A rotary aircraft mass lateral eccentric position positioning method based on parameter online identification
By identifying aerodynamic torques using flight test data and combining them with optimization algorithms to solve for eccentricity in real time, the problem of rapid and accurate positioning of lateral mass eccentricity in gyroplanes was solved, achieving high-precision online identification and real-time tracking.
Patent Information
- Application Number
- CN202611148191.5
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2026-07-30
- Publication Date
- 2026-11-06
AI Technical Summary
Existing technologies are insufficient to quickly, accurately, and in real-time identify the lateral eccentricity of the positioning mass during the flight of a rotary aircraft, and cannot effectively cover the effects of structural deformation and shape changes.
Aerodynamic torques are identified using flight test data, a mapping relationship between eccentric position and rolling torque is established, an optimization algorithm is used to solve for the optimal eccentric position in real time, and online identification is performed using feedback data from the aircraft control computer.
It enables rapid and accurate positioning of the lateral eccentricity of the mass, improves positioning accuracy, can track shape changes in real time, and supports aerodynamic analysis and attitude control optimization of the aircraft.
Smart Images
Figure CN123045606A_ABST
Abstract
Description
Technical Field
[0001] This application belongs to the field of aircraft attitude control and online aerodynamic parameter identification technology, specifically relating to a method for locating the lateral eccentricity position of a rotating aircraft based on online parameter identification. Background Technology
[0002] Axisymmetric aircraft typically have their center of mass positioned along the fuselage axis during the design and assembly phases to maintain symmetrical stability in flight attitude. However, due to factors such as uneven mass distribution of components, accumulated assembly tolerances, and mechanical vibrations during transportation and launch, the actual center of mass often deviates from the fuselage axis, resulting in eccentricity in the cross-section. This lateral eccentricity generates additional rolling torque during flight under aerodynamic forces, directly affecting the aircraft's attitude control accuracy and trajectory. Therefore, rapid identification and positioning of the eccentricity position are necessary during flight.
[0003] In existing technologies, the analysis of mass eccentricity location mainly relies on pre-set eccentricity conditions before flight, combined with computational fluid dynamics (CFD) for dynamic simulation, and estimates the possible eccentricity range by comparing the aerodynamic torque response under different eccentricity positions. This type of method establishes an aerodynamic database based on ground tests or numerical simulations, completing the eccentricity impact assessment before flight. Other methods use wind tunnel tests to obtain aerodynamic coefficients, which are then coupled with pre-set eccentricity parameters for semi-empirical estimation.
[0004] The aforementioned CFD simulation or wind tunnel testing methods based on preset operating conditions have inherent limitations. On the one hand, the aircraft shape, incoming flow conditions, and boundary conditions used in the simulation calculations deviate from the actual flight test environment, failing to cover the actual impact of factors such as structural deformation, surface ablation, and asymmetric wear on aerodynamic characteristics during flight, resulting in insufficient eccentricity positioning accuracy. On the other hand, this method is an offline prediction before flight, and the results cannot be corrected online based on measured flight data. Therefore, it cannot provide real-time aerodynamic parameter feedback for the flight control system, and it is also difficult to capture eccentricity position drift caused by mass loss or shape changes during flight.
[0005] Therefore, existing technologies cannot achieve rapid, accurate, and real-time identification and positioning of the lateral eccentricity of mass during the flight of a rotary aircraft. Summary of the Invention
[0006] To address the issues of existing methods for lateral eccentricity positioning of aircraft mass relying on pre-flight simulation prediction, lacking online correction capabilities, and having insufficient positioning accuracy, this paper proposes a method for lateral eccentricity positioning of rotating aircraft mass based on online parameter identification. By identifying aerodynamic torques through flight test data, a mapping relationship between eccentricity position and rolling torque is established, and an optimization algorithm is used to solve for the optimal eccentricity position in real time, achieving rapid and accurate positioning of lateral eccentricity position of mass mass during flight.
[0007] To achieve the above technical objectives, this application specifically employs the following technical solution: In one aspect of this application, a method for locating the lateral eccentricity of a gyroplane based on online parameter identification is provided, comprising the following steps: The flight trajectory parameters and aircraft structural parameters fed back by the aircraft control computer are acquired; the flight trajectory parameters include the time-varying acceleration along the y-axis. acceleration along the z-axis Rotational speed about the x-axis and roll attitude angle The structural parameters of the aircraft include the aircraft mass. and moment of inertia about the x-axis .
