Optical resonator automatic collimation system based on cascade feedback and PID control

Abstract

The application relates to the field of optical systems and automatic control technology thereof, in particular to an optical resonant cavity automatic collimation system based on cascade feedback and PID control, which comprises a laser emission module, an optical resonant cavity, a data acquisition module, a data analysis module and an automatic control module; the data acquisition module comprises a light spot analyzer and a photoelectric detector, the light spot analyzer is used for collecting a Gaussian fitting intensity signal in an optical path of the optical resonant cavity, the photoelectric detector is used for collecting an interference light intensity signal in the optical path of the optical resonant cavity, the data analysis module performs cascade processing on the Gaussian fitting intensity signal and the interference light intensity signal, and fine adjustment and feedback control of the optical path of the optical resonant cavity are realized through the automatic control module. The double-layer adjustment strategy of cascade feedback and PID control is innovatively adopted, manual operation errors are significantly reduced, the consistency and reliability of optical path regulation and control are improved, and the problems of insufficient manual adjustment precision and low efficiency in the prior art are solved.

Description

Technical Field

[0001] This invention relates to the field of optical systems and their automatic control technology, specifically an automatic collimation system for optical resonators based on cascaded feedback and PID control. This system is mainly used for the automatic collimation and optical path adjustment of high-precision optical resonators, and is widely applied in laser technology, quantum optics, optical communication, laser medicine, and precision measurement. Background Technology

[0002] Optical resonant cavity technology plays a crucial role in high-precision measurement fields such as gravitational wave detection and atomic clocks. Its core lies in creating a closed optical path using mirrors to achieve multiple reflections and amplification of light, thereby enhancing the directionality and monochromaticity of laser light. Precision motion control technology has evolved from early mechanical speed controllers to modern nanometer-level displacement control, integrating PID control algorithms, intelligent control algorithms (such as neural networks and fuzzy control), and high-precision sensors (such as grating rulers and laser interferometers). This enables sub-micron or even sub-femtometer-level motion adjustment, providing support for the precise manipulation of optical components.

[0003] However, existing technologies still have significant bottlenecks:

[0004] Poor environmental adaptability: Environmental factors such as temperature fluctuations and mechanical vibrations can easily cause minute displacements or deformations of optical components, affecting the stability of the optical resonant cavity;

[0005] System integration is difficult and costly: Precision motion control and interferometer systems have complex structures, are difficult to integrate, and are expensive, which limits their application in cost-sensitive fields.

[0006] Limitations of control algorithms: Traditional control algorithms are not adaptable enough to complex nonlinear systems and are difficult to cope with disturbances under extreme conditions.

[0007] To address these issues, the combination of cascaded feedback and PID control technologies has become an important direction. Cascaded feedback forms a closed-loop control through the collaboration of multiple modules, monitoring the optical path status in real time and making dynamic adjustments; the PID control algorithm, through the coordination of proportional, integral, and derivative components, achieves precise correction of optical path deviations. Simultaneously, the application of image processing technology and automated control tools has further promoted the automation and intelligence of optical path systems, providing technical support for the realization of high-precision optical systems. Summary of the Invention

[0008] To address the problems of insufficient precision, low efficiency, and difficulty in maintaining stable performance under complex environments during manual adjustment of optical resonators in existing optical path systems, this invention combines the need for automatic collimation of optical resonators with cascaded feedback control technology, designing an automatic collimation system for optical resonators based on cascaded feedback and PID control. This system automatically acquires the Gaussian fitted intensity signal of the light spot and the interference light intensity signal, and uses a PID control algorithm to achieve precise adjustment and feedback optimization of optical components. This simplifies the optical path adjustment process, improves the stability and collimation accuracy of the optical path, and provides reliable technical support for high-precision optical experiments and applications. This work lays the foundation for the intelligent and integrated development of optical systems.

