Hemispherical resonator gyroscope attitude drift error compensation method

Abstract

The invention discloses a hemispherical resonator gyroscope attitude drift error compensation method, and relates to the technical field of resonator gyroscopes, and the method comprises the following steps: S1, system modeling: firstly, establishing a mathematical model of a hemispherical resonator gyroscope, including dynamic characteristics and a noise model, for designing a PID controller; s2, a PID controller is designed, the proportion P, integral I and differential D parameters of the PID controller are designed according to the system model, and the parameters determine the response speed and stability of the controller to error signals; s3, error signal calculation: calculating an error signal between the actual output and the expected output of the system in real time, and taking the error signal as the input of a PID (Proportion Integration Differentiation) controller; by comprehensively applying the steps, the robustness of the HRG can be remarkably enhanced, the HRG can still keep high precision and stability when facing environment change, system aging or non-ideal working conditions, and a closed-loop control mechanism is combined to ensure that the system can maintain good performance under various conditions.

Description

Technical Field

[0001] The invention relates to the technical field of resonant gyroscopes, and in particular to a method for compensating an attitude drift error of a hemispherical resonant gyroscope. Background Art

[0002] Hemispherical resonant gyroscope (HRG) is an inertial sensor that uses the oscillation of a hemispherical resonator in an electric field to measure angular velocity. HRG has the characteristics of high sensitivity, wide dynamic range and low noise, and is suitable for precise navigation and positioning systems. The attitude drift error refers to the deviation of the output angular velocity of HRG due to internal effects (such as friction, temperature change, electrical noise, etc.) when there is no external angular velocity input. This error will accumulate over time and seriously affect the long-term stability and accuracy of HRG.

[0003] In the prior art, there are a variety of solutions for compensating the attitude drift error of HRG. By improving the dynamic model of HRG, adopting multi-loop digital control technology, designing a reasonable capacitor configuration and other methods, the error source can be effectively suppressed and the performance of HRG can be improved. However, in actual applications, HRG may encounter internal parameter changes caused by factors such as manufacturing tolerances, aging, and temperature changes. These changes will affect the performance of the gyroscope, especially the long-term stability and accuracy. Summary of the invention

[0004] The present invention aims to provide a method for compensating an attitude drift error of a hemispherical resonant gyroscope, so as to solve the problem that the uncertainty of the system parameters and the environmental changes affect the stability and accuracy.

[0005] The present invention is achieved through the following technical solutions: A method for compensating an attitude drift error of a hemispherical resonant gyroscope comprises the following steps: S1. System modeling. First, it is necessary to establish a mathematical model of the hemispherical resonant gyroscope, including its dynamic characteristics and noise model, for designing a PID controller. S2, PID controller design, design the proportional P, integral I and differential D parameters of the PID controller according to the system model. These parameters determine the response speed and stability of the controller to the error signal; S3, error signal calculation, real-time calculation of the error signal between the actual output and the expected output of the system, this error signal will be used as the input of the PID controller; S4, PID control algorithm is executed, the PID controller calculates the control output according to the error signal and applies it to the system to reduce the error; S5, closed-loop control, the output of the PID controller is fed back to the system to form a closed-loop control system. The actual output of the system will be measured again and compared with the expected output to form a new error signal, and the cycle will repeat; The closed-loop control mechanism ensures that the output of the HRG is continuously monitored and adjusted to achieve or maintain the desired output, which helps maintain the stability of the system under various operating conditions and reduces attitude drift errors caused by external disturbances or system nonlinearity.

[0006] S6, parameter adjustment, adjusting the PID controller parameters through experiments or simulations, involving adjusting the values ​​of P, I, and D parameters to optimize the system response speed and reduce overshoot; S7, system testing and verification, test the system in the actual environment to verify whether the PID controller can effectively compensate for the attitude drift error and ensure the stability and accuracy of the system; S8. Performance monitoring and maintenance: During system operation, continuously monitor its performance and make adjustments or maintenance when necessary to cope with the impact of factors such as environmental changes or system aging.

[0007] Furthermore, the system modeling in S1 specifically includes: Use COMSOL Multiphysics simulation software to establish the mathematical model of the hemispherical resonant gyroscope, including its dynamic model and noise model, for designing the PID controller; It is necessary to collect all available data about the HRG, including its physical dimensions, material properties, resonant frequency, and damping coefficient; Based on the collected data, a mathematical model is established to describe the dynamic behavior of HRG, including the mass of the resonant cavity, spring constant, damping force, and external forces.

