase or exponent number of linear kinetic model, and iterative learning controller is built according to learning filters；Connect hysteresis compensation device and iterative learning controller forms the precision control device of piezoelectric ceramic actuator.
Description
Technical field
The present invention relates to the invention belongs to motion control and Precision Manufacturing Technology field, and in particular to a kind of piezoelectric ceramics is held
The design method and accuracy control system of row device precision control device.
Background technology
With the continuous development of MEMS (micro electro mechanical system) technology, people are in microcosmic neck
The exploration and research in domain are constantly deepened.In many application fields, such as Precision Machining, optical-fibre communications, material science etc., for driving
Device required precision is all progressively being deepened, and traditional motor driver is since inertia is big, and low-response, precision is low, not
Meeting the requirement in above-mentioned field.As one kind of intellectual material, piezoelectric ceramics has response fast, and driving force is big, and precision is high, surely
The advantages that qualitative good, it is widely used in micro-nano positioning and drive system.
But since piezoceramic material has intrinsic Hysteresis Nonlinear, directly influence the control of micro-nano control system
Performance processed, or even can cause unstable.How Hysteresis Nonlinear that controller effectively suppress piezoelectric ceramic actuator is designed, it is real
Existing high-accuracy motion control, is the problem of micro-nano control system of piezoelectric ceramics primarily faces.
The content of the invention
For above-mentioned deficiency of the prior art, the design of piezoelectric ceramic actuator precision control device provided by the invention
Method and accuracy control system can effectively suppress the Hysteresis Nonlinear of piezoelectric ceramic actuator by precision control device, realize
High-accuracy motion control.
In order to reach foregoing invention purpose, the technical solution adopted by the present invention is：
First aspect, there is provided a kind of design method of piezoelectric ceramic actuator precision control device, it includes：
Using the Hysteresis Nonlinear model of Bouc-wen model construction piezoelectric ceramic actuators：
H (x, h)=y (t)=kx (t)-dh (t))
Wherein, h (t) is sluggish component；Y (t) is the output displacement of piezoelectric ceramic actuator；X (t) performs for piezoelectric ceramics
The driving voltage of device；K is the ratio of driving voltage and output displacement；D is the ratio of sluggish component and output displacement；
Its inverse function is asked to Hysteresis Nonlinear model, obtains hysteresis compensation device：
Wherein, yr(t) it is desired output displacement；H(yr,h)-1For the inverse function of Hysteresis Nonlinear model；
The parameter alpha gone out using the ARX Function identifications of Matlab System Identification Toolboxes1,α2,…anAnd b0,b1,…bmStructure
The linear kinetic model of piezoelectric ceramic actuator：
Wherein, z-1For unit sluggishness operator；N is the exponent number of piezoelectric ceramic actuator, and m is the parameter less than n；
Learning filters is chosen using the phase or exponent number of linear kinetic model, and iteration is built according to learning filters
Learning controller：
Ui+1(z)=Q (z) (Ui(z)+βL(z)Ei(z))
Wherein, Ui(z) and Ei(z) when being respectively ith iteration piezoelectric ceramic actuator driving voltage and tracking error；
Ui+1(z) for i+1 time iteration when piezoelectric ceramic actuator driving voltage；L (z) is learning filters；Q (z) is low-pass filtering
Device；β is gain coefficient；
Connect hysteresis compensation device and iterative learning controller forms the precision control device of piezoelectric ceramic actuator.
Second aspect, there is provided a kind of piezoelectric ceramic actuator precise flange system, it include piezoelectric ceramic actuator,
Signal generator and precision control device；Signal generator successively with adder, precision control device, digital analog converter, power
Amplifier, piezoelectric ceramic actuator, displacement sensor are connected with analog-digital converter；The output of analog-digital converter is inputted with adder
Connection；The output of the hysteresis compensation device of precision control device is connected with digital analog converter input, the iteration of precision control device
The input for practising device is connected with adder.
