Stable control method of pitch mechanism based on coordinated motion of two cylinders

Abstract

The present invention provides a pitch mechanism stabilization control method based on dual-cylinder coordinated motion, and relates to the technical field of pitch mechanism stabilization control. The method arranges sensors at key positions of the pitch mechanism to collect pitch angle and acceleration data in real time, and sets the load and friction coefficient based on this. The core of the method is to define and calculate the error of the pitch angle and its speed, and to use fuzzy control rule design and PID control real-time and dual-cylinder coordinated motion algorithm to ensure the stability and controllability of the system under the dynamic model. In the process of continuous feedback and verification, by comparing the simulated output of the model with the actual data, optimizing the control parameters, and setting the performance evaluation indicators under different working conditions, a comprehensive evaluation of the control system response time, overshoot and error is achieved, thereby improving the overall performance and stability of the pitch mechanism.

Description

Technical Field

[0001] The invention relates to the technical field of pitch mechanism stabilization control, and in particular to a pitch mechanism stabilization control method based on dual-cylinder coordinated motion. Background Art

[0002] The pitch mechanism of the dual-cylinder coordinated motion plays an important role in modern engineering and robotics, and is widely used in aerospace, unmanned driving, robotic arms and other fields. Its main function is to achieve complex motion trajectories and stable attitude control by accurately controlling the pitch angle. With the continuous advancement of technology, the performance requirements of these systems are getting higher and higher, including faster response speed, higher control accuracy and stronger anti-interference ability.

[0003] In this context, stability control becomes one of the key challenges in the design of the twin-cylinder pitch mechanism. Due to the nonlinear and coupled dynamic characteristics of the twin-cylinder system, traditional control methods often fail to meet the requirements in the face of complex environments and uncertainties. Therefore, engineers began to explore more advanced control strategies, such as the combination of fuzzy control and PID control, to make full use of their respective advantages to achieve efficient and reliable stability control.

[0004] These systems often require precise control under dynamic and complex conditions to ensure they remain stable under different loads and environmental changes. However, the control methods in the prior art often rely on simple linear control algorithms, which are prone to problems such as response lag, overshoot, and insufficient stability. These defects make it difficult for the system to maintain the expected performance in a high-load, rapidly changing environment, thus affecting the safety and reliability of the overall operation.

[0005] The prior art has the following deficiencies:

[0006] Many traditional control methods often rely on linear models, ignoring the effects of nonlinear characteristics and dynamic coupling of the system. This leads to a significant decrease in the performance of the control system in complex environments, especially when the load changes or external disturbances increase, and the inability to effectively maintain stability. This linear processing method limits the adaptability of the system to a certain extent, making it insufficiently robust in practical applications. Secondly, the feedback mechanism of the existing technology usually relies on simple sensor data and cannot fully utilize the predictive information provided by the dynamic model. This limitation makes the system slow to respond when dealing with instantaneous fluctuations and unexpected situations, affecting the overall control effect. In addition, existing control strategies often lack flexibility and intelligence. Many algorithms cannot automatically adjust parameters according to environmental changes, resulting in very different control performance under different operating conditions. Especially in dynamically changing application scenarios, this lack of adaptability control method is particularly fragile. With the improvement of technical requirements, how to achieve intelligent and adaptive control strategies has become an urgent problem to be solved.

[0007] The above information disclosed in this Background section is only for enhancement of understanding of the background of the present disclosure and therefore it may contain information that does not constitute the prior art that is already known to one of ordinary skill in the art. Summary of the invention

[0008] The object of the present invention is to provide a pitch mechanism stabilization control method based on dual-cylinder coordinated motion to solve the problems raised in the above background technology.

[0009] To achieve the above object, the present invention provides the following technical solutions:

[0010] The pitch mechanism stabilization control method based on the coordinated motion of two cylinders comprises the following specific steps:

[0011] Step 1: Mark the center position of the pitch platform of the pitch mechanism and the end of the pitch platform away from the pitch mechanism connection as key positions, arrange sensors at the key positions to collect the pitch angle data of the pitch mechanism, and set the load mass and friction coefficient of the dual cylinders;

[0012] Step 2: Calculate the pitch angle error and use it as the fuzzy input variable, set the fuzzy set and the corresponding membership function, and create fuzzy rules. Use fuzzy logic reasoning to convert the input variable into fuzzy output. Calculate the final fuzzy control output through fuzzy rules.

