Full-motion horizontal tail angle optimization method, system and equipment of helicopter, medium and product

Abstract

The invention discloses an all-moving horizontal tail angle optimization method, system and device of a helicopter, a medium and a product, and relates to the technical field of helicopters.The method comprises the steps that all-moving horizontal tail angle sequences corresponding to different speeds are randomly generated within the all-moving horizontal tail angle constraint range of the helicopter; based on the all-moving horizontal tail angle sequences corresponding to the different speeds, a genetic algorithm and an agent model are adopted for distribution optimization, the optimal all-moving horizontal tail angles corresponding to the different speeds are obtained, and control optimization of the all-moving horizontal tail angles of the helicopter is completed; the proxy model is obtained by performing fitting training on a Kriging model by adopting a kernel function. According to the method, the full-motion horizontal tail angle optimization efficiency of the helicopter can be improved, meanwhile, under the condition that the flight quality is not changed, the propeller hub load is reduced, and the service life of the propeller hub is prolonged.

Description

Technical Field

[0001] This application relates to the field of helicopter technology, and in particular to a method, system, device, medium and product for optimizing the angle of the all-moving horizontal stabilizer of a helicopter. Background Technology

[0002] The unique maneuverability and flexibility of helicopters give them strong ground attack capabilities, high stealth, and rapid response, making them increasingly important in modern warfare. However, during maneuvering missions, the various components of the helicopter rotor system must withstand significant structural loads. High-frequency vibration loads can easily cause fatigue damage to these components, which not only significantly shortens the service life of the rotor system but may also pose a serious threat to the helicopter's flight safety. The dynamic loads borne by the rotor blades are transmitted to the fuselage through the rotor hub, becoming the main source of helicopter vibration and directly affecting the helicopter's flight quality and vibration level.

[0003] In some cases, helicopters primarily achieve vibration and noise reduction through optimized rotor control, including methods such as independent pitch control, higher-order harmonic control, and trailing-edge winglet control. However, these methods place extremely high demands on actuator bandwidth, and the rotor system itself is complex, resulting in significant installation difficulties and limited lifespan for most vibration and noise reduction control actuators. Although many vibration reduction technologies have been validated in the laboratory, most have not yet been widely adopted in actual aircraft models. In recent years, research in areas such as blade airfoil design, flight trajectory control and optimization, and intelligent blades has become increasingly extensive, but research on hub load suppression technology through optimized control strategies at the flight control system level has yet to emerge.

[0004] Currently, flight control systems (FCS) for load mitigation are increasingly being applied to rotorcraft, helicopters, and tiltrotor aircraft, primarily encompassing two typical forms: one actively alters the helicopter's response by controlling rudder deflection; the other alerts the pilot when approaching flight safety boundaries without automatically changing the control system's control structure. The former is known as structural load alleviation (SLA) systems, while the latter is called tactile cueing systems. For helicopters, SLA systems are currently mainly used to reduce pitch control stick loads, rotor hub torque, blade flapping, and main rotor torque.

[0005] To achieve load mitigation using the horizontal stabilizer, it is necessary to combine longitudinal cyclic pitch control with all-moving horizontal stabilizer control. However, this also introduces the problem of multi-control surface control allocation. When a helicopter maneuvers around its longitudinal axis at high speed, incorporating all-moving horizontal stabilizer combined control can significantly reduce rotor longitudinal cyclic pitch, thereby reducing rotor pitch control linkage load and rotor hub bending moment. However, existing SLA systems use a fixed control gear ratio to allocate control between the horizontal stabilizer and longitudinal cyclic pitch, which leads to reduced handling quality and shortened rotor hub life. Summary of the Invention

[0006] The purpose of this application is to provide a method, system, device, medium, and product for optimizing the all-moving horizontal stabilizer angle of a helicopter, which can improve the efficiency of optimizing the all-moving horizontal stabilizer angle of a helicopter, while reducing the rotor hub load and increasing the service life of the rotor hub while ensuring that the flight quality remains unchanged.

[0007] To achieve the above objectives, this application provides the following solution:

[0008] Firstly, this application provides a method for optimizing the angle of the all-moving horizontal stabilizer of a helicopter, including:

[0009] Within the constraint range of the helicopter's all-moving horizontal stabilizer angle, a sequence of all-moving horizontal stabilizer angles corresponding to different speeds is randomly generated;

[0010] Based on the all-moving horizontal stabilizer angle sequence corresponding to different speeds, a genetic algorithm and a surrogate model are used for allocation optimization to obtain the optimal all-moving horizontal stabilizer angle corresponding to different speeds, thus completing the control optimization of the helicopter's all-moving horizontal stabilizer angle; the surrogate model is obtained by fitting and training the Kriging model using a kernel function.

