Output detection control method of micro-opto-electro-mechanical micro-mirror

Abstract

The invention relates to an output detection control method for a micro-opto-electro-mechanical micro-mirror, and the method comprises the steps: 1, constructing an output adjustment design research frame of an output feedback mechanism based on a kinetic model of the micro-opto-electro-mechanical micro-mirror, and forming a tracking control problem of the micro-mirror with transient performance constraint; step 2, based on an output adjustment design framework, constructing an internal model, introducing coordinate transformation, converting a transient performance constraint tracking problem of the micro-opto-electro-mechanical micro-mirror into a transient performance constraint stability design problem of an augmented system, and obtaining the augmented system in a lower triangle form; and 3, designing a detection control rule for the augmented system in the lower triangle form, learning a driving coefficient relationship between the electromagnetic torque and the driving current by using an adaptive learning mechanism, adjusting parameters of the detection control rule in combination with a barrier Lyapunov function and by using a Lyapunov stability theory, and obtaining a detection result of the augmented system in the lower triangle form. Effective asymptotic tracking of the micro-electro-mechanical torsion micro-mirror on a reference trajectory can be realized, and efficient guarantee of the angle output transient performance of the micro-mirror in the tracking process can be realized.

Description

Technical Field

[0001] The present invention relates to the technical field of micro-opto-electromechanical systems, and in particular to an output detection and control method for a micro-opto-electromechanical micromirror. Background Art

[0002] As the core component of micro-electromechanical systems (MEMS), MEMS micromirrors are widely used in a variety of optical instrumentation applications, including digital communications, high-quality imaging, and biomedical displays. These mirrors are required to provide high-precision scanning and imaging performance, achieved through precise control of the mirror's rotation angle by a MEMS actuator. Furthermore, the high-speed operation of the MEMS micromirrors enables them to operate at high frequencies and respond quickly. These characteristics have enabled MEMS systems based on torsional micromirrors to be widely used in optical communications, optical displays, biomedical imaging, and other fields, providing strong support for achieving high-precision and efficient optical imaging perception and detection control.

[0003] Scanning detection and control of a microelectromechanical torsional micromirror with transient performance constraints is crucial and a core research issue in the field of micro-nano high-precision detection and control. Achieving asymptotic tracking of a reference trajectory while satisfying transient performance constraints under quantifiable model parameter uncertainties can help improve the imaging and scanning quality of packaged micromirror systems.

[0004] Current detection and control schemes can be roughly divided into two categories: one is open-loop technology based on input-shaping and flatness-based technologies, but this technology is not robust to parameter changes caused by the MEMS device manufacturing process and is extremely susceptible to noise interference; the other is a closed-loop feedback method based on the inverse tracking framework, which relies on the available error output differential information. However, in very fast micro-nanodynamic processes, sensor noise is easily amplified by the differential link in the inverse tracking framework, which seriously affects the detection and control performance of the micro-photomechanical micromirror and may even ultimately cause the perception system based on the micro-photomechanical micromirror sensor to fail. Summary of the Invention

[0005] In view of the problems existing in the prior art, the purpose of the present invention is to provide an output detection and control method for a micro-opto-electromechanical micromirror, which can achieve effective asymptotic tracking of a reference trajectory by a micro-electromechanical torsional micromirror and efficiently guarantee the transient performance of the micromirror angle output during the tracking process.

[0006] In order to achieve the above object, the present invention adopts the following technical solutions:

[0007] A method for detecting and controlling an output of a micro-optical electromechanical micro-mirror, comprising:

[0008] Step 1: Based on the dynamic model of the micro-optical electromechanical micromirror, a research framework for the output regulation design of the output feedback mechanism is constructed to formulate a tracking control problem for the micromirror with transient performance constraints.

[0009] Step 2: Based on the output regulation design framework, an internal model is constructed and coordinate transformation is introduced to transform the transient performance constraint tracking problem of the micro-optical electromechanical micromirror into a transient performance constraint stability design problem of the augmented system, obtaining the augmented system in lower triangular form.

