An Adaptive Calibration Method and System for PID Control Parameters of Satellite Antenna

Abstract

This specification discloses an adaptive calibration method and system for satellite antenna PID control parameters. The automatic calibration method includes: acquiring and sorting the inter-axis servo nesting relationships of the satellite antenna servo axes to obtain a tuning order; initializing PID control parameters, locking all satellite antenna servo axes, and collecting the angular velocity corresponding to each satellite antenna servo axis in real time to form inertial navigation information; unlocking and calibrating each satellite antenna servo axis sequentially based on the tuning order; for any unlocked satellite antenna servo axis, using the gradient descent method to iteratively update the control parameter group corresponding to that satellite antenna servo axis based on the inertial navigation information to obtain a calibrated control parameter group, which is then fixed, and then the next satellite antenna servo axis is unlocked; until all satellite antenna servo axes are fixed, the calibrated PID control parameters are obtained. This achieves online calibration of control parameters, improves tuning efficiency, and ensures the consistency of performance of batch products.

Description

TECHNICAL FIELD

[0001] Embodiments of the present specification relate to the technical field of satellite communication device control, and in particular to optimization of satellite antenna servo performance. BACKGROUND

[0002] A satellite antenna needs to maintain the pointing accuracy to the satellite in a mobile platform such as a ship or a vehicle through a servo control system. The system usually uses a proportional-integral-derivative (PID) control algorithm to drive the azimuth, elevation and roll three-axis motors to compensate for the pointing deviation caused by the platform sway in real time. The performance of the PID controller directly depends on the reasonable configuration of parameters such as the proportional coefficient (Kp), the integral time (Ti) and the derivative time (Td). The Kp determines the response speed of the system, the Ti affects the ability to eliminate the steady-state error, and the Td suppresses the overshoot oscillation. In a dynamic sway environment, the parameter setting needs to strike a balance between the response speed and the anti-interference performance. Too high Kp will cause motor oscillation, too long Ti will lead to tracking lag, and improper Td will aggravate mechanical wear. Therefore, the rationality of the parameter configuration is the core prerequisite to ensure the stability of the communication link.

[0003] Currently, the industry generally uses an empirical trial-and-error method based on a swing test bench to complete parameter solidification. Engineers manually adjust the PID parameter combination of each axis on a test platform simulating ship motion, observe the dynamic response curve (such as overshoot, adjustment time and steady-state error) of the antenna to the step disturbance, and iteratively until the threshold value is met, and finally the optimized parameters are written into the controller to realize solidification.

[0004] However, this method has significant limitations. First, manual parameter adjustment is highly dependent on the individual experience of engineers. Due to differences between different batches or different individuals of the same type of product, if the same PID parameters are used, the performance of individual products may be poor. If the empirical trial-and-error method is used for parameter adjustment one by one, the workload is huge, and the consistency of product performance is still difficult to guarantee. Second, when the user needs to change the antenna structure (such as changing the power amplifier module specification or the weight of the feed structure), the inertia moment of the system changes, and the device must be returned to the factory for reparameterization, greatly increasing the operation and maintenance cost of the device. The above defects seriously restrict the reliability of satellite mobile communication devices in large-scale deployment and operation and maintenance. SUMMARY

[0005] The embodiments of the present specification provide a satellite antenna PID control parameter self-adaptive calibration method and system, which optimizes each axis independently through hierarchical setting and physical isolation, blocks the parameter coupling, eliminates the randomness caused by manual intervention, and guarantees the consistency of the performance of batch products. At the same time, the efficiency of setting the PID control parameters is greatly improved. In addition, it also has the adaptive ability of structure change, realizing online calibration of the PID control parameters.

[0006] The technical scheme is as follows:

[0007] In a first aspect, the embodiments of the present specification provide a satellite antenna PID control parameter adaptive calibration method, comprising the following steps:

[0008] Obtaining the inter-axis follow-up nesting relationship of the satellite antenna follow-up axes, the satellite antenna follow-up axes including a roll axis, a pitch axis and an azimuth axis;

[0009] Based on the inter-axis follow-up nesting relationship, the satellite antenna follow-up axes are sorted from the inner layer to the outer layer of the nesting to obtain the setting sequence of the satellite antenna follow-up axes;

[0010] Initializing the PID control parameters, the PID control parameters including a control parameter group corresponding to each satellite antenna follow-up axis;

[0011] Locking all the satellite antenna follow-up axes and collecting the angular velocity corresponding to each satellite antenna follow-up axis in real time to form inertial navigation information;

[0012] Based on the setting sequence, the satellite antenna follow-up axes are unlocked and calibrated one by one;

[0013] For any unlocked satellite antenna follow-up axis, the gradient descent method is used to iteratively update the control parameter group corresponding to the satellite antenna follow-up axis based on the inertial navigation information, to obtain the calibrated control parameter group corresponding to the satellite antenna follow-up axis and solidify it, and then unlock the next satellite antenna follow-up axis;

[0014] Until the calibrated control parameter groups corresponding to each satellite antenna follow-up axis are all solidified, the calibrated PID control parameters are obtained.

[0015] As a preferred scheme, the control parameter group includes a proportional coefficient, an integral time coefficient and a differential time coefficient; the gradient descent method is used to iteratively update the control parameter group corresponding to the satellite antenna follow-up axis based on the inertial navigation information, to obtain the calibrated control parameter group corresponding to the satellite antenna follow-up axis and solidify it, including:

[0016] S1, obtaining first inertial navigation information based on the current control parameter group corresponding to the satellite antenna follow-up axis and the first disturbance step of the corresponding proportional coefficient, and updating the proportional coefficient corresponding to the satellite antenna follow-up axis based on the first inertial navigation information using the gradient descent method;

[0017] S2, obtaining second inertial navigation information based on the current control parameter group corresponding to the satellite antenna follow-up axis and the second disturbance step of the corresponding integral time coefficient, and updating the integral time coefficient corresponding to the satellite antenna follow-up axis based on the second inertial navigation information using the gradient descent method;

[0018] S3. Based on the current control parameter group and the third disturbance step size of the corresponding differential time coefficient of the satellite antenna follower axis, obtain the third inertial navigation information, and use the gradient descent method to update the differential time coefficient of the satellite antenna follower axis based on the third inertial navigation information.

[0019] S4. Obtain the fourth inertial navigation information based on the current control parameter group corresponding to the satellite antenna follower axis, and calculate the objective function value based on the fourth inertial navigation information. When the objective function value is greater than or equal to the preset value, return to step S1 and iterate again.

[0020] Repeat the above steps until the calibration conditions are met, then complete the iteration and use the current control parameter set as the calibrated control parameter set corresponding to the satellite antenna follower axis for solidification.

[0021] As a preferred embodiment, the step of iteratively updating the control parameter set corresponding to the satellite antenna follower axis based on inertial navigation information using the gradient descent method includes:

[0022] For any control parameter in the control parameter group, the disturbance control parameter group is obtained based on the disturbance step size corresponding to the control parameter and the current control parameter group corresponding to the satellite antenna follower axis;

[0023] Obtain the inertial navigation information segments corresponding to the current control parameter group and the disturbance control parameter group of the satellite antenna follower axis;

[0024] Based on the inertial navigation information segments corresponding to the current control parameter group and the disturbance control parameter group respectively, the pointing error information corresponding to the current control parameter group and the disturbance control parameter group is obtained. The pointing error information includes the cumulative angular velocity value corresponding to different acquisition times within the inertial navigation information segment.