[0008] Furthermore, the design of the proportional P, integral I and differential D parameters in S2 also includes: For the initial system setup, the PID controller is placed in pure proportional control mode (i.e., the I and D parameters are set to 0), and the proportional gain is gradually increased until the system begins to exhibit stable constant amplitude oscillations; Record the critical gain and oscillation period: When the system begins to oscillate stably with equal amplitude, record the proportional gain (called the critical gain Kc) and the oscillation period (called the critical period Pc) at this time. Calculate PID parameters: Use the following formula to calculate PID parameters: Proportional gain Kp = 0.6Kc Integration time Ti = 2Pc Differentiation time Td = 0.5Pc.

[0009] Furthermore, in S3, the error signal calculation further includes: Initialize variables, including set value S, actual value Av, error E, error accumulation Es, and error derivative De; The loop execution error calculation includes: In each control cycle, the current error value is calculated: E(k)=S−Av(k); Update error accumulation: Es(k)=Es(k−1)+E(k); Calculate the error derivative: De(k)=E(k)−E(k−1); Where P, I, and D are the proportional, integral, and derivative gain parameters, respectively, and k is an integer that increases over time and represents the position of the controller algorithm in the discrete time series. For example, if the control period is 100 ms, k starts at 0 and increases by 1 every 100 ms.

[0010] Furthermore, in S4, the PID control algorithm execution specifically includes: Proportional control: The proportional control action is calculated based on the current error value E(k) multiplied by the proportional gain P. Proportional control is designed to respond to errors immediately, and its contribution is proportional to the size of the error.

[0011] Integral control: Calculate the error accumulation Es (k), and then multiply it by the integral gain I to calculate the integral control action. The purpose of integral control is to eliminate static errors, that is, long-term errors.

[0012] Derivative control: Calculate the error derivative De(k) and then multiply it by the differential gain D to calculate the derivative control action. Derivative control helps predict the future trend of the error and reduce overshoot and improve system stability by making adjustments in advance.

[0013] Combining these three control actions, the controller output U(k) is updated, which is usually calculated by the following formula: U(k)=P⋅E(k)+I⋅Es (k)+D⋅De(k); k is an integer that increases over time and represents the position of the controller algorithm in the discrete time series. For example, if the control period is 100ms, k starts at 0 and increases by 1 every 100ms. The updated output value is then sent to the control system's actuators to adjust the system's behavior so that its actual output is closer to the set point. In real applications, this process is repeated every control cycle to maintain or guide the system's performance.

[0014] Furthermore, the parameter adjustment in S6 specifically includes: Determine the initial parameters. Based on system characteristics and preliminary engineering judgment, select an initial set of PID parameters. It can also be based on empirical formulas, system identification or literature data. System testing and response recording: Run the system under closed-loop control and record the system's response behavior, including rise time, settling time, overshoot, and oscillation; Analyze system response: Analyze the recorded system response to identify control performance issues. If the system response is too slow, increase the proportional gain; if the overshoot is too large or the system continues to oscillate, adjust the integral and differential gains.

[0015] Furthermore, the adjustment of the proportional P, integral I and differential D parameters in S6 also includes: Proportional gain P adjustment: Increasing the P value can speed up the system response, but too high a P value will cause system instability and increase overshoot; Integral gain I adjustment: After adjusting the proportional parameter P, start adjusting the integral gain I, increase the integral gain I until the system reaches a steady state. Avoid over-adjustment during the adjustment process. Increasing the I value helps eliminate static errors, but too high an I value will cause the system to respond slowly or even become unstable. Differential gain D adjustment: gradually increase the differential gain D, observe the system's response to disturbances, and adjust until the system is stable and overshoot is properly suppressed. Be careful not to make the system too sensitive to noise. Increasing the D value can improve the system's dynamic performance and reduce overshoot, but too high a D value may introduce noise and affect the stability of the system. Iterative adjustment: Based on the analysis of system response and the goal of control performance, PID parameters are adjusted repeatedly until a satisfactory control effect is achieved. This process requires multiple iterations, and the system response must be retested after each adjustment. Stability check: Ensure that the tuned PID parameters do not cause the system to become unstable. This involves checking the poles and zeros of the closed-loop system to ensure that they are in the stable region.