[0009] To achieve the above objectives, the present invention is implemented through the following technical solution: an automatic collimation system for an optical resonator based on cascaded feedback and PID control, comprising a laser emission module, an optical resonator, a data acquisition module, a data analysis module, and an automatic control module; the data acquisition module includes a spot analyzer and a photodetector, the spot analyzer is used to acquire the Gaussian fitting intensity signal in the optical path of the optical resonator, the photodetector is used to acquire the interference light intensity signal in the optical path of the optical resonator, the data analysis module performs cascaded processing on the Gaussian fitting intensity signal and the interference light intensity signal, and the automatic control module realizes fine adjustment and feedback control of the optical path of the optical resonator.

[0010] The aforementioned automatic collimation system for optical resonator based on cascaded feedback and PID control:

[0011] The laser emitting module outputs near-infrared laser from a fiber laser, which is collimated by a collimator and then injected into the optical resonant cavity.

[0012] The optical resonant cavity forms a stable optical circuit with four mirrors. The first mirror is the input cavity mirror, the second mirror is the output cavity mirror, and the third and fourth mirrors are respectively mounted on an optical rotation adjustment frame. The optical rotation adjustment frame controls the tilt angle of the third and fourth mirrors in the vertical and horizontal directions through two adjusting screw pairs in the pitch and yaw directions, thereby achieving optical path alignment.

[0013] The data acquisition module includes a spot analyzer and a photodetector. After the laser is output from the optical resonant cavity by the second reflecting mirror, it continues to be incident on the beam splitter and is split into two. One part is incident on the spot analyzer to form a Gaussian fitted intensity signal, and the other part is incident on the photodetector to form an interference light intensity signal.

[0014] The data analysis module performs cascade processing on the Gaussian fitted intensity signal and the interference light intensity signal. The core function of this module is implemented by a Python script deployed on the computer, which specifically undertakes the core tasks of real-time signal processing, PID algorithm calculation and control command generation.

[0015] The automatic control module is mainly responsible for receiving Python instructions from the data analysis module and driving the Picomotor controller to perform actions. The motor is connected to the pitch adjustment thread pair and yaw adjustment thread pair of the optical rotation adjustment frame through a flexible coupling. The automatic control module receives the steering, step size and motor switching instructions output by the data analysis module, and adjusts each motor in sequence to achieve automatic collimation and stable closed-loop control of the optical path.

[0016] The aforementioned automatic collimation system for optical resonant cavities based on cascaded feedback and PID control utilizes a two-stage control strategy for cascaded processing of the data analysis module. In the initial coarse adjustment stage, the module calculates the difference in peak Gaussian fitting intensity before and after motor adjustment based on the Gaussian fitting intensity signal and determines the motor direction by judging its sign. It then calculates the coarse adjustment step size using a PID algorithm, and simultaneously judges convergence based on the change in the difference and generates a motor switching command to complete the optical path pre-alignment. In the secondary fine adjustment stage, the module calculates the difference in peak interference contrast before and after motor adjustment based on the interference intensity signal and determines the motor direction by judging its sign. It then calculates the fine adjustment step size using a PID algorithm, judges convergence based on the change in the difference and generates a motor switching command, until the interference contrast reaches a set threshold, ultimately achieving precise optical path adjustment.

[0017] The aforementioned automatic collimation system for optical resonators based on cascaded feedback and PID control achieves optical path pre-alignment based on Gaussian fitting intensity signals during the initial coarse adjustment stage. The beam shape is displayed in real time by the BeamHereSlit software built into the beam analyzer, and the Gaussian fitting result is obtained through the software data interface. First, the current peak value of the Gaussian fitting intensity H1 is acquired, and the motor is driven to move an initial step size L according to a preset direction D (D=+1 indicates forward rotation, D=-1 indicates reverse rotation). Then, the peak value of the Gaussian fitting intensity H after the movement is read. 1' Calculate the difference e1=H1-H1'. Determine the motor direction by judging the sign of the difference e1. If e1>0, reverse the direction D to correct the motor direction; otherwise, maintain the current direction. After determining the correct direction, judge the convergence according to Δe1=e1-e0, where e0 is a preset minimum value. When Δe1>0, input the current difference e1 into the PID controller. Calculate the coarse adjustment step size of the motor by dynamically adjusting the proportional, integral, and derivative parameters. When Δe1≤0, generate a command to switch to the next motor, ultimately achieving optical path pre-alignment.