[0025] The control parameter is updated based on the pointing error information corresponding to the current control parameter set and the disturbance control parameter set, respectively.

[0026] Repeat the above steps until every control parameter in the control parameter group corresponding to the satellite antenna follower axis has been updated.

[0027] As a preferred embodiment, updating the control parameter based on the pointing error information corresponding to the current control parameter set and the disturbance control parameter set includes:

[0028] Based on the pointing error information corresponding to the current control parameter group and the disturbance control parameter group respectively, the mean square value of all cumulative angular velocity values ​​in the pointing error information corresponding to the current control parameter group and the disturbance control parameter group is obtained respectively.

[0029] When the mean square value corresponding to the current control parameter group is greater than the mean square value corresponding to the disturbance control parameter group, the control parameter is updated based on the disturbance step size corresponding to the control parameter.

[0030] As a preferred embodiment, the adaptive calibration method further includes:

[0031] When the mean square value corresponding to the current control parameter group is less than the mean square value corresponding to the disturbance control parameter group, the control parameter is updated based on the disturbance step size corresponding to the control parameter and the first and second derivatives of the mean square value corresponding to the current control parameter group.

[0032] As a preferred embodiment, the objective function value is the rate of change of the mean square value of all cumulative angular velocities in the pointing error information corresponding to the control parameter set after the most recent iteration and the control parameter set after the previous iteration.

[0033] As a preferred embodiment, the calibration condition is that the objective function value corresponding to each of the consecutive preset number of iterations is less than a preset value.

[0034] Secondly, embodiments of this specification provide an adaptive calibration system for PID control parameters of a satellite antenna, including an acquisition module, a data acquisition module, and a calibration module;

[0035] The acquisition module acquires the inter-axis follower nesting relationship of the satellite antenna follower axes, which include the roll axis, pitch axis, and azimuth axis; based on the inter-axis follower nesting relationship, the satellite antenna follower axes are sorted from the innermost nesting layer to the outermost nesting layer to obtain the tuning order of the satellite antenna follower axes;

[0036] The acquisition module initializes PID control parameters, which include a control parameter group corresponding to each satellite antenna follower axis; it locks all satellite antenna follower axes and acquires the angular velocity corresponding to each satellite antenna follower axis in real time to form inertial navigation information.

[0037] The calibration module unlocks and calibrates each satellite antenna servo axis sequentially based on the tuning order. For any unlocked satellite antenna servo axis, the gradient descent method is used to iteratively update the control parameter set corresponding to that satellite antenna servo axis based on inertial navigation information, so as to obtain the calibrated control parameter set corresponding to that satellite antenna servo axis and solidify it. Then, the next satellite antenna servo axis is unlocked. This process continues until the calibrated control parameter set corresponding to each satellite antenna servo axis is completely solidified, resulting in calibrated PID control parameters.

[0038] Thirdly, embodiments of this specification provide a satellite antenna servo control system, including:

[0039] The electronic gyroscope collects the angular velocity of each satellite antenna follower axis in real time to obtain inertial navigation information;

[0040] Gravity acceleration sensor to collect satellite antenna tilt angle values ​​in real time;

[0041] Satellite signal acquisition device, which collects the satellite signal strength received by the satellite antenna in real time;

[0042] The inner loop control unit includes an adaptive calibration system for satellite antenna PID control parameters as described in the second aspect of the above embodiments, which outputs a first follow-up control signal based on the calibrated PID control parameters obtained by calibrating the inertial navigation information collected by the electronic gyroscope.

[0043] The intermediate loop control unit outputs a second follow-up control signal based on the satellite antenna tilt angle value to correct the control error of the inner loop control unit;

[0044] The outer ring control unit uses a conical scanning algorithm to output a third follow-up control signal based on the satellite signal strength to compensate for the tracking error generated after the inner ring control unit and the intermediate ring control unit perform follow-up control.

[0045] Fourthly, this specification provides a satellite antenna follow-up control device, including a three-axis control gimbal carrying a satellite antenna, a motor drive module for driving the three-axis control gimbal, and a satellite antenna follow-up control system as described in the third aspect of the above embodiments;

[0046] The control nesting relationship of the three-axis gimbal control satellite antenna follow-up is: pitch axis in the inner layer, roll axis in the middle layer, and azimuth axis in the outer layer.

[0047] The motor drive module drives the three-axis control gimbal to perform follow-up control based on the first follow-up control signal, the second follow-up control signal and the third follow-up control signal output by the follow-up control system.

[0048] Fifthly, embodiments of this specification provide an electronic device, including a processor and a memory; the processor is connected to the memory; the memory is used to store executable program code; the processor reads the executable program code stored in the memory to run a program corresponding to the executable program code, so as to perform the steps described in the first aspect of the above embodiments.

[0049] Sixthly, embodiments of this specification provide a computer storage medium storing a plurality of instructions adapted for loading by a processor and executing the steps described in the first aspect of the above embodiments.

[0050] The beneficial effects of the technical solutions provided in some embodiments of this specification include at least the following:

[0051] 1. When the motors of the three follower axes operate simultaneously, dynamic coupling exists. If the PID control parameters of all three axes are tuned at the same time, it will lead to mutual interference of parameters, difficulty in algorithm convergence, and an explosive increase in computational load. Therefore, based on the tuning sequence, the parameters of the roll axis, pitch axis, and azimuth axis are tuned separately and at different levels. The principle of this hierarchical tuning strategy is to use a physical locking mechanism to achieve decoupling between axes, thereby avoiding cross-level interference. This hardware-assisted tuning method is more reliable than pure algorithm isolation, avoids overshoot oscillation caused by parameter coupling, and thus can quickly complete the adaptive calibration of the three-axis PID control parameters.

[0052] 2. By using hierarchical tuning and physical isolation for independent optimization of each axis, parameter coupling is blocked, thereby eliminating randomness caused by manual intervention, ensuring the consistency of performance of batch products, and greatly improving the tuning efficiency of PID control parameters. In addition, it also has the ability to adapt to structural changes, and can recalibrate the PID control parameters online according to the changed antenna structure, which greatly reduces the equipment operation and maintenance costs.

[0053] 3. The three parameters (Kp, Ti, Td) of the PID controller are not independent; there is a significant coupling effect between them. To resolve this coupling effect, this scheme updates each coefficient sequentially in the order of Kp, then Ti, and finally Td, treating each update as an iteration. This collaborative iteration method considers the interaction of all three parameters simultaneously in each iteration, avoiding parameter conflicts and ultimately finding the optimal balance point for the three parameters, rather than a local optimum. This enables PID control in vehicle-mounted and shipborne satellite antenna scenarios, prioritizing proportional control for rapid response, then integral control to eliminate accumulated errors, and finally derivative control to suppress jitter.

[0054] 4. Instead of relying solely on the pointing deviation angle at a certain moment or the final pointing deviation angle within the inertial navigation information segment, a more comprehensive evaluation of the system's dynamic performance is conducted by integrating the deviation angles at each acquisition moment within the inertial navigation information segment, in order to guide the accuracy of parameter updates.