[0011] Secondly, this application provides a helicopter all-moving horizontal stabilizer angle optimization system, including:

[0012] The all-moving horizontal stabilizer angle generation module is used to randomly generate a sequence of all-moving horizontal stabilizer angles corresponding to different speeds within the all-moving horizontal stabilizer angle constraint range of the helicopter.

[0013] The optimization module is used to optimize the allocation of the all-moving horizontal stabilizer angle based on the all-moving horizontal stabilizer angle sequence corresponding to different speeds, using a genetic algorithm and a surrogate model to obtain the optimal all-moving horizontal stabilizer angle corresponding to different speeds, thereby completing the control optimization of the helicopter's all-moving horizontal stabilizer angle; the surrogate model is obtained by fitting and training the Kriging model using a kernel function.

[0014] Thirdly, this application provides a computer device, including: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the above-described method for optimizing the all-moving horizontal stabilizer angle of a helicopter.

[0015] Fourthly, this application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the above-described method for optimizing the angle of the all-moving horizontal stabilizer of a helicopter.

[0016] Fifthly, this application provides a computer program product, including a computer program that, when executed by a processor, implements the steps of the above-described method for optimizing the all-moving horizontal stabilizer angle of a helicopter.

[0017] According to the specific embodiments provided in this application, this application has the following technical effects:

[0018] (1) By using the global search capability of the genetic algorithm, the surrogate model can calculate the sequence of all-moving horizontal tail angles corresponding to different speeds in the global scope, thus achieving global optimization and ensuring the accuracy of the optimal all-moving horizontal tail angles corresponding to different speeds. At the same time, by combining the kernel function in the surrogate model, the computational load is reduced from high latitude to low latitude, thereby reducing the computational load of the surrogate model and improving the computational efficiency of the surrogate model, thereby improving the optimization efficiency of the all-moving horizontal tail angle of the helicopter.

[0019] (2) Compared with the SLA system, by combining the rapid prediction of the surrogate model and the global search of the genetic algorithm, the optimal all-moving horizontal stabilizer angle of the helicopter can be found, so as to reduce the rotor hub load and improve the rotor hub service life while keeping the helicopter flight quality unchanged. Attached Figure Description

[0020] To more clearly illustrate the technical solutions in the embodiments of this application or related technologies, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0021] Figure 1 A flowchart illustrating a method for optimizing the all-moving horizontal stabilizer angle of a helicopter according to an embodiment of this application;

[0022] Figure 2 A schematic diagram of the equivalent flapping bias and flapping constraint stiffness method provided in an embodiment of this application, representing the first-order elastic flapping motion of an equivalent rigid blade.

[0023] Figure 3 A timing diagram of pitching moment under the axis of a symmetrical dive-pull maneuvering body when the forward speed is 55 m / s and the horizontal tail angle changes, provided for an embodiment of this application;

[0024] Figure 4A timing diagram of pitching moment under the axis of a symmetrical dive-pull maneuvering body when the forward speed is 60 m / s and the horizontal tail angle changes, provided for an embodiment of this application.

[0025] Figure 5 A timing diagram of pitching moment under the axis of a symmetrical dive-pull maneuvering body when the forward speed is 70 m / s and the horizontal tail angle changes, provided for an embodiment of this application;

[0026] Figure 6 A timing diagram of pitching moment under the axis of a symmetrical dive-pull maneuvering body when the forward speed is 80 m / s and the horizontal tail angle changes, provided for an embodiment of this application.

[0027] Figure 7 This is a schematic diagram of the structure of an optimized control law system provided in an embodiment of this application;

[0028] Figure 8 This is a schematic diagram illustrating the definition of bandwidth and phase delay according to an embodiment of this application;

[0029] Figure 9 A schematic diagram illustrating the definition of helicopter speed performance indicators provided in an embodiment of this application;

[0030] Figure 10 A schematic diagram of a method for optimizing the all-moving horizontal stabilizer angle of a helicopter according to an embodiment of this application;

[0031] Figure 11 This is a schematic diagram of the structure of a computer device provided in an embodiment of this application. Detailed Implementation

[0032] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0033] In some cases, the horizontal stabilizer angle distribution ratio was not optimized for the helicopter's maneuverability and handling qualities, thus failing to achieve optimal helicopter control.

[0034] Therefore, it is necessary to design a method for optimizing the all-moving horizontal stabilizer angle of a helicopter to achieve optimal control of the horizontal stabilizer angle. While maintaining consistent flight characteristics, this optimization can achieve the best rotor hub load suppression effect and improve rotor hub lifespan.