[0018] In the secondary fine-tuning stage, the acquired interference light intensity signal is digitized by an analog-to-digital converter and transmitted to the data analysis module. Then, the DC bias and AC amplitude of the time-domain voltage signal are extracted to calculate the interference contrast. First, the current interference contrast K1 is obtained, and the motor is driven to move an initial step size L in the set direction D. The interference contrast K1' after the movement is read, and the difference e2=K1-K1' is calculated. The direction of the motor is determined by judging the sign of the difference e2. If e2>0, the direction D is reversed to correct the motor direction; otherwise, the current direction remains unchanged. After determining the correct direction, convergence is judged according to Δe2=e2-e0. When Δe2>0, the current difference e2 is input to the PID controller. The fine-tuning step size of the motor is calculated by dynamically adjusting the proportional, integral, and derivative parameters. When Δe2≤0, a command to switch to the next motor is generated until the interference contrast reaches the set standard, and finally, the precise alignment of the optical path is achieved.

[0019] The aforementioned automatic collimation system for optical resonant cavities based on cascaded feedback and PID control involves a Picomotor controller in the automatic control module. Motors M1 and M4 are connected to the pitch adjustment threads of the third and fourth reflectors via flexible couplings, respectively. Motors M2 and M3 are connected to the yaw adjustment threads of the third and fourth reflectors, respectively. The automatic control module adjusts the reflectors sequentially according to motor numbers M1 to M4. The system uses the difference e1 between the Gaussian fitting intensity peaks of the light spot and the difference e2 between the interference contrasts as the core judgment criteria, generating the step size for each motor through the PID controller. After each adjustment, the change in difference Δe is calculated in real time, and Δe ≤ 0 is used as the condition for exiting the current motor adjustment cycle.

[0020] The automatic collimation system for optical resonant cavities based on cascaded feedback and PID control is implemented by the following steps:

[0021] Step 1: Build the hardware system, using a fiber laser as the light source, constructing an optical resonant cavity through four mirrors, and connecting a data acquisition module, including connecting a spot analyzer to the data analysis module, connecting a photodetector to the data analysis module through an analog-to-digital converter, and connecting the four motors of the Picomotor controller in the automatic control module to the adjusting thread pairs on the optical rotation adjustment brackets of the third and fourth mirrors respectively, to complete the hardware connection and initialization settings;

[0022] Step 2: Start the data acquisition module, and collect the Gaussian fitting intensity signal and interference light intensity signal through the spot analyzer and photodetector respectively. The data analysis module receives and displays the signals, and the automatic acquisition and storage of signals is realized through Python scripts.

[0023] Step 3: The data analysis module processes the acquired signals. For Gaussian fitted intensity signals, the BeamHere analysis software is used to obtain Gaussian fitted curves in the X-axis and Y-axis contour windows, and the trend of peak intensity change of the curves is monitored in real time. For interference light intensity signals, the signals are digitized by an analog-to-digital converter and then transmitted to the data analysis module to extract interference contrast through time-domain voltage amplitude analysis.