[0055] 5. Compared to other methods, updating control parameters by comparing mean square values ​​has significant advantages. Calculating the square of the cumulative angular velocity values ​​unifies the pointing deviation angles represented by each cumulative angular velocity value in different directions, preventing the opposing pointing deviation angles from canceling each other out and reducing the resulting mean square value, which could lead to misjudgments (e.g., pointing deviation angles continuously varying between +0.3° and -0.3°). Furthermore, it amplifies the characteristics of large cumulative angular velocity values ​​in the error information, allowing for a clearer distinction of the dynamic performance of different control parameter groups. The average of the squares of each cumulative angular velocity value is calculated to measure the overall degree of deviation in the error information at different acquisition times.

[0056] 6. A variant derived from gradient descent improves parameter iteration efficiency and stability by comprehensively considering the first and second derivatives of the mean square value S(Kp), thus achieving more robust convergence in complex parameter spaces. It eliminates the need to construct an exact mathematical model of the system performance index S; optimization is guided solely by applying perturbations and observing changes in S, making it suitable for engineering practice. Furthermore, the update step size is not fixed but dynamically adjusted based on perturbation changes, combining speed and stability. Additionally, the computation is relatively simple, requiring only three performance evaluations (current point, positive perturbation point, and negative perturbation point) to complete one control parameter update.

[0057] 7. The method of calculating the objective function value avoids unnecessary calculations, saves computing resources, and improves tuning efficiency.

[0058] 8. The calibration condition setting method avoids accidental convergence, ensuring the reliability of locked parameters and the best system performance. Attached Figure Description

[0059] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0060] Figure 1 This is a flowchart illustrating an adaptive calibration method for PID control parameters of a satellite antenna provided in the embodiments of this specification.

[0061] Figure 2 This is a schematic diagram of the structure of an adaptive calibration system for PID control parameters of a satellite antenna provided in the embodiments of this specification.

[0062] Figure 3 This is a schematic diagram of the structure of a satellite antenna follow-up control system provided in the embodiments of this specification.

[0063] Figure 4 This is a schematic diagram of the structure of a satellite antenna follow-up control device provided in the embodiments of this specification.

[0064] Figure 5 This is a schematic diagram of the structure of an electronic device provided in the embodiments of this specification. Detailed Implementation

[0065] The technical solutions in the embodiments of this specification will be clearly and completely described below with reference to the accompanying drawings.

[0066] The terms "first," "second," "third," etc., in the description, claims, and accompanying drawings are used to distinguish different objects, not to describe a specific order. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or apparatus that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to such processes, methods, products, or apparatus.

[0067] The following description provides examples and does not limit the scope, applicability, or examples set forth in the claims. Changes may be made to the function and arrangement of the described elements without departing from the scope of this specification. Various processes or components may be appropriately omitted, substituted, or added to the examples. For example, the described methods may be performed in a different order than described, and various steps may be added, omitted, or combined. Furthermore, features described with respect to some examples may be combined into other examples.

[0068] Reference Figure 1 As shown, Figure 1 This is a flowchart illustrating an adaptive calibration method for PID control parameters of a satellite antenna provided in the embodiments of this specification. The adaptive calibration method may include at least the following steps:

[0069] Step 102: Obtain the inter-axis follower nesting relationship of the satellite antenna follower axis, which includes the roll axis, pitch axis and azimuth axis;

[0070] Step 104: Based on the inter-axis follower nesting relationship, sort the follower axes of each satellite antenna from the inner nesting layer to the outer nesting layer to obtain the tuning order of the satellite antenna follower axes;

[0071] Step 106: Initialize the PID control parameters, which include the control parameter group corresponding to each satellite antenna follower axis.

[0072] Step 108: Lock all satellite antenna follower axes and collect the angular velocity of each satellite antenna follower axis in real time to form inertial navigation information;

[0073] Step 110: Unlock and calibrate each satellite antenna follower axis sequentially based on the tuning order;

[0074] For any unlocked satellite antenna servo axis, the gradient descent method is used to iteratively update the control parameter set corresponding to the satellite antenna servo axis based on the inertial navigation information, so as to obtain the calibrated control parameter set corresponding to the satellite antenna servo axis and solidify it, and then unlock the next satellite antenna servo axis;

[0075] The calibration process continues until all the corresponding control parameter sets for each satellite antenna follower axis are solidified, resulting in the calibrated PID control parameters.

[0076] In an explanatory sense, the nested relationship between axes refers to the hierarchical layout of the three-axis (roll, pitch, and azimuth) mechanical structure that carries and controls the movement of the satellite antenna. (See reference...) Figure 4 As shown in the figure, in the three-axis mechanical structure, the pitch axis 402 mechanical structure is mounted on the roll axis 403 mechanical structure, and the roll axis 403 mechanical structure is mounted on the azimuth axis 404 mechanical structure.

[0077] For example, if the inner layer of the inter-axis follower nesting relationship of the satellite antenna 401 is the pitch axis 402, the middle layer is the roll axis 403, and the outer layer is the azimuth axis 404, then the tuning sequence is pitch axis 402, roll axis 403, and azimuth axis 404.

[0078] Illustratively, in this technical solution, the functions of locking and unlocking the roll axis 403, pitch axis 402, and azimuth axis 404 can be achieved through conventional means such as mechanical locking structures or electromagnetic brakes. These methods are mature implementations in the prior art, and their specific structures and working principles will not be elaborated here. Any mechanical or electronically controlled structure capable of achieving the same locking and unlocking functions is applicable to this solution. The inertial navigation information of the satellite antenna 401 follower axis can be obtained through the electronic gyroscope 301. The electronic gyroscope 301 can be installed at a position that can move synchronously with the antenna surface of the satellite antenna 401. Referring to Figure 4, the electronic gyroscope 301 in the figure is installed on the innermost layer of the pitch axis 402 mechanical structure in the inter-axis follower nesting relationship.

[0079] It's easy to understand that, ideally, in mobile scenarios such as shipboard or vehicle-mounted systems, satellite antennas achieve perfect homing relative to the satellite through PID control, and the angular velocities of each homing axis in the inertial navigation information should all be 0. When the angular velocity of a certain homing axis is not 0, its accumulation over time is the pointing deviation angle of that homing axis, reflecting the homing pointing performance of the satellite antenna under the current PID control parameters.

[0080] Explaining this, when the motors of the three follower axes operate simultaneously, dynamic coupling exists. Simultaneous tuning of the three-axis PID control parameters can lead to mutual interference between parameters, difficulty in algorithm convergence, and an explosive increase in computational load. Therefore, the parameters of the roll, pitch, and azimuth axes are tuned separately according to the tuning sequence. The principle of this hierarchical tuning strategy is to use a physical locking mechanism to achieve decoupling between axes, thereby avoiding cross-level interference. Continuing the previous example, the pitch axis is unlocked first for parameter tuning, while the other two axes remain locked. After the pitch axis tuning is completed, the roll axis is unlocked for parameter tuning, and after the roll axis tuning is completed, the azimuth axis is unlocked for parameter tuning. This is equivalent to decomposing the multivariable system into three independent single-input single-output systems. This hardware-assisted tuning method is more reliable than pure algorithm isolation, avoiding overshoot oscillations caused by parameter coupling, thus enabling rapid adaptive calibration of the three-axis PID control parameters.