[0010] Step 3: Design a detection and control law for the augmented system in the lower triangular form. Use an adaptive learning mechanism to learn the relationship between the electromagnetic torque and the driving coefficient of the driving current. Combined with the barrier Lyapunov function and applying the Lyapunov stability theory, adjust the parameters of the detection and control law to effectively ensure the system stability and the transient performance of the micro-optical electromechanical micromirror output.

[0011] Furthermore, in step 1, the dynamic model of the micromirror is as follows

[0012]

[0013] where θ, J m ,B d ,K s ,T field (θ) represents the rotation angle, yaw angular velocity, yaw angular acceleration, moment of inertia, damping coefficient, angular spring constant and electromagnetic torque, respectively.

[0014] Furthermore, for the micro-optical electromechanical electromagnetic driven micromirror, T field (θ) = VBHcos(θ), where V is the volume of the magnetic film, B is the magnetic flux density, and H is the magnetic field strength. Thus, the system is as follows:

[0015]

[0016] For hard electromagnetic driven micromirrors, there is T field (θ)=K i ×i, where i is the driving current, K i It can be assumed to be an unknown constant, and the driving current i can be directly used as the control input u of the micromirror model, that is, let u = i, and let y = θ, The system can be further expressed as follows:

[0017]

[0018] Let Ω=(B d ,K s ,K i ,J m )and are the actual value and nominal value of the micromirror model parameter vector respectively, and we can get Where: ω represents the parameter change of the nominal value of the micromirror model.

[0019] Furthermore, in the output regulation design framework of the imaging scanning system based on the micro-optical electromechanical micromirror, the following external system is used to define the reference angle trajectory information v1(t) that the micromirror output angle needs to achieve effective tracking:

[0020]

[0021] in, a, b are constants related to the reference trajectory;

[0022] Define the following system

[0023]

[0024] The output detection control scheme formed within the output regulation research framework is summarized as: making the controlled deflection output angle y of the micromirror achieve asymptotic tracking of the given reference signal v1 with high transient performance, that is, ensuring the error and where k b (t) is the expected constraint range of the tracking error transient performance.

[0025] Furthermore, the augmented system in step 2 is constructed by introducing a dynamic filtering system and expanding the dynamic filtering system as follows:

[0026]

[0027] Where: λ can be any positive constant, ξ represents the filter state;

[0028] Combining the systems (5) and (6) and applying the following transformation

[0029]

[0030] The system can be obtained as follows:

[0031]

[0032] in:

[0033] According to the output regulation design framework, the zero-error steady-state information represented by (z(v,ω),y(v,ω),Ξ(v,ω),u(v,ω)) satisfies the following regulation equation,

[0034]

[0035] The process of solving for the steady-state values y(v,ω), z(v,ω), and Ξ(v,ω) is as follows:

[0036] Let z(v,ω)=Z(ω)v, Z(ω)=[Z 11 Z 12 ], then Z(ω)A=-Z(ω)+[G(ω)0], where: By simplifying the left and right sides of the formula, we can get

[0037]

[0038] Then use the following formula to solve Ξ(v,ω) in formula (9):

[0039]

[0040] The result is

[0041] Ξ(v,ω)=d 11 v1+d 12 v2 (31)

[0042] in:

[0043] definition The following formula is obtained:

[0044]

[0045] in: Ψ=

[10] , select a controllable matrix pair (M,N), where: M∈R 2×2 ,N∈R 2×1 , by substituting into the Sylvester equation TΦ-MT=NΨ, we can obtain the unique reversible matrix solution T;

[0046] Create the inner model as follows:

[0047]

[0048] Combining (8) and (14) we can get the augmented system.