[0016] Furthermore, the system test in S7 includes the following steps: Create a controlled test environment that simulates actual operating conditions for system testing; Ensure that all necessary hardware devices, such as sensors, actuators, and control units, are properly installed and configured on the test bench; Integrate PID controller software with other system components to ensure data flow and correct transmission of control signals; Collect real-time data about the system during testing, including sensor readings, control outputs, and system responses.

[0017] Further, the system verification in S7 includes the following steps: Evaluate the response speed, stability, overshoot and anti-interference ability of the PID controller based on the collected data; Based on the results of the performance evaluation, adjust the parameters of the PID controller to achieve the best control effect, which may require multiple iterations and fine-tuning; Ensure that the adjusted PID controller can still maintain stable and accurate control in the face of various disturbances and changes; Record the test results in detail and analyze them to verify whether the PID controller meets the design requirements and performance standards; After all testing and adjustments are completed, a final verification test is performed to ensure that the system performs as expected in actual operation.

[0018] Furthermore, the S8 also includes: Real-time performance monitoring, using sensors and data acquisition systems to monitor the system output, input, error signal and PID controller output in real time. The monitoring data should include but not be limited to physical parameters such as temperature, pressure, flow, position, speed, and dynamic changes of control signals; Data analysis and evaluation: analyze monitoring data regularly or in real time to evaluate system performance indicators, such as response time, overshoot, steady-state error, oscillation, etc. Use statistical methods and control theory to identify potential performance degradation trends or abnormal conditions; Regular maintenance and inspection, formulate maintenance plans, regularly inspect and maintain system hardware, such as sensor calibration, actuator lubrication, controller software upgrades, etc., to prevent performance degradation due to equipment aging or wear; Fault diagnosis and repair: Establish a fault diagnosis system that can identify the type and location of system faults, guide operators to make quick repairs, and reduce system downtime; Operator training: Regularly train operators on system operation, monitoring and maintenance to improve their understanding of system performance and ability to handle abnormal situations.

[0019] Compared with the prior art, the present invention has the following advantages and beneficial effects: 1. The present invention, by combining these steps, can significantly enhance the robustness of HRG, so that it can still maintain high accuracy and stability in the face of environmental changes, system aging or non-ideal working conditions. The dynamic adjustment capability of the PID control algorithm, combined with the closed-loop control mechanism, ensures that the system can maintain good performance under various conditions; 2. The present invention can significantly reduce the attitude drift error of HRG through sophisticated PID controller design and parameter adjustment, thereby improving the measurement accuracy of the system. Closed-loop control and performance monitoring and maintenance ensure that HRG can maintain stable performance under various operating conditions, and maintain low drift error even in the case of external disturbances or internal parameter changes; 3. The present invention optimizes dynamic response. The dynamic adjustment capability of the PID control algorithm allows the HRG to respond quickly to environmental changes, which is crucial for application scenarios that require rapid startup and response, and extends the service life of the system. Through effective error compensation and control, the system wear caused by long-term accumulated errors can be reduced, thereby extending the service life and reliability of the HRG. 4. The present invention executes the PID control algorithm to dynamically adjust the control signal according to the real-time error signal to reduce the attitude drift error, reduce the error through proportional control, eliminate the steady-state error through integral control, and improve the dynamic response of the system through differential control, thereby improving the accuracy and stability of the HRG to cope with changes in the internal parameters of the HRG and external disturbances and maintain the optimal working state. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] The drawings described herein are used to provide a further understanding of the embodiments of the present invention, constitute a part of this application, and do not constitute a limitation of the embodiments of the present invention. In the drawings: Figure 1 It is a process step diagram of the present invention. DETAILED DESCRIPTION

[0021] In order to make the purpose, technical scheme and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the embodiments and drawings. The schematic implementation modes and descriptions of the present invention are only used to explain the present invention and are not intended to limit the present invention. It should be noted that the present invention is already in the actual development and use stage.