[0081] In essence, gradient descent is an iterative optimization algorithm used to find the minimum value of a function. The iteration process continues until the gradient is sufficiently small or a predetermined number of iterations is reached, thus completing the optimization and fixing the parameters. Its core principle is to adjust the parameters by continuously evaluating the local trends of the objective function, aiming to gradually approach the optimal solution. The most common approach is to apply a perturbation and calculate the gradient of the current control parameters, which indicates the direction of the fastest descent of the function value. Subsequently, the current control parameters are updated along the opposite direction of this gradient, with the update magnitude controlled by the hyperparameter, the learning rate. An excessively large learning rate may lead to oscillations, while an excessively small rate results in slow convergence.

[0082] This embodiment optimizes independently axis by axis through hierarchical tuning and physical isolation, thereby blocking parameter coupling, eliminating randomness caused by manual intervention, ensuring the consistency of performance of batch products, and greatly improving the tuning efficiency of PID control parameters. In addition, it has the ability to adapt to structural changes, and can recalibrate the PID control parameters online according to the changed antenna structure, which greatly reduces the equipment operation and maintenance costs.

[0083] It is important to note that currently, the common practice in this field is to use a single integrated inertial navigation module for unified acquisition of data from the servo axes. This reduces hardware costs and simplifies hardware installation and wiring complexity, rather than using separate sensors for each motor axis. The traditional approach only requires individual tuning of each axis based on the corresponding sensor data, eliminating the issue of inter-axis coupling, which is not considered in this solution. Therefore, the real-time acquisition of the angular velocities corresponding to each satellite antenna servo axis described in this solution uses data collected by the same inertial navigation module.

[0084] In one embodiment of this specification, the specific iterative update steps for the control parameter group corresponding to any follower axis are as follows:

[0085] The control parameter set includes proportional coefficient, integral time coefficient, and derivative time coefficient. The gradient descent method is used to iteratively update the control parameter set corresponding to the satellite antenna servo axis based on inertial navigation information, to obtain and solidify the calibrated control parameter set for the satellite antenna servo axis, including:

[0086] S1. Obtain the first inertial navigation information based on the current control parameter group and the first disturbance step size of the corresponding proportional coefficient of the satellite antenna follower axis, and update the proportional coefficient of the satellite antenna follower axis based on the first inertial navigation information using the gradient descent method.

[0087] S2. Based on the current control parameter group and the second disturbance step size of the corresponding integral time coefficient of the satellite antenna follower axis, obtain the second inertial navigation information, and use the gradient descent method to update the integral time coefficient of the satellite antenna follower axis based on the second inertial navigation information;

[0088] S3. Based on the current control parameter group and the third disturbance step size of the corresponding differential time coefficient of the satellite antenna follower axis, obtain the third inertial navigation information, and use the gradient descent method to update the differential time coefficient of the satellite antenna follower axis based on the third inertial navigation information.

[0089] S4. Obtain the fourth inertial navigation information based on the current control parameter group corresponding to the satellite antenna follower axis, and calculate the objective function value based on the fourth inertial navigation information. When the objective function value is greater than or equal to the preset value, return to step S1 and iterate again.

[0090] Repeat the above steps until the calibration conditions are met, then complete the iteration and use the current control parameter set as the calibrated control parameter set corresponding to the satellite antenna follower axis for solidification.

[0091] To illustrate, the three parameters (Kp, Ti, Td) of a PID controller are not independent; there is a significant coupling effect between them. To address this coupling effect, this scheme updates Kp, Ti, and Td sequentially and collaboratively as a single iteration, rather than iterating over one parameter at a time to find its optimal value before iterating over another. For example, if Kp is tuned individually, this "optimal Kp" is based on the assumption that Ti and Td remain constant. However, when Ti and Td are subsequently adjusted, the system's dynamic characteristics change, and the previously tuned Kp may no longer be truly optimal. This collaborative iterative approach considers the interaction of all three parameters simultaneously in each iteration, avoiding parameter conflicts and ultimately finding the best balance point with the cooperation of all three parameters, rather than a local optimum. Since the proportional term Kp has the most significant impact on the system, prioritizing its optimization can effectively reduce the number of parameter iterations. The integral term Ti is used to eliminate steady-state error and relies on the stable environment created by the proportional term. The derivative term Td can predict trends and suppress overshoot, but it can also amplify noise. Therefore, the derivative term should be updated only after the proportional and integral terms have been updated and the main dynamic characteristics of the system have been addressed. This enables PID control in vehicle-mounted and shipborne satellite antenna scenarios, prioritizing proportional control for rapid response, then integral control to eliminate accumulated errors, and finally derivative control to suppress jitter.

[0092] It should be noted that the first perturbation step size Δkp, the second perturbation step size Δti, and the third perturbation step size Δtd are all set values, and their magnitudes directly affect the convergence speed, accuracy, and stability of the parameter update algorithm. Setting them too small will result in high accuracy at the optimum but will increase the number of iterations and reduce the convergence speed; setting them too large may cause oscillations around the optimum or even prevent convergence.

[0093] Explanatoryly, the current control parameter set (Kp, Ti, Td) is composed of the current Kp, Ti, and Td, and the disturbance control parameter set (Kp±Δkp, Ti, Td) is generated by the first disturbance step size Δkp corresponding to Kp. The first inertial navigation information includes the inertial navigation information collected under the current control parameter set conditions and the disturbance control parameter set conditions respectively. The cumulative time of each of them is the pointing deviation angle of the follower axis. Kp is updated using the gradient descent method to obtain Kp`; the current control parameter set (Kp±Δkp, Ti, Td) is composed of the current Kp`, Ti, and Td. The system first generates a set of perturbation control parameters (Kp`, Ti, Td) based on the second perturbation step size Δti corresponding to Ti. Similarly, the second inertial navigation information is updated using gradient descent to obtain Ti`. The current control parameter set (Kp`, Ti`, Td) is then formed from the current Kp`, Ti`, and Td. The third perturbation step size Δtd corresponding to Td generates another set of perturbation control parameters (Kp`, Ti`, Td±Δtd). The third inertial navigation information is updated again using gradient descent to obtain Td`. This completes one iteration. After this iteration, based on the inertial navigation information acquired under the current control parameter set (Kp`, Ti`, Td`), the objective function value is calculated. It is then determined whether the calibration conditions are met. If met, the iteration stops and the parameters are fixed; otherwise, the iteration continues. Calibration conditions can include the number of iterations, iteration accuracy, etc.

[0094] In one embodiment of this specification, the specific update steps for any control parameter in the control parameter group are as follows: The control parameter group corresponding to the satellite antenna servo axis is iteratively updated based on inertial navigation information using the gradient descent method, including:

[0095] For any control parameter in the control parameter group, the disturbance control parameter group is obtained based on the disturbance step size corresponding to the control parameter and the current control parameter group corresponding to the satellite antenna follower axis;

[0096] Obtain the inertial navigation information segments corresponding to the current control parameter group and the disturbance control parameter group of the satellite antenna follower axis;

[0097] Based on the inertial navigation information segments corresponding to the current control parameter group and the disturbance control parameter group, the pointing error information corresponding to the current control parameter group and the disturbance control parameter group is obtained. The pointing error information includes the cumulative angular velocity value corresponding to different acquisition times within the inertial navigation information segment.