[0013] Step 3: Preliminarily set the parameters of the PID controller, obtain the PID control output according to the angle error at the current moment, and then combine the fuzzy control output with the PID control output to obtain the total elongation;

[0014] Step 4: Establish a dynamic model of dual-cylinder motion, construct dynamic equations, use numerical methods to solve the dynamic equations, verify the reliability of the dynamic model by comparing the pitch angle of the dynamic model with the actual value, and update the fuzzy control output and PID control output at the next moment based on the pitch angle output by the dynamic model;

[0015] Step 5: Conduct experiments on the dynamic model to obtain the absolute values ​​of response time, overshoot and pitch angle error under different loads and working conditions, and standardize the absolute values ​​of response time, overshoot and pitch angle error. Calculate the comprehensive evaluation quantity based on the standardized data, and take the average of the comprehensive evaluation quantity under different loads and working conditions as the final comprehensive evaluation quantity to evaluate the performance of fuzzy control and PID control.

[0016] Furthermore, the specific logic for arranging sensors and collecting relevant data is as follows:

[0017] A gyro sensor is installed at the center of the pitch platform of the pitch mechanism, and the gyro is aligned with the rotation axis of the pitch mechanism to collect pitch angle data. An accelerometer is arranged at one end of the pitch platform away from the pitch mechanism connection to collect acceleration data of the pitch mechanism. The load mass of the dual cylinder is set to , the friction coefficient is , It is the extension of the pitch mechanism when it is in static equilibrium without any control input.

[0018] Furthermore, the specific logic for calculating the final fuzzy control output is:

[0019] The formula for calculating the pitch angle error is:

[0020] ;

[0021] in, is the pitch angle error, is the target pitch angle, is the actual pitch angle;

[0022] Set the fuzzy control output to the extension of the double cylinder , use the triangular membership function to define the fuzzy set of pitch angles, the fuzzy set includes negative large, negative small, zero, positive small, positive large, set the range of pitch angle error , in degrees, the fuzzy set of pitch angles is:

[0023] The negative maximum range of pitch angle is defined as , the membership function expression is:

[0024] ;

[0025] The negative interval of pitch angle is defined as , the membership function expression is:

[0026] ;

[0027] The pitch angle zero interval is defined as , the membership function expression is:

[0028] ;

[0029] The positive interval of pitch angle is defined as , the membership function expression is:

[0030] ;

[0031] The positive range of pitch angle is defined as , the membership function expression is:

[0032] ;

[0033] in, They are the membership function expressions of the pitch angle fuzzy set negative large, negative small, zero, positive small, and positive large;

[0034] The specific logic for creating fuzzy rules is:

[0035] The fuzzy set of elongation is negative large, negative small, zero, positive small, positive large. Each rule maps the fuzzy state of the input variable to the fuzzy state of the output variable. Rule 1: If If the negative is large, the elongation Negative adjustment; Rule 2: If For a small negative, the elongation Negative small adjustment; Rule 3: If is zero, then the elongation Zero adjustment; Rule 4: If is positive and small, then the elongation is a small positive adjustment; Rule 5: If is positive, then the elongation Adjust for Zhengda;

[0036] The collected pitch angles are converted into fuzzy values. The minimum value combination rule is used to obtain the activation degree of each rule. The output sets of all rules are aggregated to form a comprehensive fuzzy output, and the fuzzy output is converted into elongation through the centroid method.

[0037] Furthermore, the specific logic for obtaining the total elongation is:

[0038] Preliminary setting of the maximum output value and proportional gain of the PID controller , integral gain , differential gain According to the system response, the parameters are tuned by the Ziegler-Nichols method, and the formula for calculating the control output is:

[0039] ;

[0040] in, Indicates the current The control output at the moment, Indicates the current The pitch angle error at time, are the proportional, integral and differential gains of the PID controller respectively, is the friction force;

[0041] The friction force is obtained based on the formula:

[0042] ;

[0043] in, is the acceleration due to gravity;

[0044] The formula used to obtain the total elongation is:

[0045] ;

[0046] in, For the current The total elongation at time, For the current The elongation at the moment, It is the maximum value of the PID controller output.