[0022] like Figure 1 As shown, the present invention provides a method for compensating an attitude drift error of a hemispherical resonant gyroscope, comprising the following steps: S1. System modeling. First, it is necessary to establish a mathematical model of the hemispherical resonant gyroscope, including its dynamic characteristics and noise model, for designing a PID controller. S2, PID controller design, design the proportional P, integral I and differential D parameters of the PID controller according to the system model. These parameters determine the response speed and stability of the controller to the error signal; S3, error signal calculation, real-time calculation of the error signal between the actual output and the expected output of the system, this error signal will be used as the input of the PID controller; S4, PID control algorithm is executed, the PID controller calculates the control output according to the error signal and applies it to the system to reduce the error; S5, closed-loop control, the output of the PID controller is fed back to the system to form a closed-loop control system. The actual output of the system will be measured again and compared with the expected output to form a new error signal, and the cycle will repeat; The closed-loop control mechanism ensures that the output of the HRG is continuously monitored and adjusted to achieve or maintain the desired output, which helps maintain the stability of the system under various operating conditions and reduces attitude drift errors caused by external disturbances or system nonlinearity; S6, parameter adjustment, adjusting the PID controller parameters through experiments or simulations, involving adjusting the values ​​of P, I, and D parameters to optimize the system response speed and reduce overshoot; S7, system testing and verification, test the system in the actual environment to verify whether the PID controller can effectively compensate for the attitude drift error and ensure the stability and accuracy of the system; S8. Performance monitoring and maintenance: During system operation, continuously monitor its performance and make adjustments or maintenance when necessary to cope with the impact of factors such as environmental changes or system aging.

[0023] In the above scenario: Specifically, step S1 includes using COMSOL Multiphysics simulation software to establish a mathematical model of the hemispherical resonant gyroscope, including its dynamic model and noise model, for designing a PID controller; It is necessary to collect all available data about the HRG, including its physical dimensions, material properties, resonant frequency, and damping coefficient; Based on the collected data, a mathematical model describing the dynamic behavior of HRG is established, including the mass of the resonant cavity, spring constant, damping force, and external forces. By establishing an accurate mathematical model to describe the dynamic characteristics of the HRG, we can better understand the system behavior, predict and explain the system response, and provide a theoretical basis for subsequent controller design. System modeling helps to identify and quantify the source of attitude drift error and provide an accurate error model for subsequent steps.

[0024] Specifically, in step S2, the system is initially set up, the PID controller is placed in a pure proportional control mode (i.e., the I and D parameters are set to 0), and the proportional gain is gradually increased until the system begins to exhibit stable equal-amplitude oscillations; Record the critical gain and oscillation period: When the system begins to oscillate with stable equal amplitude, record the proportional gain (called critical gain Kc) and oscillation period (called critical period Pc) at this time; Calculate PID parameters: Use the following formula to calculate PID parameters: Proportional gain Kp = 0.6Kc Integration time Ti = 2Pc Differential time Td = 0.5Pc; The designed PID controller can effectively compensate for the attitude drift error in the HRG. By adjusting the proportional P, integral I and differential D parameters, the controller can respond to the system deviation in real time, improve the dynamic response speed and stability of the system, and reduce the steady-state error.

[0025] Specifically, step S3 includes initializing variables, including set value S, actual value Av, error E, error accumulation Es, and error derivative De; The loop execution error calculation includes: In each control cycle, the current error value is calculated: E(k)=S−Av(k); Update error accumulation: Es(k)=Es(k−1)+E(k); Calculate the error derivative: De(k)=E(k)−E(k−1); Where P, I and D are the proportional, integral and derivative gain parameters respectively, and k is an integer that increases with time and represents the position of the controller algorithm in the discrete time series. For example, if the control period is 100ms, k starts at 0 and increases by 1 every 100ms. By calculating the error signal between the HRG output and the expected output in real time, the attitude drift error can be detected in time to ensure that the controller can respond quickly. This step is the basis for the execution of the PID control algorithm and ensures timely feedback and compensation of the error.

[0026] Specifically, step S4 includes: proportional control: the proportional control action is calculated according to the current error value E(k) multiplied by the proportional gain P. The proportional control is to respond to the error immediately, and its contribution is proportional to the size of the error.

[0027] Integral control: Calculate the error accumulation Es (k), and then multiply it by the integral gain I to calculate the integral control action. The purpose of integral control is to eliminate static errors, that is, long-term errors.