[0098] The control parameter is updated based on the pointing error information corresponding to the current control parameter set and the disturbance control parameter set, respectively.

[0099] Repeat the above steps until every control parameter in the control parameter group corresponding to the satellite antenna follower axis has been updated.

[0100] Explaining this, taking the update of the control parameter group Kp in the pitch axis control parameter group update stage as an example, the current control parameter group (Kp, Ti, Td) is composed of the current Kp, Ti, and Td. The disturbance control parameter groups (Kp + Δkp, Ti, Td) and (Kp - Δkp, Ti, Td) are generated from the disturbance step size Δkp corresponding to Kp. Inertial navigation information is collected under the conditions of the current control parameter group and each disturbance control parameter group, forming their respective corresponding inertial navigation information segments. The cumulative angular velocity value at each acquisition moment is the pointing deviation angle of the servo axis at that moment. A larger pointing deviation angle indicates a larger pointing error, thus determining the update direction of Kp, resulting in Kp'. Instead of solely relying on the pointing deviation angle at a certain moment or the final pointing deviation angle within the inertial navigation information segment, a more comprehensive evaluation of the system's dynamic performance is performed by integrating the deviation angles at each acquisition moment within the inertial navigation information segment, guiding the accuracy of parameter updates.

[0101] In one embodiment of this specification:

[0102] The control parameter is updated based on the pointing error information corresponding to the current control parameter set and the disturbance control parameter set, including:

[0103] Based on the pointing error information corresponding to the current control parameter group and the disturbance control parameter group respectively, the mean square value of all cumulative angular velocity values ​​in the pointing error information corresponding to the current control parameter group and the disturbance control parameter group is obtained respectively.

[0104] When the mean square value corresponding to the current control parameter group is greater than the mean square value corresponding to the disturbance control parameter group, the control parameter is updated based on the disturbance step size corresponding to the control parameter.

[0105] For illustrative purposes, let's take updating Kp in the control parameter group as an example (the same applies to other control parameters):

[0106]

[0107] in, This represents the cumulative angular velocity value at acquisition time k corresponding to the current control parameter set, where n is the total acquisition time in the error information. This is the mean square value corresponding to the current control parameter group.

[0108] Based on the idea of ​​gradient descent, the mean square value corresponding to the current parameter set is evaluated. The mean square value of the disturbance control parameter group and its vicinity , The size of the parameter Kp is used to intelligently adjust the parameter Kp in order to find the Kp value that minimizes the system performance index S.

[0109] For example, when Greater than Less than When, Kp is updated to Kp + Δkp; when Less than Greater than When, Kp is updated to Kp - Δkp; when All greater than and At that time, Kp according to and The smaller one will be updated.

[0110] Interpretive analysis reveals that updating control parameters using a mean square comparison method offers significant advantages over other approaches. Calculating the square of the cumulative angular velocity values ​​serves two purposes: firstly, it unifies the pointing deviation angles represented by the cumulative angular velocities in different directions, preventing the cancellation of pointing deviation angles in different directions and thus reducing the mean square value, which could lead to misjudgments (e.g., pointing deviation angles continuously varying between +0.3° and -0.3°). Secondly, it amplifies the characteristics of large cumulative angular velocities in the error information, allowing for a clearer distinction of the dynamic performance of different control parameter groups. The average of the squares of each cumulative angular velocity value is calculated to measure the overall degree of deviation in the error information at different acquisition times.

[0111] In one embodiment of this specification, the adaptive calibration method further includes:

[0112] When the mean square value corresponding to the current control parameter group is less than the mean square value corresponding to the disturbance control parameter group, the control parameter is updated based on the disturbance step size corresponding to the control parameter and the first and second derivatives of the mean square value corresponding to the current control parameter group.

[0113] Illustratively, a variant derived from gradient descent improves the efficiency and stability of parameter iteration by taking into account both the first and second derivatives of the mean square value, thus achieving more robust convergence in complex parameter spaces.

[0114] Specifically, taking updating Kp in the control parameter group as an example (the same applies to other control parameters), the parameter update rule is as follows:

[0115]

[0116] in, This represents the current value of the scaling factor at the k-th iteration. This is the updated value of the scaling factor after the k-th iteration.

[0117] Explanatoryly, the above parameter update rule dynamically adjusts the disturbance step size using the first and second derivatives of the mean square value S(Kp) corresponding to the current control parameter set, achieving this even when... All less than and Small updates to the control parameters can still be made when

[0118] The first derivative of the mean square value S(Kp) (i.e., the gradient, representing the slope of the tangent line of the system performance index S at ):

[0119]

[0120] The second derivative of the mean square value S(Kp) (i.e., the curvature, representing the degree of change in the gradient, and the rate of change of the slope of the tangent line of the system performance index S at ):

[0121]

[0122] In the parameter update rule, the current value of the proportional coefficient at the k-th iteration is used as the starting point for optimization. The fractional part is the result of dividing the first derivative of the mean square value S(Kp) by the second derivative, representing an estimate of the offset of the minimum point of the system performance index S. The magnitude and sign of the fractional part together determine the update direction and step size of the control parameter. If S(Kp + Δkp) > S(Kp - Δkp), the numerator is positive, meaning it is better to decrease the control parameter. If S(Kp + Δkp) < S(Kp - Δkp), the numerator is negative, meaning it is better to increase the control parameter. If the denominator value is large, it means that the system performance index S changes steeply near the Kp point, indicating that a smaller update amplitude is required to prevent overshoot. If the denominator value is small, it means that the system performance index S changes flatly near the Kp point, indicating that a larger update amplitude is required to quickly cross the flat region. Subtracting the offset estimate from the current value of the proportional coefficient gives the updated value of the proportional coefficient, thereby dynamically adjusting the perturbation step size Δkp to achieve small updates to the control parameters, making the control parameters closer to the optimal point and improving the parameter calibration accuracy.

[0123] In this embodiment, there is no need to construct an accurate mathematical model of the system performance index S. Optimization is guided only by applying perturbations and observing the changes in the performance index S, which is suitable for engineering practice. Moreover, the update step size is not fixed but is dynamically adjusted based on the perturbation changes, combining rapidity and stability. Additionally, the calculation is relatively simple. Only three performance evaluations (the current point, the positive perturbation point, and the negative perturbation point) are required to complete one update of the control parameter.

[0124] In one embodiment of this specification:

[0125] The objective function value is the rate of change of the mean square value of the cumulative values of all angular velocities in the pointing error information corresponding to the control parameter group after the most recent iteration and the control parameter group after the previous iteration, respectively.

[0126] Interpretively, the inertial navigation information segments corresponding to the control parameter sets after two iterations are obtained, and then the corresponding pointing error information is obtained. The mean square value of the cumulative angular velocity in each corresponding pointing error information can be calculated. The rate of change of the mean square value is used as the calibration condition for completing the iteration. A larger rate of change of the mean square value indicates that the pointing error generated by the control parameter set after the most recent iteration has not yet stabilized, and further iteration is needed. A smaller rate of change of the mean square value indicates that a set of control parameters with excellent performance has been obtained after the most recent iteration, and the system is very close to a local optimum, i.e., approaching convergence. Further iterations with minor adjustments are unlikely to improve system performance further. To avoid unnecessary calculations, this objective function value is used as the basis for judging parameter performance, saving computational resources and improving tuning efficiency.