[0047] Furthermore, the specific logic for establishing the dynamic model of the dual-cylinder motion is as follows:

[0048] The formula for obtaining the linear velocity of the pitch mechanism is:

[0049] ;

[0050] in, is the linear velocity of the pitch mechanism, is the acceleration data read from the accelerometer;

[0051] The dynamic equation is constructed according to Newton's second law, based on the formula:

[0052] ;

[0053] in, For the current The pitch angle at the moment, For the current Linear velocity of the pitch mechanism at any moment;

[0054] Set every 10 For one control cycle, the dynamic equations are solved using numerical methods, the values ​​of the pitch angles at different time points are calculated, the simulated values ​​of the dual-cylinder dynamic model are compared with the actual pitch angle data to verify the accuracy of the dynamic model of the dual-cylinder motion, the inputs of the fuzzy control and PID control are updated, and the fuzzy control and PID controllers are recalculated based on the updated data, and the fuzzy control and PID controllers in steps 2-3 are repeated to predict the fuzzy control output and the output of the PID control at the next moment.

[0055] Furthermore, the specific logic for calculating the comprehensive evaluation amount is:

[0056] Response time is defined as the time from when the system starts responding to when the output reaches The overshoot is defined as the ratio of the maximum amplitude of the system output exceeding the target value to the target value. The formula is:

[0057] ;

[0058] in, is the overshoot, The maximum pitch angle reached by the system output;

[0059] The absolute value of the response time, overshoot and pitch angle error is calculated using Standardization processing, the comprehensive evaluation amount is calculated based on the standardized values, and the formula is:

[0060] ;

[0061] in, For comprehensive evaluation, is the absolute value of the pitch angle error, is the response time, is the weight of the absolute value of the pitch angle error, is the weight of response time, is the weight of the overshoot, ,and ;

[0062] The average value of the comprehensive evaluation quantity under different loads and working conditions is taken as the final comprehensive evaluation quantity, and the final comprehensive evaluation quantity is compared with the preset threshold. If the average value of the comprehensive evaluation quantity is lower than the preset threshold, the current strategy continues to be executed. If the average value of the comprehensive evaluation quantity is higher than the preset threshold, the fuzzy control and PID controller are updated and the control strategy is re-optimized.

[0063] In the above technical solution, the technical effects and advantages provided by the present invention are:

[0064] This method can respond to load changes and environmental disturbances in real time by dynamically adjusting the control strategy. It improves the system's adaptability to nonlinear characteristics and dynamic coupling, making the control performance more stable under complex environments and load changes. By optimizing the control algorithm, the control lag and instability problems existing in the prior art are solved, thereby significantly improving the control accuracy and stability of the pitch mechanism, ensuring safe and efficient operation under various working conditions. BRIEF DESCRIPTION OF THE DRAWINGS

[0065] Figure 1 It is a schematic diagram of the overall method flow of the present invention. DETAILED DESCRIPTION

[0066] In order to make the objectives, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with specific embodiments.

[0067] It should be noted that, unless otherwise defined, the technical terms or scientific terms used in the present invention should be understood by people with ordinary skills in the field to which the present invention belongs. The words "first", "second" and similar words used in the present invention do not indicate any order, quantity or importance, but are only used to distinguish different components. "Include" or "comprise" and similar words mean that the elements or objects appearing before the word include the elements or objects listed after the word and their equivalents, without excluding other elements or objects. "Connect" or "connected" and similar words are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. "Up", "down", "left", "right" and the like are only used to indicate relative positional relationships. When the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0068] Example:

[0069] See also Figure 1 , the present invention provides a technical solution:

[0070] The pitch mechanism stabilization control method based on the coordinated motion of two cylinders comprises the following specific steps:

[0071] Step 1: Mark the center position of the pitch platform of the pitch mechanism and the end of the pitch platform away from the pitch mechanism connection as key positions, arrange sensors at the key positions to collect the pitch angle data of the pitch mechanism, and set the load mass and friction coefficient of the dual cylinders;

[0072] In this embodiment, the specific logic for arranging sensors and collecting relevant data is as follows:

[0073] A gyro sensor is installed at the center of the pitch platform of the pitch mechanism, and the gyro is aligned with the rotation axis of the pitch mechanism to collect pitch angle data. An accelerometer is arranged at one end of the pitch platform away from the pitch mechanism connection to collect acceleration data of the pitch mechanism. The load mass of the dual cylinder is set to , the friction coefficient is , It is the extension of the pitch mechanism when it is in static equilibrium without any control input.