[0024] Step 4: In the initial coarse adjustment stage, the Python script inputs the difference e1 between the current peak value of the Gaussian fitting intensity and the peak value after motor adjustment into the PID controller. The PID controller then outputs the coarse adjustment step size for the motor, automatically determining the motor direction based on the sign of e1, and generating cascaded adjustment instructions in the order of M1 to M4, which are sent to the C# program in real time. Upon receiving the instructions, the C# program drives the corresponding Picomotor motor to perform the adjustment action, calculating the change in difference Δe1 after each adjustment, with Δe1 ≤ 0 as the condition for exiting the current motor adjustment cycle. After all motors have completed adjustment, the system enters the secondary fine adjustment stage. The difference e2 between the current interference contrast and the interference contrast after motor adjustment is input into the PID controller, which then outputs the fine adjustment step size for the motor. The system automatically determines the motor direction based on the sign of e2, continuing to cascade the adjustment of each motor in the order of M1 to M4. After each adjustment, the system calculates the change in difference Δe2, with Δe2 ≤ 0 as the condition for exiting the current motor adjustment cycle, ultimately achieving precise optimization and control of the optical path.

[0025] Step 5: After each adjustment, the system reads back the Gaussian fitting strength and interference contrast in real time through Python. If the deviation of the Gaussian fitting strength is less than the set threshold, the coarse adjustment is determined to be completed. If the interference contrast reaches or exceeds the set threshold, the fine adjustment is determined to be completed. The judgment result is fed back from Python to the C# program to control whether the process enters the next stage.

[0026] Step 6: After all optical components have completed coarse and fine two-stage adjustment, the system outputs the final interference contrast and the step size and direction data of the motor rotation through Python, generating an adjustment log; the C# program saves the PID controller configuration parameters and exits the control loop to achieve long-term stable locking of the optical path.

[0027] Compared with the prior art, the present invention has the following advantages:

[0028] This invention innovatively employs a two-layer adjustment strategy combining cascaded feedback and PID control: In the initial coarse adjustment stage, optical path pre-alignment is rapidly achieved based on the intensity of the Gaussian fitting of the light spot. By calculating the peak difference of the Gaussian fitting intensity and inputting it into the PID controller, combined with the steering parameter D, the initial step size adjustment and steering adjustment are generated, shortening the pre-alignment time. In the secondary fine adjustment stage, high-precision optimization is performed based on interference contrast, using PID control to improve the interference contrast to over 80%. The synergistic effect of these two stages ensures adjustment efficiency and solves the problems of low accuracy and poor efficiency in complex nonlinear systems caused by traditional algorithms.

[0029] The system uses Python scripts to automatically collect, analyze, and store data, and drives a Picomotor controller via a C# program to automatically adjust the position and angle of optical components without manual intervention. During the adjustment process, the system can automatically determine the conditions for coarse adjustment convergence and fine adjustment completion, and generate adjustment logs, significantly reducing human error, improving the consistency and reliability of optical path control, and solving the problems of insufficient precision and low efficiency in manual adjustment in existing technologies. Attached Figure Description

[0030] Figure 1 This is a schematic diagram of an automatic collimation system for an optical resonant cavity based on cascaded feedback and PID control.

[0031] Figure 2 This is a flowchart illustrating the implementation method of an automatic collimation system for an optical resonant cavity based on cascaded feedback and PID control. Detailed Implementation

[0032] To facilitate understanding of the present invention, a more comprehensive description will be provided below. However, the present invention can be implemented in many different forms and is not limited to the embodiments described herein. Rather, these embodiments are provided to provide a thorough and complete understanding of the disclosure of the present invention. Example

[0033] like Figure 1 As shown, the automatic collimation system for optical resonators based on cascaded feedback and PID control includes a laser emission module, a four-mirror optical resonator, a data acquisition module, a data analysis module, and an automatic control module.

[0034] The laser emitting module outputs a near-infrared laser with a center wavelength of 780nm from a fiber laser, which is collimated by a collimator and then injected into the four-mirror optical resonant cavity.