[0127] It is easy to understand that when calculating the objective function value after the first iteration, the corresponding "control parameter set after the previous iteration" is the control parameter set corresponding to the satellite antenna follower shaft after initializing the PID control parameters.

[0128] In one embodiment of this specification:

[0129] The calibration condition is that the objective function value for each of the consecutive preset number of iterations is less than the preset value.

[0130] Interpretively, in complex satellite antenna servo systems, sensor measurement noise, transient interference from the external environment, or the algorithm's own perturbation step size can all accidentally cause the objective function value to change very little in a particular iteration. If parameters are locked based on a single judgment, it's highly likely that a noise-affected, not truly optimal, parameter point has been locked. To avoid accidental convergence, the dynamic stability of the parameters must be verified. Furthermore, even if an optimal point is found, it's necessary to ensure that the corresponding control parameter set is robust—that is, the system performance is excellent within a small range around that point in the parameter space, rather than a point on the edge where performance deteriorates drastically with slight parameter perturbations. Distinguishing between "true convergence" and "false convergence" ensures the reliability of locked parameters and the optimal performance of the system.

[0131] For example, the calibration condition is that the objective function value corresponding to each of the five consecutive iterations is less than 1%.

[0132] Working principle:

[0133] The PID control parameters include control parameter groups corresponding to the three follower axes, and each control parameter group includes Kp, Ti, and Td.

[0134] The system simulates sea state testing by applying a step disturbance to the three-axis control gimbal using the oscillating platform.

[0135] When the system is powered on, it first enters the parameter initialization mode, controls each motor shaft to run to the middle position, then locks each follower shaft, starts collecting inertial navigation information, and waits for parameter tuning.

[0136] After initializing the PID control parameters, each follower axis is independently tuned according to the tuning sequence:

[0137] Unlock the pitch axis and begin tuning the pitch axis control parameter group.

[0138] Pitch axis parameters are fixed.

[0139] Unlock the roll axis and start tuning the roll axis control parameter group.

[0140] Roll axis parameters are fixed.

[0141] Unlock the azimuth axis and start tuning the azimuth axis control parameter group.

[0142] Azimuth axis parameters are fixed.

[0143] For updating the control parameter set of any follower axis: the control parameter set is updated iteratively according to the gradient descent rule, and parameters Kp, Ti, and Td are updated sequentially in each iteration. The objective function value is calculated after each iteration.

[0144] For a single iteration, the update of any control parameter in the control parameter group is as follows: under the conditions of the current control parameter group and the disturbance control parameter group, inertial navigation information is collected to obtain the corresponding inertial navigation information segments, and the mean square value S is calculated based on the inertial navigation information segments. The control parameters are then updated after comparing the mean square value S.

[0145] One iteration is completed after Kp, Ti, and Td are updated in sequence.

[0146] Repeat the iteration multiple times until the objective function value for each of the next preset number of iterations is less than the preset value, at which point the iteration ends and the latest calibrated control parameter set is fixed. Then begin the update and iteration process for the control parameter set of the next follower axis.

[0147] Once all control parameter groups for the three follower axes are calibrated and solidified, the adaptive calibration of the PID control parameters is completed, and the calibrated PID control parameters are obtained.

[0148] The foregoing has described specific embodiments of this specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims may be performed in a different order than that shown in the embodiments and may still achieve the desired result. Furthermore, the processes depicted in the drawings do not necessarily require the specific or sequential order shown to achieve the desired result. In some embodiments, multitasking and parallel processing are possible or may be advantageous.

[0149] Please refer to the following. Figure 2 , Figure 2 This is a schematic diagram of the structure of an adaptive calibration system for PID control parameters of a satellite antenna provided in the embodiments of this specification.

[0150] The adaptive calibration system 200 includes an acquisition module 201, a data acquisition module 202, and a calibration module 203;

[0151] The acquisition module 201 acquires the inter-axis follower nesting relationship of the satellite antenna follower axes, which include the roll axis, pitch axis and azimuth axis; based on the inter-axis follower nesting relationship, the satellite antenna follower axes are sorted from the inner nesting layer to the outer nesting layer to obtain the tuning order of the satellite antenna follower axes;

[0152] The acquisition module 202 initializes the PID control parameters, which include a control parameter group corresponding to each satellite antenna follower axis; it locks all satellite antenna follower axes and acquires the angular velocity corresponding to each satellite antenna follower axis in real time to form inertial navigation information;

[0153] The calibration module 203 unlocks and calibrates each satellite antenna servo axis sequentially based on the tuning order. For any unlocked satellite antenna servo axis, the gradient descent method is used to iteratively update the control parameter set corresponding to the satellite antenna servo axis based on the inertial navigation information to obtain the calibrated control parameter set corresponding to the satellite antenna servo axis and solidify it. Then, the next satellite antenna servo axis is unlocked. This process continues until the calibrated control parameter set corresponding to each satellite antenna servo axis is completely solidified, resulting in the calibrated PID control parameters.

[0154] The various embodiments in this specification are described in a progressive manner. Similar or identical parts between embodiments can be referred to interchangeably. Each embodiment focuses on its differences from other embodiments. In particular, the adaptive calibration system embodiments are basically similar to the adaptive calibration method embodiments, so the description is relatively simple; relevant parts can be referred to the descriptions of the adaptive calibration method embodiments.

[0155] Please see Figure 3 The diagram shown is a structural schematic of a satellite antenna servo control system provided in an embodiment of this specification.

[0156] The servo control system 300 includes:

[0157] The electronic gyroscope 301 collects the angular velocity of each satellite antenna 401's follower axis in real time to obtain inertial navigation information.

[0158] Gravity acceleration sensor 302 collects the tilt angle value of satellite antenna 401 in real time;

[0159] Satellite signal acquisition unit 303 collects the satellite signal strength received by satellite antenna 401 in real time;

[0160] The inner loop control unit 304 includes an adaptive calibration system for the PID control parameters of a satellite antenna 401, which outputs a first follow-up control signal based on the calibrated PID control parameters obtained by calibrating the inertial navigation information collected by the electronic gyroscope 301.

[0161] The intermediate loop control unit 305 outputs a second follow-up control signal based on the tilt angle value of the satellite antenna 401 to correct the control error of the inner loop control unit 304;

[0162] The outer loop control unit 306 uses a conical scanning algorithm to output a third follow-up control signal based on the satellite signal strength to compensate for the tracking error generated after the inner loop control unit 304 and the intermediate loop control unit 305 perform follow-up control.

[0163] Explained, the electronic gyroscope 301 collects angular velocities, which, accumulated over time, represent the angular displacement of each follower axis. Based on the magnitude of gravitational acceleration, the overall tilt angle of the satellite antenna 401 is calculated. Typically, the data collected by the gravity acceleration sensor 302 and the electronic gyroscope 301 are fused using algorithms such as Kalman filtering or complementary filtering to calculate the tilt angle. The satellite signal acquisition unit 303 includes a receiver for receiving satellite downlink signals and a signal acquisition module. Based on the data acquired by the signal acquisition module, the signal strength and signal-to-noise ratio of the downlink signal are calculated to measure the alignment accuracy of the satellite antenna 401. The conical scanning algorithm is a commonly used technique for satellite alignment compensation in this field and will not be elaborated upon here.