[0008] According to the acceleration along the y-axis and aircraft mass Calculate the normal force According to the acceleration along the z-axis and the mass of the aircraft Calculate the lateral force According to the rotational speed about the x-axis and moment of inertia about the x-axis Calculate the actual rolling torque ; Predict the phase angle of the initial mass center eccentricity position. and eccentric distance ; in the At any given moment, the roll attitude angle is used. Normal force and lateral forces Calculate the estimated rolling torque according to the following formula. : ; Constructing the loss function The loss function The actual rolling torque at each moment With the estimated rolling torque Sum of squared residuals: ; Set optimization constraints: the phase angle The range of values is The eccentricity distance The range of values is ,in The radius of the aircraft body; An optimization algorithm is used to find the loss function that satisfies the optimization constraints. The phase angle that reaches the minimum value and the eccentricity distance The optimization result is then used as the optimal position of the lateral eccentricity of the mass at the current moment.
[0009] In one implementation, the normal force Calculate according to the following formula: ; The lateral force Calculate according to the following formula: ; The actual rolling torque Calculate according to the following formula: ; In the formula, For time, Let be the angular acceleration about the X-axis.
[0010] In one implementation, the mass of the aircraft and the moment of inertia about the x-axis Based on the pre-obtained structural design of the aircraft.
[0011] In one implementation, the optimization algorithm is a genetic algorithm.
[0012] In one implementation, the phase angle in the initial samples of the genetic algorithm Values were taken at 30° intervals from 0° to 330°, for a total of 12 sample values; the eccentricity distance From 0 to the radius of the aircraft body The phase angle is taken from a range of values, for a total of 12 sample values; With the aforementioned eccentric distance After combining, the initial total number of samples is 144.
[0013] In one implementation, the eccentricity distance The 12 sample values are arranged at non-equal intervals from 0 to the radius of the aircraft body. Choose from among them.
[0014] In one implementation, the method further includes periodically updating the flight trajectory parameters and repeating each step to obtain the variation law of the lateral eccentricity position of the mass over time; specifically, after 3 seconds of flight, the flight trajectory data used is updated at 1-second time intervals, and each time only the trajectory data within the most recent 3-second time window is extracted and identified.
[0015] In one implementation, when extracting the flight trajectory parameters based on data fed back from the aircraft control computer, the acceleration along the y-axis... The acceleration along the z-axis The rotational speed about the x-axis and the roll attitude angle All values are real-time measurements taken at the time of sampling.
[0016] In one implementation, the actual rolling torque For the first The predicted roll moment is the rolling moment identified from flight test data. For the first The time is based on the estimated phase angle. and the eccentricity distance The calculated rolling torque.
[0017] In one implementation, the output of the optimization algorithm is to make the loss function... The phase angle that reaches the minimum value and the eccentricity distance The phase angle and the eccentricity distance This is the optimal position for the lateral eccentricity of the mass.
[0018] The beneficial effects of this application are as follows: 1) Compared with the prior art, this application uses the aerodynamic parameters identified from flight test data as the reference data. This data has covered the influence of factors such as structural asymmetry, shape deformation and surface ablation on aerodynamic forces. When using this data for analysis, the identification focus is on the aerodynamic effect caused by mass eccentricity, eliminating the interference of aerodynamic shape uncertainty and improving the positioning accuracy of the mass lateral eccentricity position.
[0019] 2) This application establishes the mapping relationship between the forces, roll attitude, lateral eccentricity of mass and roll torque of the aircraft during flight, and uses an optimization algorithm to solve for the lateral eccentricity of mass. Compared with the traditional CFD dynamic simulation analysis method, it avoids the calculation deviation caused by the pre-prediction of the eccentricity position before flight and realizes the rapid identification of the lateral eccentricity of mass during flight.
[0020] 3) This application adopts the minimization of the estimated loss function as the optimization objective, transforms the solution of phase angle and eccentricity distance into a constrained optimization problem, and searches for the optimal solution in the global scope through the optimization algorithm, which avoids excessive dependence on the initial estimated value and improves the reliability and computational efficiency of the identification results.
[0021] 4) This application updates flight trajectory parameters at certain time intervals and extracts and identifies trajectory data in the most recent period. It can track changes in the shape of the aircraft due to external forces / thermal effects, obtain the variation law of the lateral eccentricity position of mass over time, provide a basis for aerodynamic analysis, structural analysis and attitude analysis of the aircraft, and support the control system to carry out real-time optimization of flight parameters.