Beneficial effects of the present invention are：This programme is asked by the Hysteresis Nonlinear model of the piezoelectric ceramic actuator to structure
Inversion model that is inverse, obtaining, i.e. hysteresis compensation device, it can compensate for the intrinsic Hysteresis Nonlinear characteristic of piezoelectric ceramic actuator；
The iterative learning controller designed by the linear kinetic model of structure can further reduce because modeling it is inaccurate and
Error, by iteration for several times, can be reduced to the precision of the hardware device of piezoelectric ceramic actuator control system by the error of introducing,
Meets the needs of accurate tracing control.
The method being combined using iterative learning controller and feedforward hysteresis compensation device, passes through the several of iterative learning controller
Secondary iteration, can be reduced to zero by error in theory, and in practical operation, error can be reduced to the pole of the equipment of whole system
Precision is limited, i.e. complete equipment is more accurate, and error is smaller.
Brief description of the drawings
Fig. 1 is the flow chart of design method one embodiment of piezoelectric ceramic actuator precision control device.
Fig. 2 is the functional block diagram of piezoelectric ceramic actuator precise flange system.
Fig. 3 is the PID control schematic diagram of the hysteresis compensation device containing feedforward.
The complex controll schematic diagram that Fig. 4 is hysteresis compensation device and iterative learning controller is connected.
Fig. 5 be the method for the present invention with traditional PID control and containing feedforward hysteresis compensation device PID control tracing control contrast
Design sketch.
Fig. 6 passes through five iteration for the method for the present invention, controls the downward trend curve of error.
Embodiment
The embodiment of the present invention is described below, in order to facilitate understanding by those skilled in the art this hair
It is bright, it should be apparent that the invention is not restricted to the scope of embodiment, for those skilled in the art,
As long as various change in the spirit and scope of the present invention that appended claim limits and determines, these changes are aobvious and easy
See, all are using the innovation and creation of present inventive concept in the row of protection.
With reference to figure 1, Fig. 1 shows the flow of design method one embodiment of piezoelectric ceramic actuator precision control device
Figure；As shown in Figure 1, this method 100 includes step 101 to step 105.
In a step 101, using the Hysteresis Nonlinear model of Bouc-wen model construction piezoelectric ceramic actuators：
H (x, h)=y (t)=kx (t)-dh (t))
Wherein, h (t) is sluggish component；Y (t) is the output displacement of piezoelectric ceramic actuator；X (t) performs for piezoelectric ceramics
The driving voltage of device；K is the ratio of driving voltage and output displacement；D is the ratio of sluggish component and output displacement.
During implementation, the nonlinear differential equation of the preferably sluggish component of this programme is：
Wherein,First derivative for sluggish component h (t) to time t；The magnitude parameters of ρ hysteresis loop amplitudes in order to control；σ
The form parameter of sluggish ring-shaped in order to control；The parameter of n hysteresis loop smoothness in order to control.
In one embodiment of the invention, the acquisition methods of parameter k, d, ρ, σ, n include：
Bouc-wen models are obtained, the initial value and error threshold of the parameter k, d, ρ, σ, n in Bouc-wen models are set；
The driving voltage of piezoelectric ceramic actuator is inputted into Bouc-wen models, and uses Matlab System Identification Toolboxes
Adjusting parameter k, d, ρ, σ, n；
Difference between the output displacement and the output displacement that actually measures of Bouc-wen models is more than or equal to error threshold
During value, continue adjusting parameter k, d, ρ, σ, n until difference is less than error threshold；
When the difference between the output displacement and the output displacement that actually measures of Bouc-wen models is less than error threshold,
Output parameter k, d, ρ, σ, n.
In a step 102, its inverse function is asked to Hysteresis Nonlinear model, obtains hysteresis compensation device：
Wherein, yr(t) it is desired output displacement；H(yr,h)-1For the inverse function of Hysteresis Nonlinear model.
This programme can compensate for the intrinsic Hysteresis Nonlinear spy of piezoelectric ceramic actuator by the hysteresis compensation device of design
Property, so as to reach the driving precision for increasing substantially piezoelectric ceramic actuator.