[0028] Derivative control: Calculate the error derivative De(k) and then multiply it by the differential gain D to calculate the derivative control action. Derivative control helps predict the future trend of the error and reduce overshoot and improve system stability by making adjustments in advance.

[0029] Combining these three control actions, the controller output U(k) is updated, which is usually calculated by the following formula: U(k)=P⋅E(k)+I⋅Es (k)+D⋅De(k); k is an integer that increases over time and represents the position of the controller algorithm in the discrete time series. For example, if the control period is 100ms, k starts at 0 and increases by 1 every 100ms. The updated output value is then sent to the control system's actuators to adjust the system's behavior so that its actual output is closer to the set point. In actual applications, this process is repeated every control cycle to maintain or guide the system's performance. Executing the PID control algorithm can dynamically adjust the control signal according to the real-time error signal to reduce the attitude drift error, reduce the error through proportional control, eliminate the steady-state error through integral control, and improve the dynamic response of the system through differential control, thereby improving the accuracy and stability of the HRG.

[0030] Specifically, step S6 includes determining initial parameters, selecting a set of initial PID parameters based on system characteristics and preliminary engineering judgment, and may also be based on empirical formulas, system identification or literature data; System testing and response recording: Run the system under closed-loop control and record the system's response behavior, including rise time, settling time, overshoot, and oscillation; Analyze system response: Analyze the recorded system response and identify control performance problems. If the system response is too slow, increase the proportional gain; if the overshoot is too large or the system continues to oscillate, adjust the integral and differential gains; Proportional gain P adjustment: Increasing the P value can speed up the system response, but too high a P value will cause system instability and increase overshoot; Integral gain I adjustment: After adjusting the proportional parameter P, start adjusting the integral gain I, increase the integral gain I until the system reaches a steady state. Avoid over-adjustment during the adjustment process. Increasing the I value helps eliminate static errors, but too high an I value will cause the system to respond slowly or even become unstable. Differential gain D adjustment: gradually increase the differential gain D, observe the system's response to disturbances, and adjust until the system is stable and overshoot is properly suppressed. Be careful not to make the system too sensitive to noise. Increasing the D value can improve the system's dynamic performance and reduce overshoot, but too high a D value may introduce noise and affect the stability of the system. Iterative adjustment: Based on the analysis of system response and the goal of control performance, PID parameters are adjusted repeatedly until a satisfactory control effect is achieved. This process requires multiple iterations, and the system response must be retested after each adjustment. Stability check: Ensure that the adjusted PID parameters do not cause the system to become unstable. This involves checking the poles and zeros of the closed-loop system to ensure that they are in the stable region. By adjusting parameters, the performance of the PID controller can be optimized to ensure that it can effectively compensate for attitude drift errors under different working conditions. This step may require iteration based on experimental data to find the optimal parameter settings.

[0031] Specifically, step S7 includes creating a controllable test environment to simulate actual operating conditions for system testing; Ensure that all necessary hardware devices, such as sensors, actuators, and control units, are properly installed and configured on the test bench; Integrate PID controller software with other system components to ensure data flow and correct transmission of control signals; Collect real-time data from the system during testing, including sensor readings, control outputs, and system responses; Evaluate the response speed, stability, overshoot and anti-interference ability of the PID controller based on the collected data; Based on the results of the performance evaluation, adjust the parameters of the PID controller to achieve the best control effect, which may require multiple iterations and fine-tuning; Ensure that the adjusted PID controller can still maintain stable and accurate control in the face of various disturbances and changes; Record the test results in detail and analyze them to verify whether the PID controller meets the design requirements and performance standards; After all tests and adjustments are completed, a final verification test is performed to ensure that the system performs as expected in actual operation; System testing and verification ensure the effectiveness of the PID algorithm compensation method in practical applications. By comparing the performance of the HRG before and after compensation, the accuracy and stability of the compensation method can be verified to ensure that it can significantly reduce the attitude drift error.