[0022] 5) This application does not require additional measuring equipment and can complete the online identification of the lateral eccentricity of the mass entirely based on the existing feedback data of the aircraft control computer, which has good engineering applicability and ease of implementation. Attached Figure Description
[0023] Figure 1 This is a schematic flowchart of the method for locating the lateral eccentricity of the mass of a rotary aircraft according to an embodiment of this application; Figure 2 This is a schematic diagram of the coordinate system of the rotary aircraft in an embodiment of this application; Figure 3a This application describes the change of normal force over time during the flight of an aircraft, as identified in an embodiment of the present application. Figure 3b This application describes the change in lateral force over time identified during the flight of an aircraft, as described in an embodiment of the present application. Figure 3c This application describes the change in rolling torque over time as identified during the flight of an aircraft according to an embodiment of the present application. Figure 4 Comparison of rolling moments calculated at different lateral eccentricity positions of the center of mass at the initial moment in the embodiments of this application; Figure 5 The rolling torque is calculated based on the optimal predicted lateral eccentricity position of the center of mass in the embodiments of this application. Detailed Implementation
[0024] The technical solution of this application will be clearly and completely described below with reference to specific embodiments. However, those skilled in the art will understand that the embodiments described below are only some embodiments of this application, not all embodiments, and are only used to illustrate this application, and should not be regarded as limiting the scope of this application. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.
[0025] To overcome the shortcomings of existing technologies in quickly and accurately identifying the lateral eccentricity of mass during the flight of a gyroplane, this application provides a method for locating the lateral eccentricity of mass in a gyroplane based on online parameter identification. This method uses aerodynamic forces and aerodynamic moments obtained from flight test data as baseline data, and combines this with the aircraft's mass parameters to establish a mapping relationship between the forces acting on the aircraft during flight, roll attitude, lateral eccentricity of mass, and roll moment. Furthermore, an optimization algorithm is used to solve for the time-varying lateral eccentricity of mass, thereby achieving rapid identification of the lateral eccentricity of mass in a gyroplane.
[0026] Specifically, this application discloses a method for locating the lateral eccentricity of a gyroplane based on online parameter identification, comprising the following steps: Step 1: Extract the required flight trajectory parameters Based on data fed back from the aircraft control computer, parameters that vary over time are obtained. These time-varying parameters include the aircraft acceleration along the x-axis. Acceleration of the aircraft along the y-axis Acceleration of the aircraft along the z-axis Rotational speed about the x-axis Rotational speed about the y-axis Rotational speed about the z-axis and roll attitude angle .
[0027] Based on the aircraft structural design, obtain the aircraft mass. Moment of inertia along the x-axis Moment of inertia along the y-axis and the moment of inertia along the z-axis .
[0028] Step 2: Calculate the basic aerodynamic parameters Based on the flight trajectory parameters and the aircraft structural parameters, the required aerodynamic parameters are identified and calculated.
[0029] The normal force of the aircraft is: ; The lateral force of the aircraft is: ; The aircraft's rolling moment is: ; In the formula, For time, Let be the angular acceleration about the X-axis of the aircraft.
[0030] Step 3: Establish the mapping relationship between the lateral eccentricity of the aircraft mass and aerodynamic parameters The estimated initial lateral eccentricity of the center of mass is determined by the phase angle. and eccentric distance Two parameters uniquely determine the outcome. Among them, The phase angle of the initial mass center eccentricity position is given. This represents the estimated initial position and distance of the center of mass eccentricity.
[0031] In the At that moment, based on the aircraft normal force calculated in step 2 and the lateral force of the aircraft and the aircraft roll attitude angle extracted in step 1 Combined with the estimated phase angle and eccentric distance Calculate the first Predicted rolling torque at time :
[0032] In the formula, and The phase angle and eccentricity distance are the estimated initial moments of the centroid's eccentric position. For the first The roll attitude angle of the spacecraft at all times, and For the first The normal and lateral forces of the aircraft are constantly tested and identified.
[0033] Step 4: Use an optimization algorithm to calculate the optimal position of the lateral eccentricity of the mass.
[0034] Predicted loss function The actual rolling torque at each moment With the estimated rolling torque Sum of squared residuals:
[0035] In the formula, For the first The actual rolling torque is constantly tested and identified.