[0035] To make the above-mentioned objectives, features and advantages of this application more apparent and understandable, the application will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0036] In one exemplary embodiment, such as Figure 1 As shown, a method for optimizing the all-moving horizontal stabilizer angle of a helicopter is provided. This method is executed by a computer device, specifically by a terminal or server alone, or by both a terminal and a server. In this embodiment, the method is described using a server as an example, and includes the following steps S1 to S2. Wherein:

[0037] Step S1: Within the constraint range of the helicopter's all-moving horizontal stabilizer angle, randomly generate a sequence of all-moving horizontal stabilizer angles corresponding to different speeds.

[0038] Step S2: Based on the all-moving horizontal stabilizer angle sequence corresponding to different speeds, a genetic algorithm and a surrogate model are used for allocation optimization to obtain the optimal all-moving horizontal stabilizer angle corresponding to different speeds, thus completing the control optimization of the helicopter's all-moving horizontal stabilizer angle; the surrogate model is obtained by fitting and training the Kriging model using a kernel function.

[0039] Furthermore, the process of constructing the surrogate model specifically includes: constructing a sample dataset of helicopters; the sample dataset includes: sample velocity, sample all-moving horizontal stabilizer angle, sample rotor hub load, and sample handling qualities; using sample velocity and sample all-moving horizontal stabilizer angle as inputs, and sample rotor hub load and sample handling qualities as outputs, the Kriging model is fitted and trained using a kernel function to obtain the surrogate model.

[0040] Specifically, a rapid prediction model for the all-moving horizontal stabilizer angle and target response (rotor hub load and handling qualities) is established based on a sample dataset of helicopters to replace the helicopter's flight dynamics model, improving computational efficiency and enabling rapid iteration of the genetic algorithm. The Matern5 / 2 kernel function is chosen for fitting and training, balancing nonlinear response modeling capability with computational efficiency.

[0041] Furthermore, a sample dataset for the helicopter is constructed, specifically including: constructing a flight dynamics model of the helicopter; randomly generating an initial velocity within the speed constraint range of the helicopter; randomly generating an initial all-moving horizontal stabilizer angle within the all-moving horizontal stabilizer angle constraint range of the helicopter; inputting the initial velocity and initial all-moving horizontal stabilizer angle into the flight dynamics model to obtain the initial rotor hub load and initial handling qualities; and using the Latin hypercube sampling method based on the initial velocity, initial all-moving horizontal stabilizer angle, initial rotor hub load, and initial handling qualities to generate sample velocity, sample all-moving horizontal stabilizer angle, sample rotor hub load, and sample handling qualities.

[0042] Specifically, the process of establishing a flight dynamics model for a helicopter is as follows.

[0043] The helicopter is an all-moving horizontal stabilizer configuration. Establishing a flight dynamics model for the helicopter involves quantifying the relationship between the horizontal stabilizer angle, flight conditions (speed, G-forces, etc.), rotor hub load, and handling qualities. Different flight conditions of the helicopter can be simulated by adjusting the control inputs. The model inputs mainly include: initial speed and initial all-moving horizontal stabilizer angle (e.g., the timing of control inputs for maneuvering actions (such as sharp pull-up, dive-pull-up), and the range of all-moving horizontal stabilizer angle variation). The model outputs mainly include: initial rotor hub load and initial handling qualities. The initial rotor hub load (pitch moment) is a load that changes over time, and handling quality parameters include: bandwidth and phase delay, etc.

[0044] Helicopter flight dynamics models include: rotor equivalent rigid blade dynamics model, airframe aerodynamics model, horizontal and vertical tail aerodynamics model, and tail rotor aerodynamics model.

[0045] First, define the global coordinate system: the ground inertial coordinate system (G), with the unit direction vector as (i G ,j G ,k G The origin of the ground coordinate system is a point on the ground, i. G Let k be the vector along the i-axis in the ground inertial coordinate system, with the i-axis pointing due north. G The vector along the k-axis in the ground inertial coordinate system is positive, pointing vertically towards the Earth's center. G This is a vector along the j-axis in the ground inertial coordinate system, determined by the right-hand rule. The ground coordinate system is primarily used to describe the position of the helicopter's center of mass, its velocity relative to the ground, and its direction of motion.

[0046] The body coordinate system (F) has a unit direction vector of (i). F ,j F ,k F The origin of the body coordinate system is located at the helicopter's center of gravity (CG). F is the vector along the i-axis in the airframe coordinate system, where the i-axis is parallel to the airframe structural baseline and points towards the helicopter's nose. F Let k be the vector along the k-axis in the body coordinate system, where the k-axis is perpendicular to the i-axis and downwards is positive, and i... F -k F The plane is the longitudinal symmetry plane of the body, j F Let be the vector along the j-axis in the body coordinate system, determined by the right-hand rule. The three Euler angles of the body coordinate system relative to the ground coordinate system are: φ represents the roll angle, θ represents the pitch angle, and ψ represents the yaw angle. The transformation matrix from the ground coordinate system to the body coordinate system is T. FG .