[0032] Specifically, step S8 includes real-time performance monitoring, using sensors and data acquisition systems to monitor the output, input, error signal of the system and the output of the PID controller in real time. The monitoring data should include but are not limited to physical parameters such as temperature, pressure, flow, position, speed, and dynamic changes of control signals; Data analysis and evaluation: analyze monitoring data regularly or in real time to evaluate system performance indicators, such as response time, overshoot, steady-state error, oscillation, etc. Use statistical methods and control theory to identify potential performance degradation trends or abnormal conditions; Regular maintenance and inspection, formulate maintenance plans, regularly inspect and maintain system hardware, such as sensor calibration, actuator lubrication, controller software upgrades, etc., to prevent performance degradation due to equipment aging or wear; Fault diagnosis and repair: Establish a fault diagnosis system that can identify the type and location of system faults, guide operators to make quick repairs, and reduce system downtime; Operator training: Regularly train operators on system operation, monitoring and maintenance to improve their understanding of system performance and ability to handle abnormal situations; Performance monitoring and maintenance ensure that the HRG maintains good performance in long-term operation. By continuously monitoring the system response and adjusting the PID parameters, potential problems can be discovered and solved in a timely manner, reducing attitude drift errors caused by equipment aging or environmental changes.

[0033] In summary, the combined use of these steps can significantly enhance the robustness of the HRG, enabling it to maintain high accuracy and stability in the face of environmental changes, system aging or non-ideal working conditions. The dynamic adjustment capability of the PID control algorithm, combined with the closed-loop control mechanism, ensures that the system can maintain good performance under various conditions.

[0034] The specific implementation methods described above further illustrate the objectives, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above description is only a specific implementation method of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A method for compensating attitude drift error of a hemispherical resonator gyroscope, characterized in that: The following steps are involved: S1. System modeling,First, a mathematical model of the hemispherical resonant gyroscope is established to design the PID controller; S2, PID controller design, design the proportional P, integral I and differential D parameters of the PID controller according to the system model; S3, error signal calculation, real-time calculation of the error signal between the actual output and the expected output of the system; S4, PID control algorithm is executed, and the PID controller calculates the control output according to the error signal; S5, closed-loop control, feeds the output of the PID controller back to the system to form a closed-loop control system, measures the actual output of the system, and compares it with the expected output to form a new error signal; S6, parameter adjustment, by adjusting the PID controller parameters, adjust the values ​​of P, I, and D parameters; S7, system testing and verification, test the system in the actual environment to verify whether the PID controller can compensate for the attitude drift error; S8. Performance monitoring and maintenance. During the system operation, its performance is continuously monitored and the P, I, and D parameters are adjusted using the PID controller.

2. The method for compensating attitude drift error of a hemispherical resonator gyroscope according to claim 1, characterized in that: The system modeling in S1 specifically includes: Use COMSOL Multiphysics simulation software to establish a mathematical model of the hemispherical resonant gyroscope, including a dynamic model and a noise model of the hemispherical resonant gyroscope, for designing a PID controller; Specifically, first data about the hemispherical resonant gyroscope is collected, including its physical dimensions, material properties, resonant frequency, and damping coefficient; Based on the first data, a mathematical model describing the dynamic behavior of the HRG is established, including the mass of the resonant cavity, the spring constant, the damping force, and the external force.

3. The method for compensating attitude drift error of a hemispherical resonator gyroscope according to claim 1, characterized in that: The design of the proportional P, integral I and differential D parameters in S2 also includes: For the initial system settings, the PID controller is placed in pure proportional control mode, the I and D parameters are set to 0, and the proportional gain is gradually increased until the system begins to exhibit stable constant amplitude oscillations; Record the critical gain and oscillation period: When the system begins to oscillate with stable equal amplitude, record the proportional gain and oscillation period at this time; Calculate PID parameters: Use the following formula to calculate PID parameters: Proportional gain Kp = 0.6Kc Integration time Ti = 2Pc Differential time Td = 0.5Pc; Kc is the critical gain and Pc is the critical period, both of which are determined experimentally. Using the Ziegler-Nichols method, the integral I and differential D links of the PID controller are turned off, leaving only the proportional P link, and then the proportional gain is gradually increased until the system begins to oscillate continuously. At this time, the critical gain recorded is Kc, and the critical period is Pc.

4. The method for compensating attitude drift error of a hemispherical resonator gyroscope according to claim 1, characterized in that: In said S3, the error signal calculation also includes: Initialize variables, including set value S, actual value Av, error E, error accumulation Es, and error derivative De; The loop execution error calculation includes: In each control cycle, the current error value is calculated: E(k)=S−Av(k); Update error accumulation: Es(k)=Es(k−1)+E(k); Calculate the error derivative: De(k)=E(k)−E(k−1); Where P, I, and D are the proportional, integral, and derivative gain parameters, respectively, and k is an integer that increases with time and represents where the controller algorithm is in the discrete time series.