In step 103, the parameter alpha gone out using the ARX Function identifications of Matlab System Identification Toolboxes1,α2,…anWith
b0,b1,…bmBuild the linear kinetic model of piezoelectric ceramic actuator：
Wherein, z-1For unit sluggishness operator；N is the exponent number of piezoelectric ceramic actuator, and m is the parameter less than n.
In one embodiment of the invention, parameter alpha1,α2,…anAnd b0,b1,…bmAcquisition methods include：
Using swept-frequency signal, (frequency range is [f1-f2]) Hysteresis Nonlinear model and piezoelectric ceramic actuator are driven respectively,
Obtain driving voltage and the reality output displacement of the piezoelectric ceramic actuator of nonlinear model；
Driving voltage and reality output displacement to piezoelectric ceramic actuator are normalized；
The driving voltage of the exponent number of ARX functions and collection piezoelectric ceramic actuator in Matlab System Identification Toolboxes is set
Sampling time；
By the driving voltage of the piezoelectric ceramic actuator after normalized and reality output displacement input ARX functions, obtain
To parameter alpha1,α2,…anAnd b0,b1,…bm。
At step 104, learning filters is chosen using the phase or exponent number of linear kinetic model, and is filtered according to study
Ripple device builds iterative learning controller：
Ui+1(z)=Q (z) (Ui(z)+βL(z)Ei(z))
Wherein, Ui(z) and Ei(z) when being respectively ith iteration piezoelectric ceramic actuator driving voltage and tracking error；
Ui+1(z) for i+1 time iteration when piezoelectric ceramic actuator driving voltage；L (z) is learning filters；Q (z) is low-pass filtering
Device；β is gain coefficient.
During implementation, this programme is preferably chosen learning filters using linear kinetic model and is further comprised：
When the phase of linear kinetic model is located at (- 90 °, 90 °), learning filters L (z)=1；
When linear kinetic model is second-order system, and during an only integrator, learning filters L (z)=1-z-1；
When the exponent number of linear kinetic model is more than 2, and at most has two integrators, learning filters L (z)=1-
2z-1+z-2, z-2For the inverse square of sluggish operator；
When the phase of linear kinetic model meets minimum, learning filters L (z)=G (z)-1；As learning filters L
(z)=G (z)-1When, the error convergence of iterative learning controller is fastest.
Iterative learning controller utilizes the last output error signal E testedi(z) and input control signal Ui(z), lead to
Above-mentioned Iterative Algorithm is crossed, learns more preferably control signal Ui+1(z) as the control input tested next time, by several
The output error of piezoelectric ceramic actuator, can be reduced to hardware device (sensor, digital analog converter etc.) by secondary iteration experiment
Ultimate precision (tracking accuracy reaches the ultimate precision of hardware device).
In step 105, connect hysteresis compensation device and iterative learning controller forms the precision control of piezoelectric ceramic actuator
Device processed.
During implementation, the preferred tracking error E of this programmei(z) calculation formula is：
Ei(z)=Yr(z)-Yi(z)
Wherein, Yr(z) it is the reference signal of tracking；Yi(z) the ith iteration control collected for displacement sensor is defeated
Go out displacement.
As shown in Fig. 2, the piezoelectric ceramic actuator precise flange system includes piezoelectric ceramic actuator, signal occurs
Device and precision control device；Signal generator successively with adder, precision control device, digital analog converter, power amplifier, pressure
Electroceramics actuator, displacement sensor are connected with analog-digital converter；The output of analog-digital converter is connected with adder input；Precision
The output of the hysteresis compensation device of control device is connected with digital analog converter input, the input of the iterative learning device of precision control device
It is connected with adder.