[0164] Explained, the system first uses angular velocity signals as the inner loop control, then uses gravity acceleration sensor 302 as the angle loop control to correct velocity loop control errors, obtaining the correct attitude and ensuring the accuracy of antenna surface tracking. Finally, a conical scanning algorithm is used to compensate for tracking errors by searching for the maximum satellite signal strength. The three control loops work together to achieve precise satellite antenna 401 tracking control. The gravity acceleration sensor 302 and the electronic gyroscope 301 together form an upper-mounted inertial navigation system, mounted on the pitch axis 402 mechanical structure, moving synchronously with the antenna surface of the satellite antenna 401.

[0165] It is important to note that the inner loop control of angular velocity has the greatest impact on the antenna servo performance. PID control algorithms are typically used. Therefore, this solution utilizes an adaptive calibration system for PID control parameters to calibrate the PID parameters. The calibrated PID parameters are then used for servo control to achieve optimal performance of the inner loop control of angular velocity.

[0166] Please see Figure 4 The diagram shown is a structural schematic of a satellite antenna follow-up control device provided in an embodiment of this specification.

[0167] The servo control device includes a three-axis control gimbal that carries the satellite antenna 401, a motor drive module that drives the three-axis control gimbal, and the aforementioned satellite antenna 401 servo control system 300.

[0168] The control nesting relationship of the three-axis gimbal controlling the satellite antenna 401 is as follows: the pitch axis 402 is located in the inner layer, the roll axis 403 is located in the middle layer, and the azimuth axis 404 is located in the outer layer.

[0169] The motor drive module drives the three-axis control gimbal for follow-up control based on the first follow-up control signal, the second follow-up control signal and the third follow-up control signal output by the follow-up control system 300.

[0170] Explanatory, such as Figure 4 As shown, in this embodiment, the mechanical structure of the three-axis control gimbal is configured such that the pitch axis 402 is nested in the roll axis 403, and the roll axis 403 is nested in the azimuth axis 404. The satellite antenna 401 is used to control the gimbal step by step, which corresponds to the tuning sequence of pitch axis 402 first, then roll axis 403 and then azimuth axis 404. This hierarchical decoupling sequence blocks the parameter transmission path step by step from the inside out, which is typical and scientific.

[0171] It should be noted that the hierarchical tuning strategy in this invention solves the mathematical difficulties caused by multi-axis coupling through physical isolation. The tuning sequence strictly follows the nesting relationship of each servo axis in the gimbal structure, and this nesting relationship is determined by the importance of each axis to satellite alignment. The pitch angle change directly affects the antenna's elevation angle to the satellite, therefore it has the highest priority; the roll axis 403 is used to suppress high-frequency ship roll and requires rapid compensation, therefore it has the second highest priority; and the azimuth axis 404 responds to low-frequency yaw, therefore it is tuned last. Other parameter tuning methods that also employ a hierarchical decoupling strategy and adaptively adjust the hierarchical decoupling sequence according to the nesting relationship of each axis in their own gimbal structure are all essentially the same technical solutions as this one.

[0172] Please see Figure 5 The diagram shown is a structural schematic of an electronic device provided in an embodiment of this specification.

[0173] like Figure 5 As shown, the electronic device 500 may include: at least one processor 501, at least one network interface 504, user interface 503, memory 505, and at least one communication bus 502.

[0174] The communication bus 502 can be used to realize the connection and communication of the above components.

[0175] The user interface 503 may include buttons, and the optional user interface may also include a standard wired interface or a wireless interface.

[0176] The network interface 504 may include, but is not limited to, Bluetooth modules, NFC modules, Wi-Fi modules, etc.

[0177] The processor 501 may include one or more processing cores. The processor 501 connects to various parts within the electronic device 500 using various interfaces and lines. It executes various functions and processes data by running or executing instructions, programs, code sets, or instruction sets stored in the memory 505, and by calling data stored in the memory 505. Optionally, the processor 501 may be implemented using at least one hardware form of DSP, FPGA, or PLC. The processor 501 may integrate one or more of the following: CPU, GPU, and modem. The CPU primarily handles the operating system, user interface, and applications; the GPU is responsible for rendering and drawing the content to be displayed on the screen; and the modem handles wireless communication. It is understood that the modem may also not be integrated into the processor 501 and may be implemented as a separate chip.

[0178] The memory 505 may include RAM or ROM. Optionally, the memory 505 may include a non-transitory computer-readable medium. The memory 505 may be used to store instructions, programs, code, code sets, or instruction sets. The memory 505 may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for at least one function (such as touch function, sound playback function, image playback function, etc.), instructions for implementing the above-described method embodiments, etc.; the data storage area may store data involved in the above-described method embodiments, etc. Optionally, the memory 505 may also be at least one storage device located remotely from the aforementioned processor 501. As a computer storage medium, the memory 505 may include an operating system, a network communication module, a user interface module, and an adaptive calibration application. The processor 501 may be used to call the adaptive calibration application stored in the memory 505 and execute the steps of the adaptive calibration method mentioned in the foregoing embodiments.

[0179] This specification also provides a computer-readable storage medium storing instructions that, when executed on a computer or processor, cause the computer or processor to perform one or more steps in the above-described adaptive calibration method embodiments. If the constituent modules of the above-described electronic device are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium.

[0180] In the above embodiments, implementation can be achieved, in whole or in part, through software, hardware, firmware, or any combination thereof. When implemented in software, it can be implemented, in whole or in part, as a computer program product. A computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the flow or function according to the embodiments of this specification is generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in or transmitted through a computer-readable storage medium. The computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, Digital Subscriber Line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that integrates one or more available media. The available media can be magnetic media (e.g., floppy disks, hard disks, magnetic tapes), optical media (e.g., Digital Versatile Discs (DVDs)), or semiconductor media (e.g., Solid State Disks (SSDs)).

[0181] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. This program can be stored in a computer-readable storage medium, and when executed, it can include the processes of the embodiments of the methods described above. The aforementioned storage medium includes various media capable of storing program code, such as ROM, RAM, magnetic disks, or optical disks. Unless otherwise specified, the technical features of this embodiment and its implementation can be combined arbitrarily.

[0182] The above embodiments are merely preferred embodiments described in this specification and are not intended to limit the scope of this specification. Any modifications and improvements made by those skilled in the art to the technical solutions of this specification without departing from the spirit of this specification should fall within the protection scope defined by the claims of this specification.

Claims

1. A method for adaptive calibration of PID control parameters of a satellite antenna, characterized in that, The method comprises the following steps: obtaining an inter-axis follow-up nesting relationship of satellite antenna follow-up axes, the satellite antenna follow-up axes comprising a roll axis, a pitch axis and an azimuth axis; sequencing the satellite antenna follow-up axes from the inner layer to the outer layer of the nesting based on the inter-axis follow-up nesting relationship to obtain a setting sequence of the satellite antenna follow-up axes; initializing PID control parameters, the PID control parameters comprising a control parameter group corresponding to each satellite antenna follow-up axis; locking all the satellite antenna follow-up axes and collecting the angular velocity of each satellite antenna follow-up axis in real time to obtain inertial navigation information; unlocking and calibrating the satellite antenna follow-up axes in sequence based on the setting sequence; for any unlocked satellite antenna follow-up axis, iteratively updating the control parameter group corresponding to the satellite antenna follow-up axis based on the inertial navigation information by using the gradient descent method to obtain the calibrated control parameter group corresponding to the satellite antenna follow-up axis and solidify the calibrated control parameter group, and then the axis remains unlocked and the next satellite antenna follow-up axis is unlocked; until the calibrated control parameter groups corresponding to all the satellite antenna follow-up axes are all solidified, obtaining the calibrated PID control parameters.