[0074] First, the arrangement of sensors at key positions can accurately obtain dynamic state information of the pitch mechanism. By installing a gyroscope at the center, the pitch angle can be monitored in real time to ensure accurate identification of the pitch motion; at the same time, the accelerometer pitch platform is located at one end away from the pitch mechanism connection, which can obtain the acceleration data of the pitch mechanism and further improve the understanding of the dynamic behavior of the system. Secondly, setting the load mass, friction coefficient and elongation of the twin cylinders at static equilibrium provides the necessary parameter basis for the control algorithm. These parameters directly affect the motion characteristics and stability of the pitch mechanism. Only when these variables are clear can a suitable control strategy be designed to keep the system stable under different load conditions. In addition, the consideration of the friction coefficient helps to evaluate the resistance that may occur during the movement and ensure that the control system can effectively cope with various interferences in actual operation.

[0075] Step 2: Calculate the pitch angle error and use it as the fuzzy input variable, set the fuzzy set and the corresponding membership function, and create fuzzy rules. Use fuzzy logic reasoning to convert the input variable into fuzzy output. Calculate the final fuzzy control output through fuzzy rules.

[0076] In this embodiment, the specific logic for calculating the final fuzzy control output is:

[0077] The formula for calculating the pitch angle error is:

[0078] ;

[0079] in, is the pitch angle error, is the target pitch angle, is the actual pitch angle;

[0080] Set the fuzzy control output to the extension of the double cylinder , use the triangular membership function to define the fuzzy set of pitch angles, the fuzzy set includes negative large, negative small, zero, positive small, positive large, set the range of pitch angle error , in degrees, the fuzzy set of pitch angles is:

[0081] The negative maximum range of pitch angle is defined as , the membership function expression is:

[0082] ;

[0083] The negative interval of pitch angle is defined as , the membership function expression is:

[0084] ;

[0085] The pitch angle zero interval is defined as , the membership function expression is:

[0086] ;

[0087] The positive interval of pitch angle is defined as , the membership function expression is:

[0088] ;

[0089] The positive range of pitch angle is defined as , the membership function expression is:

[0090] ;

[0091] in, They are the membership function expressions of the pitch angle fuzzy set negative large, negative small, zero, positive small, and positive large;

[0092] The specific logic for creating fuzzy rules is:

[0093] The fuzzy set of elongation is negative large, negative small, zero, positive small, positive large. Each rule maps the fuzzy state of the input variable to the fuzzy state of the output variable. Rule 1: If If the negative is large, the elongation It is a negative adjustment, and the negative adjustment elongation range is [-50,-30]; Rule 2: If For a small negative, the elongation It is a negative minor adjustment. The range of negative minor adjustment elongation reduction is [-30, -10]; Rule 3: If is zero, then the elongation For zero adjustment, the zero adjustment extension range is [-5,5]; Rule 4: If is positive and small, then the elongation is a positive minor adjustment, the positive minor adjustment elongation range is [10,30]; Rule 5: If is positive, then the elongation It is positive adjustment, the extension range of positive adjustment is [30,50], the unit is centimeter;

[0094] The collected pitch angles are converted into fuzzy values. The minimum value combination rule is used to obtain the activation degree of each rule. The output sets of all rules are aggregated to form a comprehensive fuzzy output, and the fuzzy output is converted into elongation through the centroid method.

[0095] Fuzzy control theory provides an effective tool to deal with the control problems of complex systems. In this embodiment, the use of fuzzy logic reasoning enables the system to maintain good control effects under fuzzy, nonlinear and uncertain conditions, which is a supplement and extension of traditional control methods. By defining the pitch angle error, the deviation between the current system state and the target state can be accurately evaluated. This error definition provides the basis for subsequent fuzzy control, enabling the control system to adjust the output more effectively and ensure the stability and accuracy of the pitch mechanism. The main advantage of applying fuzzy logic is that it handles uncertainty and imprecision. By setting fuzzy sets and membership functions, various input states can be flexibly handled, especially when there are fluctuations or uncertainties in the input data, fuzzy control can provide smooth and effective output. This is particularly important for dual-cylinder cooperative motion control in a dynamic environment. By creating fuzzy rules, the control system can dynamically adjust the output force according to the real-time pitch angle error. This adaptive ability enhances the stability of the system under different load and environmental conditions, enabling it to respond to changes more quickly. Through the minimum combination rule and the centroid method, the output of each fuzzy rule is aggregated into an elongation to ensure that the output is not just the result of a single rule, but a comprehensive response taking into account all input conditions. This combined output helps balance the various demands and avoids control instability or over-adjustment caused by a single factor.