[0049] Furthermore, the following coordinate transformation is performed on the augmented system:

[0050]

[0051] in: The system in lower triangular form is obtained

[0052]

[0053] in:

[0054] Furthermore, the following detection and control law is designed for system (16):

[0055]

[0056] in: and In the controller (17) is the adaptive learning parameter introduced to learn the driving coefficient relationship between electromagnetic torque and driving current, and k is the high gain dynamic introduced to deal with the uncertainty of micromirror model parameters; considering the constant selection property of the micromirror output error limit in practice, k is selected b (t) = L, where L is a positive constant. The output detection controller can be simplified into the following form:

[0057]

[0058] in: and

[0059] Further, step 3 includes,

[0060] Introducing the barrier Lyapunov function in is some normal quantity, It is a positive constant to be specified later, and the positive definite matrix P satisfies the Lyapunov equation PM+M T P = -I2, M is the Hurwitz matrix, I2 is the given positive definite symmetric unit matrix, and the time derivative of V1 can be calculated as

[0061]

[0062] remember Then there is

[0063]

[0064] Then set the controller (17) Substituting into the above equation, we can get:

[0065]

[0066] in

[0067] Since ω is within a compact set W, that is, ω∈W, there exists a positive constant and Satisfying g≥4 and l-3||d(ω)T -1 || 2 ≥1; definition Then there exists a smooth positive definite function and satisfy choose Available thus So, for all t≥0 we have

[0068]

[0069] Therefore, all states and derivatives of the closed-loop systems (6), (14) and (17) are bounded, and thus the system is stable. and where k b (t) is the expected constraint range of transient performance.

[0070] Furthermore, the method further includes step 4: verifying the effectiveness of the micro-opto-electromechanical detection control framework through experiments.

[0071] Furthermore, the verification process is as follows: the laser reflected by the micromirror is divided into two parts by a beam splitter, one part is collected by a position sensing detector; the other part is focused by an objective lens to scan the target object and is collected by the position sensing detector at the same time; the position sensing detector measures the position information of the micromirror, while the photodetector detects the intensity of the laser beam. The real-time controller is used to generate excitation signals and obtain sensor readings. The readout signals of the position sensing detector and the photodetector are sent to the FPGA pre-loaded with the development controller. The micromirror is driven to enable the laser to scan the target object. Whenever the laser beam scans the target object, the scattered laser light is collected by the photodetector. Then the position information obtained by the position sensing detector and the laser beam intensity detected by the photodetector are used to reconstruct the scanned target object.

[0072] In general, the present invention has the following advantages:

[0073] The present invention provides an output regulation control method based on a combination of an obstacle Lyapunov function and an adaptive learning mechanism, developing a high-performance detection and servo control scheme for a micro-electromechanical (MEMS) micromirror output with enhanced transient performance. The present invention utilizes the internal model principle to address the parameter uncertainty of the MEMS micromirror model and achieve asymptotic tracking of the micromirror output angle relative to a general reference trajectory. An adaptive learning mechanism is introduced to learn the coefficient relationship between the electromagnetic torque and the drive current. Combined with the obstacle Lyapunov function method, this method prevents tracking constraint violations of the micromirror angle output, enabling effective asymptotic tracking of the MEMS torsional micromirror relative to the reference trajectory. This method also effectively ensures the transient performance of the micromirror angle output during tracking, avoids potential collisions between the micromirror device and the physical structure, and improves the service life of the micromirror device. Furthermore, the present invention ensures that the servo feedback control scheme for the MEMS torsional micromirror is independent of the micromirror's angular velocity information, thereby improving the MEMS sensor system's immunity to external noise. Therefore, the detection and servo control strategy proposed in the present invention does not require an observer algorithm to obtain the angular velocity information of the micromirror for use in the feedback control channel, nor does it require the addition of an additional velocity sensor, thereby reducing hardware costs and shrinking the device volume of the micro-opto-electromechanical sensor system, which is conducive to further expanding the application scope of micro-electromechanical torsional micromirrors in optical imaging scanning and audio-visual perception systems. BRIEF DESCRIPTION OF THE DRAWINGS

[0074] Figure 1 This is a diagram of the output angle detection and control framework of the micro-opto-electromechanical micromirror according to an embodiment of the present invention.