[0047]

[0048] Among them, L x (·) is the transformation matrix along the x-axis, L y (·) is the transformation matrix along the y-axis, L z (·) is the transformation matrix along the z-axis.

[0049] The rotor axis is in a fixed coordinate system (S), and the unit direction vector is (i S ,j S ,k S i S Let k be the vector along the i-axis in the fixed coordinate system of the rotor shaft. S Let j be the vector along the k-axis in the fixed coordinate system of the rotor shaft. S This is the vector along the j-axis in the fixed coordinate system of the rotor shaft. The fixed coordinate system of the rotor shaft is actually fixed to the body coordinate system, and the transformation between the two is determined by the lateral tilt angle i of the rotor shaft. φ longitudinal tilt angle i of the rotor shaft θ It is determined that forward tilt is positive. The transformation matrix from the body coordinate system to the rotor axis fixed coordinate system is T. SF .

[0050]

[0051] The rotor hub rotating coordinate system (R) has a unit direction vector (i). R ,j R ,k R i R Let k be the vector along the i-axis in the rotating coordinate system of the propeller hub. R Let j be the vector along the k-axis in the rotating coordinate system of the propeller hub. R Let be the vector along the j-axis in the rotor hub rotating coordinate system. The rotor hub rotating coordinate system is defined the same as in the previous section, and the transformation matrix from the rotor shaft fixed coordinate system to the rotor hub rotating coordinate system is T. RS .

[0052]

[0053] The blade coordinate system (B) is fixed on the rotor blade, and the unit direction vector is (i B ,j B ,k B i B Let k be the vector along the i-axis in the blade coordinate system. B Let j be the vector along the k-axis in the blade coordinate system. B Let be the vector along the j-axis in the blade coordinate system. The origin is located at the flapping hinge. B The shaft is along the blade axis, with the direction pointing towards the blade tip being positive. B axis and jB The axis points perpendicularly to the leading edge of the blade, k B The axis is determined by the right-hand rule. The coordinate transformation matrix from the rotor rotating coordinate system to the blade coordinate system is T. BR .

[0054]

[0055] Wind axis system (W), unit direction vector is (i W ,j W ,k W i W Let k be the vector along the i-axis in the blade coordinate system. W Let j be the vector along the k-axis in the blade coordinate system. W Let be the vector along the j-axis in the rotor blade coordinate system. The origin is located at the helicopter's center of gravity. W The axis is parallel to and opposite to the direction of the incoming flow. W axis and i W The axis is perpendicular to the plane and lies in a plane parallel to the longitudinal plane of symmetry, pointing upwards. W The axis conforms to the right-hand rule. When transforming from the body coordinate system to the wind axis system, first rotate around the body j... W Axis rotation - α F Angle, then rotate β around the z-axis of the aircraft. F Angle. The coordinate transformation matrix from the body coordinate system to the wind axis system is T. WF α F For the angle of attack, β F It is the sideslip angle.

[0056]

[0057] Coordinates within each coordinate system are distinguished by superscripts or subscripts, and transformations between coordinate systems can be performed using matrices.

[0058] The velocity vector V of the aircraft's center of gravity f and angular velocity vector ω f Represented as:

[0059]

[0060] Where u is the x-axis component of the helicopter's center of gravity relative to the air in the body coordinate system; v is the y-axis component of the helicopter's center of gravity relative to the air in the body coordinate system; w is the z-axis component of the helicopter's center of gravity relative to the air in the body coordinate system; p is the roll rate; q is the pitch rate; and r is the yaw rate.

[0061] The relative position vector r between the propeller hub and the fuselage center of gravity H for:

[0062] rH =x H i F +y H j F +z H k F .

[0063] Where, x H The x-axis component represents the relative position of the propeller hub to the fuselage center of gravity in the body coordinate system; the y-axis component represents the position of the propeller hub to the fuselage center of gravity. H The z-axis component represents the relative position of the propeller hub to the fuselage center of gravity in the body coordinate system. H The z-axis component represents the relative position of the propeller hub to the center of gravity of the aircraft in the body coordinate system.

[0064] Then the rotor hub speed V H and acceleration a H They are respectively:

[0065]

[0066] Among them, V f ω is the velocity vector of the aircraft's center of gravity. f The angular velocity vector of the aircraft's center of gravity; r H This is the relative position vector from the propeller hub to the aircraft's center of gravity; For V f The first derivative; For ω f The first derivative; For r H The first derivative; For r H The second derivative of .