[0036] Predicted loss function The magnitude of the deviation reflects the degree of lateral eccentricity between the estimated mass and the actual mass. The smaller the value, the closer the estimated rolling torque is to the actual rolling torque, i.e., the closer the estimated phase angle is to the actual rolling torque. and eccentric distance The closer the mass is to the actual flight conditions, the more lateral the eccentricity position.
[0037] Finding the optimal position for the lateral eccentricity of the mass is transformed into a constrained optimization problem. The optimization objective is to find a set of phase angles. and eccentric distance Make the predicted loss function The minimum value is reached. The optimization constraints are as follows:
[0038] In the formula, The radius of the aircraft body.
[0039] An optimization algorithm is used to find the optimal solution. and .
[0040] Step 5: Update the flight trajectory parameters at regular time intervals.
[0041] During flight, the shape of the aircraft may change due to external forces / heat. The control computer continuously samples and obtains real-time flight trajectory parameters, and can periodically update the currently used flight trajectory parameters and repeat steps 1 to 4 to obtain the real-time changes in the lateral eccentricity of the mass of the rotating aircraft.
[0042] Example This embodiment provides a method for locating the lateral eccentricity of a rotating aircraft based on online parameter identification, such as... Figure 1 As shown, the method includes the following steps: Step 1: Extract the required flight trajectory parameters The aircraft body coordinate system is defined as follows: Figure 2 As shown. During flight, the control computer samples and records flight trajectory data, extracting parameters that change over time: the aircraft's acceleration along the y-axis and z-axis. , Rotational speed about the x-axis and roll attitude angle .
[0043] Step 2: Calculate the basic aerodynamic parameters.
[0044] Based on the flight trajectory parameters extracted in the first step, calculate the aerodynamic parameters.
[0045] The acceleration of the aircraft along the y-axis and z-axis , and quality The calculations show that the aircraft is subjected to normal and lateral forces.
[0046] The normal force of the aircraft is: .
[0047] The lateral force of the aircraft is: .
[0048] The speed of the aircraft's rotation around the X-axis and moment of inertia Calculate the aircraft's rolling torque.
[0049] The aircraft's rolling moment is: ; In the formula, For time, Let be the angular acceleration about the X-axis.
[0050] The changes in normal force, lateral force, and roll moment identified during the flight of a certain aircraft over time are as follows: Figure 3a , 3b As shown in 3c.
[0051] Step 3: Establish the mapping relationship between the lateral eccentricity of the aircraft mass and aerodynamic parameters First, estimate the phase angle of the initial mass center eccentricity position. and eccentric distance Then in the next At that moment, using the roll attitude angle extracted in the first step, and the aircraft's normal force and lateral force identified in the second step, the estimated roll moment of the aircraft at that moment can be calculated:
[0052] In the formula, For the first The roll attitude angle of the spacecraft at all times, and For the first The normal and lateral forces of the aircraft are constantly tested and identified.
[0053] The rolling moment calculated at different estimated lateral eccentric positions of the center of mass at the initial moment is as follows: Figure 4 As shown.
[0054] Step 4: Calculate the optimal position of the lateral eccentricity of the mass using an optimization algorithm. Predicted loss function Actual rolling torque With the estimated rolling torque Sum of squared residuals: .
[0055] As the predicted lateral eccentricity of the center of gravity approaches the actual position during flight, the predicted roll moment gradually converges with the actual roll moment, meaning the value of the predicted loss function continuously decreases. Therefore, to obtain the lateral eccentricity position of the center of gravity that best approximates the actual flight position, an optimization algorithm can be used to find the position that minimizes the predicted loss function. and .
[0056] Optimization iterations are performed using a genetic algorithm. Initial samples are selected first. Phase angle. Values are taken in 30° increments from 0° to 330°, for a total of 12 values; due to the aircraft's fuselage radius of 0.3m, the eccentricity distance... The values range from 0 to 0.3. Specific values are shown in Table 1. After combining the two, the initial sample consists of 144 samples.
[0057] Table 1. Initial sample phase angle and eccentricity distance values
[0058] Genetic algorithms are used to optimize the sample.
[0059] Through iteration, the minimum value of the predicted loss function was finally estimated to be 1.5086. It is 104.3°. It is 0.00366m. The optimal predicted roll moment and the flight-identified roll moment are compared as follows: Figure 5 As shown.