2. The adaptive calibration method for PID control parameters of a satellite antenna according to claim 1, characterized in that, The control parameter group comprises a proportional coefficient, an integral time coefficient and a differential time coefficient; the iteratively updating the control parameter group corresponding to the satellite antenna follow-up axis based on the inertial navigation information by using the gradient descent method to obtain the calibrated control parameter group corresponding to the satellite antenna follow-up axis and solidify the calibrated control parameter group comprises: S1, obtaining first inertial navigation information based on the current control parameter group corresponding to the satellite antenna follow-up axis and a first perturbation step of the corresponding proportional coefficient, and updating the proportional coefficient corresponding to the satellite antenna follow-up axis based on the first inertial navigation information by using the gradient descent method; S2, obtaining second inertial navigation information based on the current control parameter group corresponding to the satellite antenna follow-up axis and a second perturbation step of the corresponding integral time coefficient, and updating the integral time coefficient corresponding to the satellite antenna follow-up axis based on the second inertial navigation information by using the gradient descent method; S3, obtaining third inertial navigation information based on the current control parameter group corresponding to the satellite antenna follow-up axis and a third perturbation step of the corresponding differential time coefficient, and updating the differential time coefficient corresponding to the satellite antenna follow-up axis based on the third inertial navigation information by using the gradient descent method; S4, obtaining fourth inertial navigation information based on the current control parameter group corresponding to the satellite antenna follow-up axis, and calculating a target function value based on the fourth inertial navigation information, and returning to step S1 for iteration again when the target function value is greater than or equal to a preset value; repeating the above steps until the iteration is completed when the calibration condition is met, and solidifying the current control parameter group as the calibrated control parameter group corresponding to the satellite antenna follow-up axis.

3. The adaptive calibration method for PID control parameters of a satellite antenna according to claim 2, characterized in that, The iteratively updating the control parameter group corresponding to the satellite antenna follow-up axis based on the inertial navigation information by using the gradient descent method comprises: for any control parameter in the control parameter group, obtaining a perturbed control parameter group based on the perturbation step corresponding to the control parameter and the current control parameter group corresponding to the satellite antenna follow-up axis; obtaining the inertial navigation information segments corresponding to the current control parameter group and the perturbed control parameter group corresponding to the satellite antenna follow-up axis; Based on the inertial navigation information corresponding to the current control parameter set and the disturbance control parameter set, the pointing error information corresponding to the current control parameter set and the disturbance control parameter set is obtained, and the pointing error information includes the angular velocity cumulative value corresponding to each collection time in the inertial navigation information; The control parameter is updated based on the pointing error information corresponding to the current control parameter set and the disturbance control parameter set; The above steps are repeated until each control parameter in the control parameter set corresponding to the satellite antenna servo shaft is updated.

4. The adaptive calibration method for PID control parameters of a satellite antenna according to claim 3, characterized in that, The control parameter is updated based on the pointing error information corresponding to the current control parameter set and the disturbance control parameter set, including: Based on the inertial navigation information corresponding to the current control parameter set and the disturbance control parameter set, the pointing error information corresponding to the current control parameter set and the disturbance control parameter set is obtained, and the pointing error information includes the angular velocity cumulative value corresponding to each collection time in the inertial navigation information; When the mean square value corresponding to the current control parameter set is greater than the mean square value corresponding to the disturbance control parameter set, the control parameter is updated based on the disturbance step corresponding to the control parameter.

5. The adaptive calibration method for PID control parameters of a satellite antenna according to claim 4, characterized in that, Also includes: When the mean square value corresponding to the current control parameter set is less than the mean square value corresponding to the disturbance control parameter set, the control parameter is updated based on the disturbance step corresponding to the control parameter, and the first derivative and the second derivative of the mean square value corresponding to the current control parameter set.

6. The adaptive calibration method for PID control parameters of a satellite antenna according to claim 4, characterized in that, The target function value is the change rate of the mean square value of all angular velocity cumulative values in the pointing error information corresponding to the control parameter set after the last iteration and the control parameter set after the previous iteration.

7. The method of claim 6, wherein the PID control parameters are self-adaptively calibrated by using a PID control algorithm. The calibration condition is that the target function value corresponding to each of the continuous preset number of iterations is less than the preset value.

8. A system for adaptive calibration of satellite antenna PID control parameters, characterized in that, It includes an acquisition module, a collection module and a calibration module; The acquisition module acquires the inter-axis servo nesting relationship of the satellite antenna servo shaft, the satellite antenna servo shaft includes a roll axis, a pitch axis and an azimuth axis, and sorts each satellite antenna servo shaft from the inner layer to the outer layer of the nesting based on the inter-axis servo nesting relationship to obtain the setting order of the satellite antenna servo shaft; The collection module initializes the PID control parameter, the PID control parameter includes a control parameter set corresponding to each satellite antenna servo shaft, locks all satellite antenna servo shafts and collects the angular velocity of each satellite antenna servo shaft in real time to form inertial navigation information; The calibration module unlocks and calibrates each satellite antenna servo shaft in turn based on the setting order; for any unlocked satellite antenna servo shaft, the gradient descent method is used to update the control parameter set corresponding to the satellite antenna servo shaft based on the inertial navigation information to obtain the calibrated control parameter set corresponding to the satellite antenna servo shaft and solidify it, and then the shaft remains unlocked, and the next satellite antenna servo shaft is unlocked; until the calibrated control parameter set corresponding to each satellite antenna servo shaft is completely solidified, the calibrated PID control parameter is obtained.

9. A satellite antenna follow-up control system characterized by, It includes: An electronic gyroscope that collects the angular velocity of each satellite antenna servo shaft in real time to obtain inertial navigation information; A gravity acceleration sensor that collects the satellite antenna inclination value in real time; A satellite signal collector that collects the satellite signal strength received by the satellite antenna in real time; The inner loop control unit comprises the satellite antenna PID control parameter self-adaptive calibration system of claim 8, outputs a first servo control signal based on the calibrated PID control parameter obtained based on the inertial navigation information collected by the electronic gyroscope; The intermediate loop control unit outputs a second servo control signal based on the satellite antenna tilt angle value, to correct the control error of the inner loop control unit; The outer loop control unit outputs a third servo control signal based on the satellite signal strength using the conical scanning algorithm, to compensate for the tracking error generated after the servo control of the inner loop control unit and the intermediate loop control unit.

10. A satellite antenna follow-up control device characterized by comprising: The three-axis control holder comprises a three-axis control holder carrying a satellite antenna, a motor drive module driving the three-axis control holder, and the satellite antenna servo control system of claim 9; The control nesting relationship of the three-axis control holder controlling the satellite antenna servo is that the pitch axis is located in the inner layer, the roll axis is located in the intermediate layer, and the azimuth axis is located in the outer layer; The motor drive module drives the three-axis control holder to perform servo control based on the first servo control signal, the second servo control signal and the third servo control signal output by the servo control system.

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