[0096] Step 3: Preliminarily set the parameters of the PID controller, obtain the PID control output according to the angle error at the current moment, and then combine the fuzzy control output with the PID control output to obtain the total elongation;

[0097] In this embodiment, the specific logic for obtaining the total elongation is:

[0098] Preliminary setting of the maximum output value and proportional gain of the PID controller , integral gain , differential gain According to the system response, the parameters are tuned by the Ziegler-Nichols method, and the formula for calculating the control output is:

[0099] ;

[0100] in, Indicates the current The control output at the moment, Indicates the current The pitch angle error at the moment, are the proportional, integral and differential gains of the PID controller respectively, is the friction force;

[0101] The formula based on which the friction force is obtained is:

[0102] ;

[0103] in, is the acceleration due to gravity;

[0104] The formula used to obtain the total elongation is:

[0105] ;

[0106] in, For the current The total elongation at time, For the current The elongation at the moment, It is the maximum value of the PID controller output.

[0107] By preliminarily setting the parameters of the PID controller, fine control of the pitch angle error can be achieved. The PID controller combines proportional, integral and differential control strategies, and can effectively adjust different types of errors (steady-state error, dynamic error), thereby improving the response speed and stability of the system. Combining the PID control output with the fuzzy control output to form the total elongation can fully utilize the advantages of the two control strategies. Fuzzy control performs well in dealing with uncertainty and nonlinearity, while PID control can provide fast and linear response. Combining the outputs of the two can enable the system to achieve smoother control under various operating conditions. By using the Ziegler-Nichols method to tune the PID parameters, the parameters of the controller can be dynamically adjusted to make it more suitable for the dynamic characteristics of the actual system. This automatic adjustment mechanism enhances the system's adaptability to external disturbances and changing environments, ensuring good control performance at different operating stages. The output of the PID controller Directly affects the dynamic response of the system. By adding the formula, we take into account the relative strength of PID control within a normalized range. This approach makes the impact of the PID controller dynamic and proportional to the actual control demand. Represents the elongation provided by fuzzy control. Fuzzy controllers are usually based on empirical rules and fuzzy logic to deal with uncertainties and nonlinear systems, so it provides a basic elongation in the formula, which becomes the basis for superimposed adjustment of other factors. It is a quantitative expression of friction, usually related to the load mass m and the gravitational acceleration g. Introducing friction into the formula in the form of , we can understand that friction, as a factor that weakens the total output, affects the efficiency of the entire force output. It is the basic force output of the system under frictionless conditions. As the denominator of the ratio, it normalizes the effect of friction so that the effect of friction in different systems can be reasonably evaluated. By multiplying different factors, the response of the system can be expressed as a nonlinear synthesis. This is closer to the phenomenon of multiple factors interacting with each other in the actual system. Through normalization and proportional adjustment, it is ensured that the impact of each factor on the total output is moderate, so that the output will not be distorted when a single factor is extremely large or extremely small. The control and friction processing methods added to the formula allow the system to dynamically adjust the output under different states and conditions, reflecting flexible adaptability.

[0108] Step 4: Establish a dynamic model of dual-cylinder motion, construct dynamic equations, use numerical methods to solve the dynamic equations, verify the reliability of the dynamic model by comparing the pitch angle of the dynamic model with the actual value, and update the fuzzy control output and PID control output at the next moment based on the pitch angle output by the dynamic model;

[0109] In this embodiment, the specific logic for establishing the dynamic model of the dual-cylinder motion is as follows:

[0110] The formula for obtaining the linear velocity of the pitch mechanism is:

[0111] ;

[0112] in, is the linear velocity of the pitch mechanism, is the acceleration data read from the accelerometer;

[0113] The dynamic equation is constructed according to Newton's second law, based on the formula:

[0114] ;