[0035] The four-mirror optical resonant cavity forms a stable optical circuit with four mirrors. The first mirror is the input mirror, and the second mirror is the output mirror. Both the first and second mirrors employ a double-layer design: a high-transmission film is coated on the front side facing the laser injection direction, while a high-reflectivity film is coated on the back side facing away from the laser injection direction. The third and fourth mirrors are both high-reflectivity mirrors and are mounted on optical rotation adjustment frames. The optical rotation adjustment frames control the tilt angle of the mirrors in the vertical and horizontal directions through two precision adjusting screw pairs in the pitch and yaw directions, thereby achieving optical path alignment.

[0036] The data acquisition module consists of a slit-type spot analyzer and a photodetector. The laser is output from the second reflecting mirror into the four-mirror optical cavity and then continues to be incident on the beam splitter and split into two. One part is incident on the spot analyzer to form a Gaussian fitted intensity signal, and the other part is incident on the photodetector to form an interference light intensity signal.

[0037] The data analysis module cascades the Gaussian fitted intensity signal and the interference light intensity signal, and optimizes the optical path through a two-stage control strategy. In the initial coarse adjustment stage, based on the Gaussian fitted intensity signal, the module calculates the difference in peak Gaussian fitted intensity before and after motor adjustment and determines its sign to determine the motor direction. It then uses a PID algorithm to calculate the coarse adjustment step size, and judges convergence based on the change in the difference, generating a motor switching command to complete the optical path pre-alignment. In the secondary fine adjustment stage, based on the interference light intensity signal, the module calculates the difference in peak interference contrast before and after motor adjustment and determines its sign to determine the motor direction. It then uses a PID algorithm to calculate the fine adjustment step size, judges convergence based on the change in the difference, and generates a motor switching command until the interference contrast reaches a set threshold, ultimately achieving precise optical path adjustment.

[0038] The automatic control module receives steering, step size, and motor switching commands output by the data analysis module, and drives the four motor actuators of the Picomotor controller: motors M1 and M4 are connected to the pitch adjustment threaded pairs of the third and fourth reflectors respectively through flexible couplings, and motors M2 and M3 are connected to the yaw adjustment threaded pairs of the third and fourth reflectors respectively, forming a four-channel drive system. The motors are cascaded and adjusted in sequence to finally achieve automatic collimation and stable closed-loop control of the optical path.

[0039] The system forms a closed-loop feedback circuit through a cascaded feedback control mechanism, which monitors and adjusts the optical path status in real time to ensure the precise pointing and stability of the optical path.

[0040] In this embodiment, the Picomotor controller establishes a physical communication connection with the computer via a USB interface. An automatic control module developed using C# is responsible for sending digital commands to the controller to control the motion of the four motors, including setting forward and reverse directions and adjusting the step size per run. In terms of the drive mechanism, the computer sends digital commands to the Picomotor controller, which then analyzes these commands to generate a specific high-voltage drive waveform. This waveform, based on the voltage timing principle of piezoelectric ceramics, precisely controls the motors to achieve nanometer-level stepping motion, enabling fine adjustment and adaptive control of the optical path.

[0041] This system uses a closed-loop Picomotor controller combined with a PID control algorithm to achieve fully automated adjustment of the optical rotation adjustment frame angle. For example... Figure 2 As shown, the method for automatically adjusting the optical path in this system includes the following steps:

[0042] Step 1: Experimental System Initialization Phase. First, the fiber laser, spot analyzer, photodetector, and Picomotor controller are integrated into the optical path system. The fiber laser output beam is coupled into the four-mirror optical resonator through a collimator. The computer identifies and initializes each hardware device. Specific parameter settings include: establishing a cyclic adjustment sequence for motor numbers M (M=1 to M=4 correspond to four adjustment motors), initializing motion parameters (initial step size L=10, initial direction D=+1, where the polarity of D defines the motor direction, +1 for forward rotation and -1 for reverse rotation), and setting a minimal value e0 as the dynamic convergence criterion threshold. This configuration ensures that when the system enters the automatic adjustment cycle, it can achieve closed-loop control based on spot analysis data, gradually approaching the optimal optical path alignment state through iterative calculations.