[0075] Figure 2 This is a design diagram of the micro-optical electromechanical micromirror experimental platform according to an embodiment of the present invention.

[0076] Figure 3 This is a schematic diagram of the micro-optical electromechanical micro-mirror scanning application principle according to an embodiment of the present invention. DETAILED DESCRIPTION

[0077] The present invention will be described in further detail below.

[0078] The present invention provides an output regulation control method based on a combination of an obstacle Lyapunov function and an adaptive learning mechanism, which eliminates the requirement for measurement information of the angular velocity of a micro-optical electromechanical micromirror and effectively improves the high-precision scanning performance of an imaging scanning device based on a micro-optical electromechanical micromirror system. The method comprises the following steps:

[0079] Step 1: Based on the dynamic model of the micro-optical electromechanical micromirror, an output regulation design framework of the output feedback mechanism is constructed to formulate a tracking control problem for the micromirror with transient performance constraints.

[0080] Step 2: Based on the output regulation design framework, an internal model is constructed to transform the transient performance constraint tracking problem of the micro-opto-electromechanical micromirror into the transient performance constraint stability design problem of the augmented system. This transformation eliminates the requirement for the micromirror detection and control system to measure the micromirror's angular velocity. Simultaneously, an adaptive learning mechanism is introduced to learn the coefficient relationship between the electromagnetic torque and the drive current.

[0081] Step 3: Use Lyapunov stability theory to prove the stability of the augmented system and select control system parameters that can effectively guarantee the transient performance of the micro-optical electromechanical micromirror output;

[0082] Step 4: Build an experiment to verify the design scheme and verify the effectiveness of the micro-opto-electromechanical detection and control framework.

[0083] Specifically, each step is implemented as follows:

[0084] Step 1: The dynamic model of the micromirror is as follows:

[0085]

[0086] where θ, J, B, K, T field (θ) represents the rotation angle, yaw angular velocity, yaw angular acceleration, moment of inertia, damping coefficient, angular spring constant and electromagnetic torque, respectively.

[0087] For the micro-optical electromechanical electromagnetic driven micromirror, it can be seen that T field (θ) = VBHcos(θ), where V represents the volume of the magnetic film, B represents the magnetic flux density, and H is the magnetic field strength. Therefore, the system is as follows:

[0088]

[0089] Due to the electromagnetic torque T field (θ) is generated by driving the micromirror through a planar microcoil using a driving current i. Studies have shown that the driving current i is related to the electromagnetic torque T field (θ) is roughly linear, so T field (θ)=K i ×i, where K i It can be assumed to be an unknown constant, and then let y=θ, u=i, the system can be further expressed as follows:

[0090]

[0091] In the micro-manufacturing process of micro-optical electromechanical micromirrors, there are various factors that may cause the model parameter values to change. Therefore, let Ω = (B d ,K s ,K i ,Jm )and are the actual value and nominal value of the model parameter vector respectively. Then, let where ω represents the change of the parameter from its nominal value.

[0092] The imaging scanning system based on the micro-optical electromechanical micromirror requires that the output angle of the micromirror can achieve high transient performance asymptotic tracking of a given reference trajectory. Within the output regulation design framework, the following external system can be used to define the reference angle trajectory information v1(t) that the micromirror output angle needs to achieve effective tracking:

[0093]

[0094] Among them, a and b are constants related to the reference trajectory.

[0095] Define the following system

[0096]

[0097] e=y-v1 (43)

[0098] In order to make the controlled deflection output angle y of the micromirror achieve asymptotic tracking of the given reference signal v1 with high transient performance, it should be ensured that and where k b (t) is the expected constraint range of transient performance.

[0099] Step 2: Introduce the filtering system, transform the system (5) into the lower triangular form, construct the internal model, and transform the transient performance constraint tracking problem of the micro-optical electromechanical micromirror into the transient performance constraint stability design problem of the augmented system.