[0067] (1) The equivalent rigid blade dynamic model of the rotor adopts the method of equivalent flapping offset and flapping constraint stiffness to represent the first-order elastic flapping motion of the rigid blade. The basic principle is as follows: Figure 2 As shown.

[0068] In the diagram, w h This represents the flapping deflection. The position of the equivalent flapping hinge is determined by the intersection of the tip tangent of the first-order elastic flapping mode of the blade and the x-axis. L e This is the equivalent waving bias. Additionally, to ensure consistent equivalent waving frequencies, an equivalent waving constraint torsion spring is added to the equivalent model.

[0069] Position vector from any point P on the blade to the center of the blade hub in the blade coordinate system for:

[0070]

[0071] The position vector from any point on the blade to the center of the hub in the rotor axis coordinate system for:

[0072]

[0073] Among them, T SR T is the transformation matrix from the rotor hub rotating coordinate system to the rotor shaft fixed coordinate system; RB This is the transformation matrix from the blade coordinate system to the hub rotating coordinate system.

[0074] The velocity V at any point on the blade in the rotor axis coordinate system P for:

[0075]

[0076] Among them, V S Let ω be the velocity at the center of the rotor hub in the rotor axis coordinate system; S The angular velocity at the center of the rotor hub in the rotor axis coordinate system; Let be the position vector from any point on the blade to the center of the rotor hub in the rotor axis coordinate system; V is the partial derivative operator; t is time; V H The speed of the rotor hub; u S v represents the x-component of the velocity at the rotor hub center in the rotor axis coordinate system. S The component of the velocity at the rotor hub center along the y-axis in the rotor axis coordinate system; w S Let ω be the z-axis component of the velocity at the rotor hub center in the rotor axis coordinate system; f p is the angular velocity vector of the aircraft's center of gravity; S q represents the roll angular velocity at the center of the rotor hub in the rotor axis coordinate system. S r is the pitch angular velocity at the center of the rotor hub in the rotor axis coordinate system. S Let yaw rate be the yaw rate at the center of the rotor hub in the rotor axis coordinate system.

[0077] The velocity of any point on the blade in the blade coordinate system for:

[0078]

[0079] Among them, T BR T is the transformation matrix from the rotor hub coordinate system to the blade coordinate system; RS This is the transformation matrix from the fixed coordinate system of the rotor shaft to the rotating coordinate system of the rotor hub.

[0080] Differentiating the velocity, we obtain the acceleration of any point on the blade in the blade coordinate system as follows:

[0081]

[0082] Among them, the acceleration a in the fixed coordinate system of the rotor axisS =T SF a H a S Let a be the acceleration in a fixed coordinate system along the rotor axis. H For rotor hub acceleration, ω S The angular velocity in the fixed coordinate system of the rotor shaft, For ω S The first derivative.

[0083] From the acceleration of the blade, the inertial force dF and inertial torque dM per unit length of blade are respectively:

[0084]

[0085] dM=r×dF.

[0086] Where, ρ b This represents the blade linear density.

[0087] Integrating the above equation yields the inertial torque M acting on the swinging hinge. βI for:

[0088]

[0089] in, Let ρ be the acceleration of the blade element in the Z-direction in the reference blade coordinate system. b Let be the blade linear density. Establishing the blade flapping motion equations in the blade coordinate system, the torque balance generated by the aerodynamic torque, inertial torque, and flapping constraint spring torque at the flapping hinge reveals the following:

[0090] M βI +M βA +M βK =0.

[0091] Among them, M βA To generate aerodynamic torque, M βK The equivalent constraint spring torque at the propeller root.

[0092]

[0093] in, For the angular acceleration of the swing, Let be the roll acceleration in the rotor axis coordinate system. For the pitch acceleration in the rotor axis coordinate system, Let x be the x-component of the acceleration at the hub center in the rotor axis coordinate system. Let be the y-component of the acceleration at the hub center in the rotor axis coordinate system. M represents the z-axis component of the acceleration at the hub center in the rotor axis coordinate system. βAFor the flapping aerodynamic torque, Ω is the rotor speed, and I is the rotor speed. b M is the moment of inertia of a single rotor blade relative to the flapping hinge. b Let β0 be the static moment of mass of a single rotor blade relative to the flapping hinge, and k be the pre-cone angle. β For equivalent swing stiffness.

[0094] The effects of body angular acceleration and linear acceleration on the waving motion can usually be ignored, so the equation of the waving motion is:

[0095]

[0096] Among them, I b M is the moment of inertia of a single rotor blade relative to the flapping hinge. b β0 is the static moment of mass of a single rotor blade relative to the flapping hinge, and β0 is the pre-cone angle.