[0043] Step 2: The beam spot analyzer first acquires the Gaussian fitting intensity peak value H1 of the current beam. Then, the drive motor M moves an initial step length L according to the preset direction D and acquires a new Gaussian fitting intensity peak value H1'. The difference between the two peak values ​​is calculated as e1=H1-H1' and its change Δe1=e1-e0. If e1>0, it indicates that the peak value is decreasing and the motor rotation direction is incorrect. At this time, the motor rotation direction D is reversed (D=-1) and readjusted. If e1≤0, the change of Δe1 is further judged: when Δe1>0, the current difference e1 is input into the PID controller to calculate a new coarse adjustment step length and continue to adjust. When Δe1<0, it indicates that the current motor adjustment has reached the optimal state. At this time, the system switches to the next motor and repeats the above adjustment process. This cycle continues to run until all motors (motors M1 to M4) have completed the adjustment and Δe1 is less than zero. The system determines that the coarse adjustment process is complete.

[0044] Step 3: After coarse adjustment, the beam enters the photodetector to detect the interference signal in real time and converts it into voltage data. The initial interference contrast K1 is calculated through time-domain voltage amplitude analysis. The target interference contrast threshold K0 = 80% and the minimum value e0 are set as the dynamic convergence criterion thresholds. The entire adjustment process uses the real-time detected interference contrast as the core feedback index. The photodetector detects the current interference light intensity signal in real time and calculates the current interference contrast K1. Then, the drive motor M moves an initial step size L according to the preset direction D and re-detects and calculates the new interference contrast K1'. The difference between the two interference contrasts, e2 = K1 - K1', and its change Δe2 = e2 - e0, are calculated. If e2 > 0, it indicates that the interference contrast has decreased and the motor rotation direction is incorrect. At this time, the motor rotation direction D is reversed (D = -1) and readjusted. If e2 ≤ 0, the change of Δe2 is further judged: when Δe2 > 0, the current difference e2 is input into the PID controller to calculate a new fine-tuning step size and continue to adjust. When Δe2 < 0, it indicates that the current motor adjustment has reached the optimal state. At this time, the system switches to the next motor and repeats the above adjustment process. This cycle continues to run until all motors (motors M1 to M4) have completed the adjustment and the interference contrast K reaches or exceeds the target threshold K0 = 80%. At this time, the system determines that the fine-tuning process is complete.

[0045] Step 4: When all channels reach the preset accuracy, the system writes the final interference contrast, lens angle and PID controller configuration parameters into the log and saves the configuration. Then it exits the control program to achieve long-term stable locking of the optical path.

[0046] Contents not described in detail in this specification are prior art known to those skilled in the art. Although illustrative specific embodiments of the invention have been described above to facilitate understanding by those skilled in the art, it should be understood that the invention is not limited to the scope of the specific embodiments. Various modifications are readily apparent to those skilled in the art as long as they fall within the spirit and scope of the invention as defined and determined by the appended claims, and all inventions utilizing the concept of this invention are protected.