[0100] First, the dynamic filtering system is expanded as follows

[0101]

[0102] Wherein λ can be any positive constant, and the present invention selects λ=1.

[0103] Combining the systems (5) and (6) and applying the following transformation

[0104]

[0105] The system can be obtained as follows:

[0106]

[0107] e=y-v1 (46)

[0108] in:

[0109] According to the output regulation design framework, the zero-error steady-state information represented by (z(v,ω),y(v,ω),Ξ(v,ω),u(v,ω)) satisfies the following regulation equation

[0110]

[0111] 0=y(v)-v1 (47)

[0112] The process of solving for the steady-state values y(v,ω), z(v,ω), and Ξ(v,ω) is as follows:

[0113] Let z(v,ω)=Z(ω)v, where: Z(ω)=[Z 11 Z 12 ], then Z(ω)A=-Z(ω)+[G(ω) 0], By simplifying the left and right sides of the formula, we can get

[0114]

[0115] Then use the following formula to solve Ξ(v,ω)

[0116]

[0117] The result is

[0118] Ξ(v,ω)=d 11 v1+d 12 v2 (50)

[0119] in:

[0120] definition The following formula is obtained:

[0121]

[0122] Ξ(v,ω)=Ψτ(v,ω) (51)

[0123] and Ψ=[1 0], select the controllable pair M∈R 2×2 ,N∈R 2×1 Substituting the Sylvester equation TΦ-MT=NΨ, we can obtain the unique reversible matrix solution T.

[0124] The internal model is established as follows:

[0125]

[0126] Combining (8) and (14) we can get the augmented system. The following coordinate transformation is performed on the augmented system

[0127]

[0128] in: The system can be obtained in lower triangular form

[0129]

[0130] in:

[0131] In order to ensure the stability of system (16), the following detection and control law is designed:

[0132]

[0133] in: and

[0134] In the controller (17) is the adaptive learning parameter introduced to learn the coefficient relationship between electromagnetic torque and driving current; It is mainly used to prevent the output angle of the micromirror from going out of bounds, so as to achieve better transient performance. However, considering that the constraint boundary k b (t) becomes strict, which may require a larger control input action, resulting in input saturation. To solve this problem, k can be selected b (t) = L, thus simplifying the controller into the following form:

[0135]

[0136] in: and

[0137] Step 3: Stability Analysis

[0138] Introducing the barrier Lyapunov function in is a positive constant. Therefore, the time derivative of V1 can be calculated as

[0139] remember Then there is

[0140]

[0141] Then set the controller (17) Substituting into the above equation, we can get:

[0142]

[0143] in

[0144] Since ω is within a compact set W, that is, ω∈W, there exists a positive constant and Satisfying g≥4 and l-3||d(ω)T -1 || 2 ≥1. Definition Then there exists a positive, smooth function and satisfy choose And satisfy Can get So, for all t≥0

[0145] Both

[0146]

[0147] Therefore, all states and derivatives of the closed-loop systems (6), (14) and (17) are bounded, and thus the system is stable. and where k b (t) is the expected constraint range of transient performance. Figure 1 This is the framework diagram of the entire detection and control scheme.

[0148] Step 4: In this step, an experimental platform will be built to verify the detection and control scheme proposed in this invention.

[0149] The main components of the experimental platform include HeNe laser, position sensing detector (PSD), NIPXI 7852R real-time controller, voltage controlled current amplifier (VCCA) circuit and micro-optical electromechanical micromirror, such as Figure 2 The control algorithm was programmed using LabVIEW software, with code compiled using Xilinx compilation tools. The VCCA circuit consists of an operational amplifier, N-channel and P-channel MOSFETs, and several resistors. This circuit uses a DC voltage source to drive the N-channel and P-channel MOSFETs, providing current amplification.