[0097] Based on the rotor flapping dynamics modeling method, the single-blade hub torque M... H It can be determined by the equivalent swing hinge bias K β The approximate solution for the blade flapping angle β is as follows:

[0098]

[0099] (2) Aerodynamic model of the fuselage

[0100] The key to calculating the fuselage aerodynamics based on wind tunnel measurements is determining the airflow velocity at the fuselage aerodynamic reference point. The airflow velocity U at the fuselage aerodynamic reference point is... F Subject to atmospheric speed U, helicopter flight speed V, and body angular velocity ω f and rotor wake induced velocity v i (ρ F The effect of ) can be expressed as:

[0101] U F =[U Fx U Fy U Fz e f =UV f -ω f ×ρ F +v i (ρ F ).

[0102] Among them, U Fx U is the airflow velocity along the x-axis at the fuselage aerodynamic reference point. Fy U is the airflow velocity along the y-axis at the fuselage aerodynamic reference point. Fz e represents the airflow velocity along the z-axis at the fuselage aerodynamic reference point. f Let U be the vector basis of the body coordinate system, where U is the atmospheric velocity and V is the velocity.f Let ω be the velocity vector of the aircraft's center of gravity. f ρ is the angular velocity vector of the aircraft's center of gravity. F This is the position vector of the fuselage aerodynamic reference point relative to the helicopter's center of gravity.

[0103] After determining the airflow velocity at the fuselage aerodynamic reference point, the fuselage angle of attack α F and sideslip angle β F It can be represented as:

[0104]

[0105] After determining the fuselage angle of attack and sideslip angle, six aerodynamic load coefficients for the fuselage are obtained through numerical interpolation. These coefficients are all functions of the fuselage angle of attack and sideslip angle. They represent the fuselage lift coefficient C. LF (α F ,β F Drag coefficient C DF (α F ,β F Lateral force coefficient C YF (α F ,β F Rolling moment coefficient C RF (α F ,β F Pitch moment coefficient C MF (α F ,β F ) and yaw moment coefficient C NF (α F ,β F In the body coordinate system, the force F exerted by the fuselage aerodynamic load on the helicopter's center of gravity is... F and torque M F It can be represented as:

[0106]

[0107] in, For the incoming flow pressure, For the fuselage aerodynamic vector, l F A is the characteristic length of the fuselage. F For fuselage area, X is the transformation matrix from the fuselage airflow coordinate system to the fuselage coordinate system. F The force F exerted by the aerodynamic loads of the fuselage on the center of gravity of the helicopter. F The components on the X-axis, Y F The force F exerted by the aerodynamic loads of the fuselage on the center of gravity of the helicopter. F The component on the Y-axis, Z F The force F exerted by the aerodynamic loads of the fuselage on the center of gravity of the helicopter. FThe component on the Z-axis, M X,F The moment M is the force exerted by the aerodynamic loads of the fuselage on the center of gravity of the helicopter. F On the X-axis, M Y,F The moment M is the force exerted by the aerodynamic loads of the fuselage on the center of gravity of the helicopter. F On the Y-axis, M Z,F The moment M is the force exerted by the aerodynamic loads of the fuselage on the center of gravity of the helicopter. F On the Z-axis.

[0108] (3) Aerodynamic model of horizontal and vertical tail

[0109] The calculation of aerodynamic forces for the horizontal and vertical stabilizers is basically the same as that for the fuselage. First, determine the incoming flow velocity U at the horizontal stabilizer aerodynamic reference point. H The incoming flow velocity U at the vertical tail aerodynamic reference point V , respectively represented as:

[0110]

[0111] Among them, U Hx U is the inflow velocity along the x-axis of the horizontal stabilizer aerodynamic reference point. Hy U is the inflow velocity along the y-axis of the horizontal stabilizer aerodynamic reference point. Hz The incoming flow velocity along the z-axis of the horizontal stabilizer aerodynamic reference point is ω. f U is the angular velocity vector of the aircraft's center of gravity. Vx U is the inflow velocity along the x-axis of the vertical tail aerodynamic reference point. Vy U is the inflow velocity along the y-axis of the vertical tail aerodynamic reference point. Vz Let ρ be the incoming flow velocity along the z-axis of the vertical tail aerodynamic reference point. S Let ρ be the position vector of the horizontal stabilizer aerodynamic reference point relative to the helicopter's center of gravity. V K is the position vector of the vertical tail aerodynamic reference point relative to the helicopter's center of gravity. H K is the dynamic pressure loss coefficient at the tail section. V These are the dynamic pressure loss coefficients at the vertical tail, which are related to the helicopter configuration. i (ρ S The velocity induced by the rotor wake on the vertical stabilizer is v. The longitudinal motion characteristics of a helicopter are highly sensitive to the aerodynamic forces of the horizontal stabilizer; under certain flight conditions, the wake interference velocity v... i (ρ S It has a significant impact on the aerodynamic force of the horizontal tail.