Claims

1. An automatic collimation system for an optical resonant cavity based on cascaded feedback and PID control, characterized in that: It includes a laser emission module, an optical resonant cavity, a data acquisition module, a data analysis module, and an automatic control module. The data acquisition module includes a spot analyzer and a photodetector. The spot analyzer is used to acquire the Gaussian fitting intensity signal in the optical path of the optical resonant cavity, and the photodetector is used to acquire the interference light intensity signal in the optical path of the optical resonant cavity. The data analysis module performs cascade processing on the Gaussian fitting intensity signal and the interference light intensity signal. The automatic control module realizes fine adjustment and feedback control of the optical path of the optical resonant cavity. The laser emitting module outputs near-infrared laser from a fiber laser, which is collimated by a collimator and then injected into the optical resonant cavity. The optical resonant cavity forms a stable optical circuit with four mirrors. The first mirror is the input cavity mirror, the second mirror is the output cavity mirror, and the third and fourth mirrors are respectively mounted on an optical rotation adjustment frame. The optical rotation adjustment frame controls the tilt angle of the third and fourth mirrors in the vertical and horizontal directions through two adjusting screw pairs in the pitch and yaw directions, thereby achieving optical path alignment. The data acquisition module includes a spot analyzer and a photodetector. After the laser is output from the optical resonant cavity by the second reflecting mirror, it continues to be incident on the beam splitter and is split into two. One part is incident on the spot analyzer to form a Gaussian fitted intensity signal, and the other part is incident on the photodetector to form an interference light intensity signal. The data analysis module performs cascade processing on the Gaussian fitted intensity signal and the interference light intensity signal. In the automatic control module, the motor is connected to the pitch adjustment thread pair and yaw adjustment thread pair of the optical rotation adjustment frame through a flexible coupling. The automatic control module receives the steering, step size and motor switching commands output by the data analysis module, and adjusts each motor in sequence to achieve automatic collimation and stable closed-loop control of the optical path. The cascaded processing of the data analysis module is achieved through a two-level control strategy. In the initial coarse adjustment stage, the module is based on the Gaussian fitting intensity signal. It calculates the difference between the peak values ​​of the Gaussian fitting intensity before and after the motor adjustment and determines its positive or negative value to determine the motor direction. It also calculates the coarse adjustment step size using the PID algorithm, and judges the convergence based on the change in the difference and generates a motor switching command to complete the optical path pre-alignment. In the secondary fine-tuning stage, the module calculates the peak difference of interference contrast before and after motor adjustment based on the interference light intensity signal and determines the direction of motor rotation by judging its positive or negative value. It then calculates the fine-tuning step size using a PID algorithm, judges the convergence based on the change in the difference, and generates a motor switching command until the interference contrast reaches the set threshold, ultimately achieving precise adjustment of the optical path.

2. The automatic collimation system for optical resonant cavities based on cascaded feedback and PID control according to claim 1, characterized in that: In the initial coarse adjustment stage, optical path pre-alignment is achieved based on the Gaussian fitting intensity signal. First, the current Gaussian fitting intensity peak value H1 is acquired, and the motor is driven to move an initial step size L according to the preset direction D. Then, the Gaussian fitting intensity peak value H1' after the movement is read, and the difference e1=H1-H1' is calculated. The direction of the motor is determined by judging the positive or negative value of the difference e1. If e1>0, the direction D is reversed to correct the motor direction; otherwise, the current direction remains unchanged. After determining the correct direction, convergence is judged based on Δe1=e1-e0, where e0 is a preset minimum value. When Δe1>0, the current difference e1 is input into the PID controller, and the coarse adjustment step size of the motor is calculated by dynamically adjusting the proportional, integral and derivative parameters. When Δe1≤0, a command to switch to the next motor is generated, and the optical path pre-alignment is finally achieved. In the secondary fine-tuning stage, the acquired interference light intensity signal is digitized by an analog-to-digital converter and transmitted to the data analysis module. Then, the DC bias and AC amplitude of the time-domain voltage signal are extracted to calculate the interference contrast. First, the current interference contrast K1 is obtained, and the motor is driven to move an initial step size L according to the preset direction D. The interference contrast K1' after the movement is read, and the difference e2=K1-K1' is calculated. The direction of the motor is determined by judging the sign of the difference e2. If e2>0, the direction D is reversed to correct the direction of the motor; otherwise, the current direction remains unchanged. After determining the correct direction, convergence is judged based on Δe2=e2-e0. When Δe2>0, the current difference e2 is input to the PID controller. The motor fine-tuning step size is calculated by dynamically adjusting the proportional, integral and derivative parameters. When Δe2≤0, a command to switch to the next motor is generated, and finally the optical path is accurately pre-aligned until the interference contrast reaches the set threshold.