[0150] Figure 3The schematic diagram of a scanning system based on a micro-optical electromechanical micromirror is shown. The target to be scanned is a metal grid pattern. The laser light reflected by the micromirror is split into two parts by a beam splitter. One part is collected by the PSD. The other part is focused by the objective lens, scans the target object, and is collected by the photodetector (PD) at the same time. The PSD measures the position information of the micromirror, while the PD detects the intensity of the laser beam. The PXI 7852R real-time controller is used to generate excitation signals and obtain sensor readings. The readout signals of the PSD and PD are sent to the FPGA pre-loaded with the development controller. The micromirror is driven to enable the laser to scan across the target object. Whenever the laser beam scans across the target object (metal grid pattern), the scattered laser light is collected by the PD. The position information obtained by the PSD and the intensity of the laser beam detected by the PD are then recorded in real time. In this regard, the position information obtained by the PSD and the intensity signal on the PD are displayed and stored in the host computer for reconstruction of the scanned target. It is a series of peaks and valleys due to the reflection of the white and black stripes of the metal grid pattern. Figure 3 In this paper, the position signal measured by PSD and the light intensity signal of PD are combined to reconstruct the image of the metal grid pattern.

[0151] Experimental results show that the micro-opto-electromechanical micromirror detection and tracking controller with enhanced transient performance designed by us can avoid measuring the angular velocity information of the micromirror, improve the reliability and durability of the micromirror, and effectively enhance the scanning performance of micromirror-based optical sensors and imaging devices.

[0152] The above embodiments are preferred implementation modes of the present invention, but the implementation modes of the present invention are not limited to the above embodiments. Any other changes, modifications, substitutions, combinations, and simplifications that do not deviate from the spirit and principles of the present invention should be considered as equivalent replacement methods and are included in the scope of protection of the present invention.

Claims

1. A method for detecting and controlling the output of a micro-optical electromechanical micromirror, characterized in that: include Step 1: Based on the dynamic model of the micro-optical electromechanical micromirror, a research framework for the output regulation design of the output feedback mechanism is constructed to formulate a tracking control problem for the micromirror with transient performance constraints. Step 2: Based on the output regulation design framework, an internal model is constructed and coordinate transformation is introduced to transform the transient performance constraint tracking problem of the micro-optical electromechanical micromirror into a transient performance constraint stability design problem of the augmented system, obtaining the augmented system in lower triangular form. Step 3: Design a detection and control law for the augmented system in the lower triangular form. Use an adaptive learning mechanism to learn the relationship between the electromagnetic torque and the driving coefficient of the driving current. Combined with the barrier Lyapunov function and applying the Lyapunov stability theory, adjust the parameters of the detection and control law to effectively ensure the system stability and the transient performance of the micro-optical electromechanical micromirror output.

2. The output detection control method according to claim 1, wherein: In step 1, the dynamic model of the micromirror is as follows where θ, J m ,B d ,K s ,T field (θ) represents the rotation angle, yaw angular velocity, yaw angular acceleration, moment of inertia, damping coefficient, angular spring constant and electromagnetic torque, respectively.

3. The output detection control method according to claim 2, wherein: For the micro-optical electromechanical electromagnetic driven micromirror, T field (θ) = VBHcos(θ), where V is the volume of the magnetic film, B is the magnetic flux density, and H is the magnetic field strength. Thus, the system is as follows: For hard electromagnetic driven micromirrors, there is T field (θ)=K i ×i, where i is the driving current, K i It can be assumed to be an unknown constant, and the driving current i can be directly used as the control input u of the micromirror model, that is, let u = i, and let y = θ, The system can be further expressed as follows: Let Ω=(B d ,K s ,K i ,J m )and are the actual value and nominal value of the micromirror model parameter vector respectively, and we can get Where: ω represents the parameter change of the nominal value of the micromirror model.

4. The output detection control method according to claim 3, wherein: In the output regulation design framework of the imaging scanning system based on the micro-optical electromechanical micromirror, the following external system is used to define the reference angle trajectory information v1(t) required for effective tracking of the micromirror output angle: in, a, b are constants related to the reference trajectory; Define the following system The output detection control scheme formed within the output regulation research framework is summarized as: making the controlled deflection output angle y of the micromirror achieve asymptotic tracking of the given reference signal v1 with high transient performance, that is, ensuring the error and where k b (t) is the expected constraint range of the tracking error transient performance.