[0115] in, For the current The pitch angle at the moment, For the current Linear velocity of the pitch mechanism at any moment;

[0116] Set every 10 For one control cycle, the dynamic equations are solved using numerical methods, the values ​​of the pitch angles at different time points are calculated, the simulated values ​​of the dual-cylinder dynamic model are compared with the actual pitch angle data to verify the accuracy of the dynamic model of the dual-cylinder motion, the inputs of the fuzzy control and PID control are updated, and the fuzzy control and PID controllers are recalculated based on the updated data, and the fuzzy control and PID controllers in steps 2-3 are repeated to predict the fuzzy control output and the output of the PID control at the next moment.

[0117] By establishing a dynamic model of the dual-cylinder motion and constructing dynamic equations, the mechanical behavior of the pitch mechanism during the motion process can be systematically described. This model can provide a theoretical basis for subsequent control strategies, so that the control algorithm can more accurately reflect the real dynamic characteristics of the system. The dynamic equations can be solved using numerical methods to effectively obtain the changes in pitch angle and pitch speed. This method can handle complex dynamic systems, provide real-time status updates, ensure that the system can respond to dynamic changes in a timely manner, and significantly improve the timeliness and accuracy of control. The reliability of the dynamic model can be verified by comparing the pitch angle of the simulated output with the actual measured value. If the output of the model is consistent with the actual value, the accuracy of the model can be confirmed, thereby enhancing the credibility of the entire control system. This process provides an important basis for the debugging and optimization of the control system. The inputs of fuzzy control and PID control are updated according to the simulated output to achieve closed-loop control. By continuously optimizing the control input, the system can adjust the output in real time to adapt to changes in the external environment and ensure the stability and accuracy of the pitch mechanism. This feedback mechanism is crucial to improving the overall control effect.

[0118] Step 5: Conduct experiments on the dynamic model to obtain the absolute values ​​of response time, overshoot and pitch angle error under different loads and working conditions, and standardize the absolute values ​​of response time, overshoot and pitch angle error. Calculate the comprehensive evaluation quantity based on the standardized data, and take the average of the comprehensive evaluation quantity under different loads and working conditions as the final comprehensive evaluation quantity to evaluate the performance of fuzzy control and PID control;

[0119] In this embodiment, the specific logic for calculating the comprehensive evaluation amount is:

[0120] Response time is defined as the time from when the system starts responding to when the output reaches The overshoot is defined as the ratio of the maximum amplitude of the system output exceeding the target value to the target value. The formula is:

[0121] ;

[0122] in, is the overshoot, The maximum pitch angle reached by the system output;

[0123] The absolute value of the response time, overshoot and pitch angle error is calculated using Standardization processing, the comprehensive evaluation amount is calculated based on the standardized values, and the formula is:

[0124] ;

[0125] in, For comprehensive evaluation, is the absolute value of the pitch angle error, is the response time, is the weight of the absolute value of the pitch angle error, is the weight of response time, is the weight of the overshoot, ,and ;

[0126] The average value of the comprehensive evaluation quantity under different loads and working conditions is taken as the final comprehensive evaluation quantity, and the final comprehensive evaluation quantity is compared with the preset threshold. If the average value of the comprehensive evaluation quantity is lower than the preset threshold, the current strategy continues to be executed. If the average value of the comprehensive evaluation quantity is higher than the preset threshold, the fuzzy control and PID controller are updated and the control strategy is re-optimized.

[0127] By setting the response time, overshoot and absolute value of pitch angle error under different loads and working conditions for experiments, the control performance of the dual-cylinder dynamic model can be fully evaluated. This multi-dimensional evaluation method can help identify the performance of the system under different conditions and ensure the adaptability and effectiveness of the control strategy. Standardizing the absolute values ​​of response time, overshoot, and pitch angle error can eliminate the influence of different dimensions and make the indicators comparable under the same standard. This processing method enhances the comparability between various performance indicators and helps to provide objective evaluation results. The constructed comprehensive evaluation quantity can provide an overall evaluation indicator for system performance. By integrating multiple important performance indicators into a single quantitative indicator, it is convenient to quickly evaluate the improvement effect when adjusting the control strategy. Recording the pitch angle under the best performance can provide a basis for strategy adjustment and parameter optimization in practical applications. By analyzing the best performance, a more accurate and efficient control strategy can be formulated to improve the overall performance of the system. At the same time, it provides data support for subsequent optimization.