3. The automatic collimation system for an optical resonator based on cascaded feedback and PID control according to claim 2, characterized in that, In the automatic control module, motors M1 and M4 of the Picomotor controller are connected to the pitch adjustment threaded pairs of the third and fourth reflectors respectively via flexible couplings, and motors M2 and M3 are connected to the yaw adjustment threaded pairs of the third and fourth reflectors respectively. The automatic control module adjusts the third and fourth reflectors sequentially according to motor numbers M1 to M4. The system uses the difference e1 between the peak intensity values ​​of the Gaussian fitting of the light spot and the difference e2 between the interference contrast values ​​as the core judgment criteria, and generates the step size of each motor through a PID controller. After each adjustment, the change in difference Δe is calculated in real time, and Δe≤0 is used as the condition for exiting the current motor adjustment cycle.

4. The automatic collimation system for optical resonant cavities based on cascaded feedback and PID control according to any one of claims 1-3, characterized in that, The implementation method specifically includes the following steps: Step 1: Build the hardware system, using a fiber laser as the light source, constructing an optical resonant cavity through four mirrors, and connecting a data acquisition module, including connecting a spot analyzer to the data analysis module, connecting a photodetector to the data analysis module through an analog-to-digital converter, and connecting the four motors of the Picomotor controller in the automatic control module to the adjusting thread pairs on the optical rotation adjustment brackets of the third and fourth mirrors respectively, and completing the hardware connection and initialization settings. Step 2: Start the data acquisition module, and collect the Gaussian fitting intensity signal and interference light intensity signal through the spot analyzer and photodetector respectively. The data analysis module receives and displays the signals, and the automatic acquisition and storage of signals is realized through Python scripts. Step 3: The data analysis module processes the acquired signals. For Gaussian fitted intensity signals, the BeamHere analysis software is used to obtain Gaussian fitted curves in the X-axis and Y-axis contour windows, and the trend of peak intensity change of the curves is monitored in real time. For interference light intensity signals, the signals are digitized by an analog-to-digital converter and then transmitted to the data analysis module to extract interference contrast through time-domain voltage amplitude analysis. Step 4: In the initial coarse adjustment stage, the system inputs the difference e1 between the current peak value of the Gaussian fitting intensity and the peak value of the Gaussian fitting intensity after motor adjustment into the PID controller. After PID calculation, the system outputs the coarse adjustment step size of the motor. At the same time, the motor direction is automatically determined based on the sign of e1, and each motor is cascaded and adjusted in the order of M1 to M4. After each adjustment, the change in difference Δe1 is calculated, and Δe1≤0 is used as the condition to exit the current motor adjustment cycle. After all motors have been adjusted, the system enters the secondary fine adjustment stage. The difference e2 between the current interference contrast and the interference contrast after motor adjustment is input into the PID controller. After calculation, the system outputs the fine adjustment step size of the motor. At the same time, the motor direction is automatically determined based on the sign of e2, and each motor is cascaded and adjusted in the order of M1 to M4. After each adjustment, the change in difference Δe2 is calculated, and Δe2≤0 is used as the condition to exit the current motor adjustment cycle. Finally, the system achieves precise optimization and control of the optical path. Step 5: After each adjustment, the system reads back the Gaussian fitting strength and interference contrast in real time. If the deviation of the Gaussian fitting strength is less than the set threshold, the coarse adjustment is determined to be completed. If the interference contrast reaches or exceeds the set threshold, the fine adjustment is determined to be completed. Step 6: After all optical components have completed coarse and fine two-stage adjustment, the system outputs the final interference contrast and the step size and direction data of the motor rotation, and generates the adjustment log; saves the PID controller configuration parameters and exits the control loop to achieve long-term stable locking of the optical path.

Images