, can be with Hysteresis Nonlinear model after the Hysteresis Nonlinear model and linear kinetic model of foundation are connected
With the model of linear kinetic model expression piezoelectric ceramic actuator：P=H (yr,h)-1·G(z)。
Tracing control experiment is carried out below by the cylindricality piezoelectric ceramic actuator to model Pst150/7/60VS12,
The precision control device of this programme design is verified：
Tracing control experiment, actuator travel are carried out using the piezoelectric ceramic actuator of model Pst150/7/60VS12
Scope is 58.83um, driving voltage 0-150V；Power amplifier select piezoelectric ceramics servo power amplifier, A D conversion choosing
With dSPACE semi-physical emulation platforms, board DS1006, is Newport S-2000 optical vibration reduction platforms using experiment porch；
Tracing control experiment sampling interval t is 0.0001s, and the reference signal of tracking is：
The composite control method that the feedforward hysteresis compensation and iterative learning that control method is designed using the present invention program control,
Scheme used in contrast experiment is traditional PID control method and the PID composite control methods of the hysteresis compensation device containing feedforward.
It is containing feedforward with reference to figure 3 with reference to iterative learning controller (ILC) schematic diagram that figure 4 is the hysteresis compensation device containing feedforward
The PID controller schematic diagram of hysteresis compensation device.Traditional PID control is few feedforward hysteresis compensation device on the basis of Fig. 3.
Fig. 5 be the method for the present invention with tradition PID closed-loop controls and containing feedforward against compensator PID/feedback control method with
Track effect contrast figure.
By contrast it can be found that the precision control device of this programme design is (single relative to existing two kinds of conventional methods
Pure closed loop PID control and the PID control method containing the hysteresis compensation device that feedovers) compare, improve a lot in control accuracy；
Specifically, the maximum value of the error signal of simple closed loop PID control is 128.3nm, the hysteresis compensation device containing feedforward
The maximum value of the error signal of PID control is 81.6nm, and the error signal of the precision control device of this programme design is most
Big absolute value error is 18.5nm.Relative to two kinds of traditional control methods, the method in the present invention is distinguished in control accuracy
Improve 85.6% and 77.3%.
As shown in fig. 6, the controller designed by this programme can drop to hardware device by five iteration errors
18.5 nanometers of ultimate precision.
Performed in conclusion the precision control device of this programme design can compensate for piezoelectric ceramics by hysteresis compensation device
The intrinsic Hysteresis Nonlinear characteristic of device；Positioning accuracy can just be brought up to by the iteration several times of iterative learning controller used flat
The ultimate precision of platform hardware device.
Claims (8)
1. the design method of piezoelectric ceramic actuator precision control device, it is characterised in that including：
Using the Hysteresis Nonlinear model of Bouc-wen model construction piezoelectric ceramic actuators：
H (x, h)=y (t)=kx (t)-dh (t))
Wherein, h (t) is sluggish component；Y (t) is the output displacement of piezoelectric ceramic actuator；X (t) is piezoelectric ceramic actuator
Driving voltage；K is the ratio of driving voltage and output displacement；D is the ratio of sluggish component and output displacement；
Its inverse function is asked to the Hysteresis Nonlinear model, obtains hysteresis compensation device：
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Wherein, yr(t) it is desired output displacement；H(yr,h)-1For the inverse function of Hysteresis Nonlinear model；
The parameter alpha gone out using the ARX Function identifications of Matlab System Identification Toolboxes1,α2,…anAnd b0,b1,…bmBuild piezoelectricity
The linear kinetic model of ceramic actuator：
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Wherein, z-1For unit sluggishness operator；N is the exponent number of piezoelectric ceramic actuator, and m is the parameter less than n；
Learning filters is chosen using the phase or exponent number of linear kinetic model, and iterative learning is built according to learning filters
Controller：
Ui+1(z)=Q (z) (Ui(z)+βL(z)Ei(z))
Wherein, Ui(z) and Ei(z) when being respectively ith iteration piezoelectric ceramic actuator driving voltage and tracking error；Ui+1
(z) for i+1 time iteration when piezoelectric ceramic actuator driving voltage；L (z) is learning filters；Q (z) is low-pass filter；
β is gain coefficient；
Connect hysteresis compensation device and iterative learning controller forms the precision control device of piezoelectric ceramic actuator.