[0128] Each indicator in the formula ( , , ) respectively reflect the stability, response speed and overshoot characteristics of the control system, which are key factors in evaluating control performance. By combining these indicators, the control capability and execution effect of the system can be fully reflected, avoiding the shortcomings of a single parameter. The angle error directly reflects the accuracy between the system output and the target, so the absolute value of the pitch angle error is considered to be the most important indicator. Too large an angle error may cause the system to fail to achieve the expected working state, so it has the largest weight; the response time is the speed at which the system reacts to input changes, affecting the overall dynamic performance. Especially in a dynamic environment, a fast response time is often necessary, and its weight is smaller but higher than the overshoot; the overshoot reflects the stability and overshoot of the system when it reaches the target value. Although excessive overshoot may cause system instability, its impact is small in some cases (especially systems with large dynamic changes). Such a weight setting ensures that the comprehensive evaluation can truly reflect the priority and characteristics of system performance. This constraint ensures that the comprehensive evaluation quantity is a normalized indicator, ensuring that the total contribution of the weighted combination of the three factors is 100%.

[0129] The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters in the formula are set by technicians in this field according to actual conditions.

[0130] The above embodiments may be implemented in whole or in part by software, hardware, firmware or any other combination thereof. When implemented by software, the above embodiments may be implemented in whole or in part in the form of a computer program product. Those skilled in the art may appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein may be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed by hardware or software methods depends on the specific application and design constraints of the technical solution.

[0131] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, and may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0132] The above description is only a specific implementation manner of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application.

Claims

1. A pitch mechanism stabilization control method based on dual-cylinder coordinated motion, characterized in that: The specific steps include: Step 1: Mark the center position of the pitch platform of the pitch mechanism and the end of the pitch platform away from the pitch mechanism connection as key positions, arrange sensors at the key positions to collect the pitch angle data of the pitch mechanism, and set the load mass and friction coefficient of the dual cylinders; Step 2: Calculate the pitch angle error and use it as the fuzzy input variable, set the fuzzy set and the corresponding membership function, and create fuzzy rules. Use fuzzy logic reasoning to convert the input variable into fuzzy output. Calculate the final fuzzy control output through fuzzy rules. Step 3: Preliminarily set the parameters of the PID controller, obtain the PID control output according to the angle error at the current moment, and then combine the fuzzy control output with the PID control output to obtain the total elongation; Step 4: Establish a dynamic model of dual-cylinder motion, construct dynamic equations, use numerical methods to solve the dynamic equations, verify the reliability of the dynamic model by comparing the pitch angle of the dynamic model with the actual value, and update the fuzzy control output and PID control output at the next moment based on the pitch angle output by the dynamic model; Step 5: Conduct experiments on the dynamic model to obtain the absolute values ​​of response time, overshoot and pitch angle error under different loads and working conditions, and standardize the absolute values ​​of response time, overshoot and pitch angle error. Calculate the comprehensive evaluation quantity based on the standardized data, and take the average of the comprehensive evaluation quantity under different loads and working conditions as the final comprehensive evaluation quantity to evaluate the performance of fuzzy control and PID control.

2. The pitch mechanism stabilization control method based on dual-cylinder coordinated motion according to claim 1 is characterized in that: The specific logic for arranging sensors and collecting relevant data is as follows: A gyro sensor is installed at the center of the pitch platform of the pitch mechanism, and the gyro is aligned with the rotation axis of the pitch mechanism to collect pitch angle data. An accelerometer is arranged at one end of the pitch platform away from the pitch mechanism connection to collect acceleration data of the pitch mechanism. The load mass of the dual cylinder is set to , the friction coefficient is , It is the extension of the pitch mechanism when it is in static equilibrium without any control input.