[0112] After determining the airflow velocity at the reference point, the angles of attack and sideslip angles of the horizontal and vertical stabilizers are expressed as follows:

[0113]

[0114] Where, α H For the horizontal stabilizer angle of attack, β HFor the horizontal tail sideslip angle, α V For the vertical tail angle of attack, β V This refers to the sideslip angle of the vertical tail.

[0115] The incoming flow pressures can be expressed as:

[0116]

[0117] Where, q H For the flat-tailed flow pressure, q V The pressure is from the vertical tail.

[0118] Similar to the fuselage, after determining the angles of attack and sideslip angles of the horizontal and vertical stabilizers, the lift coefficient C of the horizontal stabilizer is obtained through numerical interpolation. LH (α H ,β H and drag coefficient C DH (α H ,β H ), vertical tail lift coefficient C LV (α V ,β V and drag coefficient C DV (α V ,β V In the airframe coordinate system, the forces and moments exerted by the aerodynamic loads of the horizontal and vertical stabilizers on the helicopter's center of gravity can be expressed as:

[0119]

[0120] M V =[M X,V M Y,V M Z,V ] T =ρ V ×F V .

[0121] Among them, F H For horizontal tail aerodynamic vectoring, F V M is the aerodynamic vector of the vertical tail. H M is the aerodynamic torque vector of the horizontal tail. V A is the aerodynamic moment vector of the vertical tail. H Let A be the area of ​​the flat tail. V Let be the area of ​​the vertical tail. This is the transformation matrix from the horizontal tail airflow coordinate system to the body coordinate system. F is the transformation matrix from the vertical tail airflow coordinate system to the body coordinate system. H X is the force exerted by the horizontal stabilizer aerodynamic load on the helicopter's center of gravity. H The component of the force exerted by the horizontal stabilizer aerodynamic load on the helicopter's center of gravity along the X-axis, Y HZ represents the component of the force exerted by the horizontal stabilizer aerodynamic load on the helicopter's center of gravity along the Y-axis. H q represents the Z-axis component of the force exerted by the horizontal stabilizer aerodynamic load on the helicopter's center of gravity. H For the flat-tailed flow pressure, M X,H M represents the component of the torque on the helicopter's center of gravity caused by the horizontal stabilizer aerodynamic load along the X-axis. Y,H M represents the component of the torque on the helicopter's center of gravity caused by the horizontal stabilizer aerodynamic load along the Y-axis. Z,H ρ represents the component of the moment along the Z-axis of the aerodynamic load of the horizontal stabilizer acting on the helicopter's center of gravity. S F is the position vector of the horizontal stabilizer aerodynamic reference point relative to the helicopter's center of gravity. H X is the force vector of the horizontal stabilizer aerodynamic load acting on the helicopter's center of gravity. V The component of the force exerted by the vertical tail aerodynamic load on the helicopter's center of gravity along the X-axis, Y V Z represents the component of the force exerted by the vertical tail aerodynamic load on the helicopter's center of gravity along the Y-axis. V M represents the Z-axis component of the force exerted by the vertical tail aerodynamic load on the helicopter's center of gravity. X,V M represents the component of the torque on the helicopter's center of gravity caused by the aerodynamic load of the vertical tail. Y,V M represents the component of the torque on the helicopter's center of gravity caused by the aerodynamic load of the vertical tail acting on it along the Y-axis. Z,V ρ represents the component of the moment along the Z-axis of the aerodynamic load of the vertical tail acting on the helicopter's center of gravity. V F is the position vector of the vertical tail aerodynamic reference point relative to the helicopter's center of gravity. V This is the force vector of the vertical tail aerodynamic load acting on the helicopter's center of gravity.

[0122]

[0123] (4) Tail rotor aerodynamic model

[0124] In the aerodynamic calculation of the tail rotor, it is assumed that the induced velocity of the tail rotor itself is uniformly distributed but unsteady; the aerodynamic force of the tail rotor blade profile is calculated using a linear quasi-steady aerodynamic model; the blocking effect of the vertical tail on the tail rotor is considered through empirical coefficients; the hub torque, backlash force and lateral force of the tail rotor are ignored.

[0125] Taking into account the interference velocity of the rotor wake at the tail rotor, the incoming flow velocity at the center of the tail rotor hub can be expressed as: U TR =[U TRx U TRy U TRz e f =κ TR (UV f )-ω f ×ρ TR +v TRi +vi (ρ TR ).