5. The method for compensating attitude drift error of a hemispherical resonator gyroscope according to claim 1, characterized in that: In S4, the PID control algorithm execution specifically includes: Proportional control: The proportional control action is calculated by multiplying the current error value E(k) by the proportional gain P; Integral control: Calculate the error accumulation Es (k), and then multiply it by the integral gain I to calculate the integral control action; Derivative control: Calculate the error derivative De(k), then multiply it by the differential gain D to calculate the derivative control action; Combining these three control actions, the controller output U(k) is updated and calculated by the following formula: U(k)=P⋅E(k)+I⋅Es (k)+D⋅De(k); k is an integer that increases with time and represents the position of the controller algorithm in the discrete time series; The updated output value is then sent to the control system's actuators to bring the actual output closer to the set point, which is repeated every control cycle.

6. The method for compensating attitude drift error of a hemispherical resonator gyroscope according to claim 1, characterized in that: The parameter adjustment in S6 specifically includes: Determine the initial parameters. Select a set of initial PID parameters based on system characteristics and preliminary engineering judgment. It can also be based on empirical formulas and system identification. The specific empirical formula includes the Ziegler-Nichols rule of PID control theory. System identification includes the mathematical model established by simulation. System testing and response recording: Run the system under closed-loop control and record the system's response behavior, including rise time, settling time, overshoot, and oscillation; Analyze system response: Analyze the recorded system response and identify control performance problems. If the system response is too slow, the proportional gain needs to be increased. If the overshoot is too large and the system continues to oscillate, the integral and differential gains need to be adjusted.

7. The method for compensating attitude drift error of a hemispherical resonator gyroscope according to claim 6, characterized in that: The adjustment of the proportional P, integral I and differential D parameters in S6 also includes: Proportional gain P adjustment: Increasing the P value speeds up the system response speed, and too high a P value increases the overshoot; Integral gain I adjustment: After adjusting the proportional parameter P, start adjusting the integral gain I and increase the integral gain I until the system reaches a steady state; Differential gain D adjustment: gradually increase the differential gain D, observe the system's response to disturbances, and adjust until the system is stable and has no sensitive noise; Iterative adjustment: Based on the analysis of system response and the goal of control performance, PID parameters are adjusted repeatedly, multiple times, and the system response is retested after each adjustment; Stability Check: Check the poles and zeros of the closed-loop system.

8. The method for compensating attitude drift error of a hemispherical resonator gyroscope according to claim 1, characterized in that: The system test in S7 includes the following steps: Create a controlled test environment that simulates actual operating conditions; Installing and configuring hardware devices on a test platform, the hardware devices including sensors, actuators, and control units; Integrate PID controller software with other system components to ensure data flow and correct transmission of control signals; Collect real-time data about the system during testing, including sensor readings, control outputs, and system responses.

9. The method for compensating attitude drift error of a hemispherical resonator gyroscope according to claim 8, characterized in that: The system verification in S7 includes the following steps: Evaluate the response speed, stability, overshoot and anti-interference ability of the PID controller based on the collected data; According to the results of performance evaluation, adjust the parameters of PID controller, iterate and fine-tune multiple times; Record the test results in detail and analyze them to verify whether the PID controller meets the design requirements and performance standards; After all tests and adjustments are completed, a final verification test is performed to verify that the system performs as expected in actual operation.

10. The method for compensating attitude drift error of a hemispherical resonator gyroscope according to claim 1, characterized in that: The S8 also includes: Real-time performance monitoring, using sensors and data acquisition systems to monitor the system output, input, error signal and PID controller output in real time. The monitoring data should include temperature, pressure, flow, position, speed and dynamic changes of control signals; Data analysis and evaluation: regular or real-time analysis of monitoring data to evaluate system performance indicators, response time, overshoot, steady-state error and oscillation; Regular maintenance and inspection, formulate maintenance plans, regularly inspect and maintain system hardware, calibrate sensors, lubricate actuators, and upgrade controller software; Fault diagnosis and repair: establish a fault diagnosis system, identify the type and location of system faults, and guide operators to perform quick repairs.

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