3. The pitch mechanism stabilization control method based on dual-cylinder coordinated motion according to claim 2 is characterized in that: The specific logic for calculating the final fuzzy control output is: The formula for calculating the pitch angle error is: ； in, is the pitch angle error, is the target pitch angle, is the actual pitch angle; Set the fuzzy control output to the extension of the double cylinder , use the triangular membership function to define the fuzzy set of pitch angles, the fuzzy set includes negative large, negative small, zero, positive small, positive large, set the range of pitch angle error , in degrees, the fuzzy set of pitch angles is: The negative maximum range of pitch angle is defined as , the membership function expression is: ； The negative interval of pitch angle is defined as , the membership function expression is: ； The pitch angle zero interval is defined as , the membership function expression is: ； The positive interval of pitch angle is defined as , the membership function expression is: ； The positive range of pitch angle is defined as , the membership function expression is: ； in, They are the membership function expressions of the pitch angle fuzzy set negative large, negative small, zero, positive small, and positive large; The specific logic for creating fuzzy rules is: The fuzzy set of elongation is negative large, negative small, zero, positive small, positive large. Each rule maps the fuzzy state of the input variable to the fuzzy state of the output variable. Rule 1: If If the negative is large, the elongation Negative adjustment; Rule 2: If For a small negative, the elongation Negative small adjustment; Rule 3: If is zero, then the elongation Zero adjustment; Rule 4: If is positive and small, then the elongation is a small positive adjustment; Rule 5: If is positive, then the elongation Adjust for Zhengda; The collected pitch angles are converted into fuzzy values. The minimum value combination rule is used to obtain the activation degree of each rule. The output sets of all rules are aggregated to form a comprehensive fuzzy output, and the fuzzy output is converted into elongation through the centroid method.

4. The pitch mechanism stabilization control method based on dual-cylinder coordinated motion according to claim 3 is characterized in that: The specific logic for obtaining the total elongation is: Preliminary setting of the maximum output value and proportional gain of the PID controller , integral gain , differential gain According to the system response, the parameters are tuned by the Ziegler-Nichols method, and the formula for calculating the control output is: ； in, Indicates the current The control output at the moment, Indicates the current The pitch angle error at the moment, are the proportional, integral and differential gains of the PID controller respectively, is the friction force; The formula based on which the friction force is obtained is: ； in, is the acceleration due to gravity; The formula used to obtain the total elongation is: ； in, For the current The total elongation at time, For the current The elongation at the moment, It is the maximum value of the PID controller output.

5. The pitch mechanism stabilization control method based on dual-cylinder coordinated motion according to claim 4 is characterized in that: The specific logic for establishing the dynamic model of dual-cylinder motion is: The formula for obtaining the linear velocity of the pitch mechanism is: ； in, is the linear velocity of the pitch mechanism, is the acceleration data read from the accelerometer; The dynamic equation is constructed according to Newton's second law, based on the formula: ； in, For the current The pitch angle at the moment, For the current Linear velocity of the pitch mechanism at any moment; Set every 10 For one control cycle, the dynamic equations are solved using numerical methods, the values ​​of the pitch angles at different time points are calculated, the simulated values ​​of the dual-cylinder dynamic model are compared with the actual pitch angle data to verify the accuracy of the dynamic model of the dual-cylinder motion, the inputs of the fuzzy control and PID control are updated, and the fuzzy control and PID controllers are recalculated based on the updated data, and the fuzzy control and PID controllers in steps 2-3 are repeated to predict the fuzzy control output and the output of the PID control at the next moment.

6. The pitch mechanism stabilization control method based on dual-cylinder coordinated motion according to claim 5 is characterized in that: The specific logic for calculating the comprehensive evaluation amount is: Response time is defined as the time from when the system starts responding to when the output reaches The overshoot is defined as the ratio of the maximum amplitude of the system output exceeding the target value to the target value. The formula is: ； in, is the overshoot, The maximum pitch angle reached by the system output; The absolute value of the response time, overshoot and pitch angle error is calculated using Standardization processing, the comprehensive evaluation amount is calculated based on the standardized values, and the formula is: ； in, For comprehensive evaluation, is the absolute value of the pitch angle error, is the response time, is the weight of the absolute value of the pitch angle error, is the weight of response time, is the weight of the overshoot, ,and ; The average value of the comprehensive evaluation quantity under different loads and working conditions is taken as the final comprehensive evaluation quantity, and the final comprehensive evaluation quantity is compared with the preset threshold. If the average value of the comprehensive evaluation quantity is lower than the preset threshold, the current strategy continues to be executed. If the average value of the comprehensive evaluation quantity is higher than the preset threshold, the fuzzy control and PID controller are updated and the control strategy is re-optimized.

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