2. the design method of piezoelectric ceramic actuator precision control device according to claim 1, it is characterised in that described
Learning filters is chosen using linear kinetic model to further comprise：
When the phase of linear kinetic model is located at (- 90 °, 90 °), learning filters L (z)=1；
When linear kinetic model is second-order system, and during an only integrator, learning filters L (z)=1-z-1；
When the exponent number of linear kinetic model is more than 2, and at most has two integrators, learning filters L (z)=1-2z-1+z-2, z-2For the inverse square of sluggish operator；
When the phase of linear kinetic model meets minimum, learning filters L (z)=G (z)-1。
3. the design method of piezoelectric ceramic actuator precision control device according to claim 1, it is characterised in that described
The nonlinear differential equation of sluggish component is：
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Wherein,First derivative for sluggish component h (t) to time t；The magnitude parameters of ρ hysteresis loop amplitudes in order to control；σ is control
The form parameter of the sluggish ring-shaped of system；The parameter of n hysteresis loop smoothness in order to control.
4. the design method of piezoelectric ceramic actuator precision control device according to claim 1, it is characterised in that described
The acquisition methods of parameter k, d, ρ, σ, n include：
Bouc-wen models are obtained, the initial value and error threshold of the parameter k, d, ρ, σ, n in Bouc-wen models are set；
The driving voltage of piezoelectric ceramic actuator is inputted into Bouc-wen models, and using the adjustment of Matlab System Identification Toolboxes
Parameter k, d, ρ, σ, n；
When the difference between the output displacement and the output displacement that actually measures of Bouc-wen models is more than or equal to error threshold,
Continue adjusting parameter k, d, ρ, σ, n until difference is less than error threshold；
When the difference between the output displacement and the output displacement that actually measures of Bouc-wen models is less than error threshold, output
Parameter k, d, ρ, σ, n.
5. the design method of piezoelectric ceramic actuator precision control device according to claim 1, it is characterised in that described
Parameter alpha1,α2,…anAnd b0,b1,…bmAcquisition methods include：
Drive Hysteresis Nonlinear model and piezoelectric ceramic actuator respectively using swept-frequency signal, obtain the piezoelectricity pottery of nonlinear model
The driving voltage of porcelain actuator and reality output displacement；
Driving voltage and reality output displacement to piezoelectric ceramic actuator are normalized；
The driving voltage of the exponent number of ARX functions and collection piezoelectric ceramic actuator adopts in setting Matlab System Identification Toolboxes
The sample time；
By the driving voltage of the piezoelectric ceramic actuator after normalized and reality output displacement input ARX functions, joined
Number α1,α2,…anAnd b0,b1,…bm。
6. the design method of piezoelectric ceramic actuator precision control device according to claim 1, it is characterised in that described
Tracking error Ei(z) calculation formula is：
Ei(z)=Yr(z)-Yi(z)
Wherein, Yr(z) it is the reference signal of tracking；Yi(z) carry-out bit of the ith iteration control collected for displacement sensor
Move.
7. piezoelectric ceramic actuator precise flange system, it is characterised in that including piezoelectric ceramic actuator, signal generator
And the precision control device using any the method designs of claim 1-6；The signal generator successively with adder, essence
Degree control device, digital analog converter, power amplifier, piezoelectric ceramic actuator, displacement sensor are connected with analog-digital converter；Institute
The output and adder input for stating analog-digital converter connect；The output of the hysteresis compensation device of the precision control device and number
Mode converter input connection, the input of the iterative learning device of precision control device are connected with adder.