5. The output detection control method according to claim 4, wherein: The augmented system in step 2 is constructed by introducing a dynamic filtering system and expanding the dynamic filtering system as follows: Where: λ can be any positive constant, ξ represents the filter state; Combining the systems (5) and (6) and applying the following transformation The system can be obtained as follows: in: According to the output regulation design framework, the zero-error steady-state information represented by (z(v,ω),y(v,ω),Ξ(v,ω),u(v,ω)) satisfies the following regulation equation, The process of solving for the steady-state values y(v,ω), z(v,ω), and Ξ(v,ω) is as follows: Let z(v,ω)=Z(ω)v, Z(ω)=[Z 11 Z 12 ], then Z(ω)A=-Z(ω)+[G(ω)0], where: By simplifying the left and right sides of the formula, we can get Then use the following formula to solve Ξ(v,ω) in formula (9): The result is Ξ(v,ω)=d 11 v1+d 12 v2 (12) in: definition The following formula is obtained: in: Ψ=[10], select a controllable matrix pair (M,N), where: M∈R 2×2 ,N∈R 2×1 , by substituting into the Sylvester equation TΦ-MT=NΨ, we can obtain the unique reversible matrix solution T; Create the inner model as follows: Combining (8) and (14) we can get the augmented system.

6. The output detection control method according to claim 5, wherein: Perform the following coordinate transformation on the augmented system in: The system in lower triangular form is obtained in:

7. The output detection control method according to claim 6, wherein: The following detection and control law is designed for system (16): in: and In the controller (17) is the adaptive learning parameter introduced to learn the driving coefficient relationship between electromagnetic torque and driving current, and k is the high gain dynamic introduced to deal with the uncertainty of micromirror model parameters; considering the constant selection property of the micromirror output error limit in practice, k is selected b (t) = L, where L is a positive constant. The output detection controller can be simplified into the following form: in: and 8. The output detection control method according to claim 7, wherein: Step 3 includes, Introducing the barrier Lyapunov function in is some normal quantity, It is a positive constant to be specified later, and the positive definite matrix P satisfies the Lyapunov equation PM+M T P = -I2, M is the Hurwitz matrix, I2 is the given positive definite symmetric unit matrix, and the time derivative of V1 can be calculated as remember Then there is Then set the controller (17) Substituting into the above equation, we can get: in Since ω is within a compact set W, that is, ω∈W, there exists a positive constant and Satisfying g≥4 and l-3||d(ω)T -1 || 2 ≥1; definition Then there exists a smooth positive definite function and satisfy choose Available thus So, for all t≥0 we have Therefore, all states and derivatives of the closed-loop systems (6), (14) and (17) are bounded, and thus the system is stable. where k b (t) is the expected constraint range of transient performance.

9. The output detection control method according to claim 1, wherein: It also includes step 4: verifying the effectiveness of the micro-opto-electromechanical detection and control framework through experiments.

10. The output detection control method according to claim 9, wherein: The verification process is as follows: the laser reflected by the micromirror is split into two parts by a beam splitter. One part is collected by a position sensor detector; the other part is focused by an objective lens to scan the target object and is also collected by the position sensor detector. The position sensing detector measures the position information of the micromirror, while the photodetector detects the intensity of the laser beam. A real-time controller is used to generate excitation signals and obtain sensor readings. The readout signals of the position sensing detector and the photodetector are sent to the FPGA pre-loaded with the development controller. The micromirror is driven to enable the laser to scan the target object. Whenever the laser beam scans the target object, the scattered laser light is collected by the photodetector. The position information obtained by the position sensing detector and the intensity of the laser beam detected by the photodetector are then used to reconstruct the scanned target object.

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