[0060] Step 5: Update the flight trajectory parameters at regular time intervals.
[0061] After 3 seconds of flight, the flight trajectory data is updated at 1-second intervals. Only the trajectory data of the most recent 3 seconds is extracted and identified, fully utilizing the operations from step one to step four to obtain the latest mass lateral eccentricity position.
[0062] The above method was used to identify the variation of the lateral eccentricity of the center of mass of the aircraft over time during flight, providing a basis for the aerodynamic, structural and attitude analysis of the aircraft and helping the control system to carry out real-time optimization of flight parameters.
[0063] Although the embodiments of this application have been described above in conjunction with the accompanying drawings, this application is not limited to the specific embodiments and application fields described above. The specific embodiments described above are merely illustrative and instructive, not restrictive. Those skilled in the art can make many other forms based on the guidance of this specification and without departing from the scope of protection of the claims of this application, and these are all within the scope of protection of this application.
Claims
1. A method for locating the lateral eccentricity position of a gyroplane based on online parameter identification, characterized in that, Includes the following steps: The flight trajectory parameters and aircraft structural parameters fed back by the aircraft control computer are acquired; the flight trajectory parameters include the time-varying acceleration along the y-axis. acceleration along the z-axis Rotational speed about the x-axis and roll attitude angle The structural parameters of the aircraft include the aircraft mass. and moment of inertia about the x-axis . According to the acceleration along the y-axis and aircraft mass Calculate the normal force According to the acceleration along the z-axis and the mass of the aircraft Calculate lateral force According to the rotational speed about the x-axis and moment of inertia about the x-axis Calculate the actual rolling torque ; Predict the phase angle of the initial mass center eccentricity position. and eccentric distance ; in the At any given moment, the roll attitude angle is used. Normal force and lateral forces Calculate the estimated rolling torque according to the following formula. : ； Constructing the loss function The loss function Actual rolling torque at each moment With the estimated rolling torque Sum of squared residuals: ； Set optimization constraints: the phase angle The range of values is The eccentricity distance The range of values is ,in The radius of the aircraft body; An optimization algorithm is used to find the loss function that satisfies the optimization constraints. The phase angle that reaches the minimum value and the eccentricity distance The optimization result is then used as the optimal position of the lateral eccentricity of the mass at the current moment.
2. The method according to claim 1, characterized in that, The normal force Calculate according to the following formula: ； The lateral force Calculate according to the following formula: ； The actual rolling torque Calculate according to the following formula: ； In the formula, For time, Let be the angular acceleration about the X-axis.
3. The method according to claim 1, characterized in that, The mass of the aircraft and the moment of inertia about the x-axis Based on the pre-obtained structural design of the aircraft.
4. The method according to claim 1, characterized in that, The optimization algorithm is a genetic algorithm.
5. The method according to claim 4, characterized in that, In the initial samples of the genetic algorithm, the phase angle Values were taken at 30° intervals from 0° to 330°, for a total of 12 sample values; the eccentricity distance From 0 to the radius of the aircraft body The phase angle is taken from a range of values, for a total of 12 sample values; With the aforementioned eccentric distance After combining, the initial total number of samples is 144.
6. The method according to claim 5, characterized in that, The eccentricity distance The 12 sample values are arranged at non-equal intervals from 0 to the radius of the aircraft body. Choose from among them.
7. The method according to claim 1, characterized in that, The method also includes periodically updating the flight trajectory parameters and repeating each step to obtain the variation law of the lateral eccentricity position of the mass over time; specifically: after 3 seconds of flight, the flight trajectory data used is updated at 1-second time intervals, and each time only the trajectory data within the most recent 3-second time window is extracted and identified.
8. The method according to claim 1, characterized in that, When extracting the flight trajectory parameters based on the data fed back by the aircraft control computer, the acceleration along the y-axis The acceleration along the z-axis The rotational speed about the x-axis and the roll attitude angle All values are real-time measurements taken at the time of sampling.
9. The method according to claim 1, characterized in that, The actual rolling torque For the first The predicted roll moment is the rolling moment identified from flight test data. For the first The time is based on the estimated phase angle. and the eccentricity distance The calculated rolling torque.
10. The method according to claim 1, characterized in that, The output of the optimization algorithm is to make the loss function... The phase angle that reaches the minimum value and the eccentricity distance The phase angle and the eccentricity distance This is the optimal position for the lateral eccentricity of the mass.