8. piezoelectric ceramic actuator precise flange system according to claim 1, it is characterised in that using precision control
The Hysteresis Nonlinear model of device design process structure processed and the model of linear kinetic model expression piezoelectric ceramic actuator：P
=H (yr,h)-1·G(z)。
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Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102280572A (en) * | 2011-04-15 | 2011-12-14 | 重庆大学 | Composite linear control method of hysteresis characteristic of piezoelectric ceramic actuator and realization circuit thereof |
| CN104122798A (en) * | 2014-07-24 | 2014-10-29 | 上海交通大学 | High-speed nano precision movement control method and system for piezoelectric ceramic driver |
| CN104503244A (en) * | 2014-12-29 | 2015-04-08 | 中国科学技术大学 | Nonrepetitiveness disturbance observer based precision positioning selective ILC (iteration learning control) system and method |
| CN105068564A (en) * | 2015-08-03 | 2015-11-18 | 北京理工大学 | Displacement control method for piezoelectric ceramic actuator |
-
2017
- 2017-12-26 CN CN201711427714.0A patent/CN107991882A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102280572A (en) * | 2011-04-15 | 2011-12-14 | 重庆大学 | Composite linear control method of hysteresis characteristic of piezoelectric ceramic actuator and realization circuit thereof |
| CN104122798A (en) * | 2014-07-24 | 2014-10-29 | 上海交通大学 | High-speed nano precision movement control method and system for piezoelectric ceramic driver |
| CN104503244A (en) * | 2014-12-29 | 2015-04-08 | 中国科学技术大学 | Nonrepetitiveness disturbance observer based precision positioning selective ILC (iteration learning control) system and method |
| CN105068564A (en) * | 2015-08-03 | 2015-11-18 | 北京理工大学 | Displacement control method for piezoelectric ceramic actuator |
Non-Patent Citations (7)
| Title |
|---|
| JIANXIN XU等: "High Performance Tracking of Piezoelectric Positioning Stage Using Current-cycle Iterative Learning Control With Gain Scheduling", 《6TH IFAC SYMPOSIUM ON MECHATRONIC SYSTEMS THE INTERNATIONAL FEDERATION OF AUTOMATIC CONTROL》 * |
| KHALID ABIDI等: "Iterative Learning control for Sampled-Data Systems:From Theory to Practice", 《IEEE TRANSACTIONS ON INDUSTPIAL ELECTRONICS》 * |
| KHALID ABIDI等: "Iterative Learning Control for Sampled-Data Systems：From Theory to Practice", 《IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS》 * |
| 刘莉欣: "微小型四旋翼飞行器辨识建模研究", 《中国优秀硕士学位论文全文数据库》 * |
| 姜皓等: "压电陶瓷驱动器的迭代学习逆补偿混合控制", 《江苏航空》 * |
| 马彪: "压电柔性板自适应滤波振动控制研究", 《中国优秀硕士学位论文全文数据库》 * |
| 马志军等: "永磁直线同步电机的零相位迭代学习控制", 《第十二届沈阳科学学术年会论文集》 * |
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
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| CN108877843B (en) * | 2018-09-11 | 2019-09-24 | 中科院合肥技术创新工程院 | A kind of threshold decision anti-saturation method for piezo actuator in hard disk |
| CN110618609A (en) * | 2019-06-04 | 2019-12-27 | 上海卫星工程研究所 | Method suitable for flexible satellite body-flexible body cooperative control |
| CN110531708A (en) * | 2019-07-02 | 2019-12-03 | 上海大学 | A kind of identification of Three Degree Of Freedom piezoelectric actuating platform and compensating control method |
| CN110543097A (en) * | 2019-08-06 | 2019-12-06 | 广东工业大学 | Piezoelectric ceramic driver control method based on model reference self-adaption |
| CN110543097B (en) * | 2019-08-06 | 2023-01-20 | 广东工业大学 | Piezoelectric ceramic driver control method based on model reference self-adaptation |
| CN114237045A (en) * | 2021-11-29 | 2022-03-25 | 哈尔滨工业大学 | Sensorless piezoelectric drive closed-loop control method |
| CN114296349A (en) * | 2021-12-27 | 2022-04-08 | 华中科技大学 | Magnetic hysteresis control method and device for nano positioning platform |
| CN114296349B (en) * | 2021-12-27 | 2024-04-05 | 华中科技大学 | Hysteresis control method and device for nanometer positioning platform |
| CN114776756A (en) * | 2022-01-11 | 2022-07-22 | 温州大学 | Active and passive broadband vibration isolation system for high-precision instrument |
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