[0126] Among them, U TRx U is the inflow velocity along the x-axis at the center of the tail rotor hub. TRy U is the incoming flow velocity along the y-axis at the center of the tail rotor hub. TRz Let κ be the incoming flow velocity along the z-axis at the center of the tail rotor hub. TR ρ is the dynamic pressure loss coefficient. TR Let v be the position vector of the tail rotor hub center relative to the helicopter's center of gravity. TRi v is the tail rotor induced velocity. i (ρ TR The induced velocity is the tail rotor wake. For some helicopters, the tail rotor hub is not within the helicopter's longitudinal plane of symmetry. For example, the tail rotor of the UH-60A helicopter is deflected to the left by an angle Λ, where Λ is the tilt angle of the tail rotor shaft relative to the fuselage's vertical axis. The tail rotor inflow velocity needs to be converted to the tail rotor coordinate system.

[0127]

[0128] Among them, U TR Let be the incoming flow velocity at the center of the tail rotor hub in the tail rotor coordinate system. Let x be the incoming flow velocity along the x-axis at the center of the tail rotor hub in the tail rotor coordinate system. Let be the incoming flow velocity along the y-axis at the center of the tail rotor hub in the tail rotor coordinate system. The incoming flow velocity is the z-axis velocity of the tail rotor hub center in the tail rotor coordinate system. The transformation matrix from the body coordinate system to the tail rotor coordinate system can be expressed as:

[0129]

[0130] Tail rotor advance ratio μ TR and inflow ratio λ TR The expressions are as follows:

[0131]

[0132] Among them, R TR Ω is the tail rotor radius. TR This refers to the tail rotor speed. According to rotor blade element theory, the tail rotor's cone angle β... 0TR Tensile coefficient C TTR and torque coefficient C QTR The expressions are as follows:

[0133]

[0134] Where, θ TR For the tail rotor collective pitch, σ TR For tail rotor solidity, γ TRThe tail rotor blade loc number, a ∞ Let C be the slope of the airfoil's lift line. x The airfoil's drag coefficient is... Dimensionless uniform induced velocity, Υ is the tip loss coefficient, K TR Δ is the blocking factor of the vertical tail to the tail rotor, which is related to the helicopter configuration. Δ is the sign factor, which is related to the tail rotor's direction of rotation. Δ = 1 corresponds to bottom forward and Δ = -1 corresponds to bottom backward.

[0135] The tail rotor force vector F acting on the helicopter's center of gravity TR The torque M of the force acting on the tail rotor TR It can be represented as:

[0136]

[0137]

[0138] Among them, X TR Let Y be the component of the tail rotor force acting on the helicopter's center of gravity along the X-axis. TR Z represents the component of the tail rotor force acting on the helicopter's center of gravity along the Y-axis. TR This represents the Z-axis component of the tail rotor force acting on the helicopter's center of gravity. C is the transformation matrix from the tail rotor coordinate system to the body coordinate system. TTR M is the tail rotor thrust coefficient. X,TR M represents the torque component of the tail rotor force on the X-axis. Y,TR M is the component of the torque of the tail rotor force on the T-axis. Z,TR C represents the Z-axis component of the torque exerted by the tail rotor force. QTR This is the tail rotor torque coefficient.

[0139] (5) Dynamics model of helicopter engine / transmission system

[0140] In the rotor rotational degrees of freedom, the main focus is on the balance between the inertial torque generated by the rotor system's rotational inertia, the aerodynamic reaction torque acting on the rotor, and the engine's driving torque. Therefore, the rotor speed dynamics equation is:

[0141]

[0142] Among them, J MR It includes the equivalent rotational inertia of the rotor and transmission system. M is the rotor angular acceleration. A For rotor counter-torque, M E The engine output torque is determined by the engine output power / speed.

[0143] Assuming the entire transmission system is rigid, based on the torque balance condition of the transmission system, the equation of motion for the rotor speed degree of freedom is:

[0144]

[0145] Among them, J tot The moment of inertia of the entire transmission system. Q is the angular acceleration of the reducer. eng Q represents engine torque. acc Q represents the torque of systems other than the rotor and tail rotor. gbx Q is the torque of the reducer. MR Q is the rotor torque. TR For tail rotor torque, G TR P is the tail rotor speed ratio. acc For the power required by other components, Q is the damping coefficient of the reducer. pt For engine output torque, G eng N is the reduction ratio of the engine relative to the rotor. eng J represents the number of engines. TR J is the moment of inertia of the tail rotor. hs J represents the moment of inertia of the rotor hub and rotor shaft. eng J is the engine's moment of inertia. gbx This is the rotational inertia of the reducer.

[0146] Specifically, to obtain training data covering the entire flight envelope of the helicopter to construct a surrogate model, the input variables are defined as: sample velocity and sample all-moving horizontal stabilizer angle. The output response is defined as: sample rotor hub load and sample handling qualities. The Latin Hypercube Sampling (LHS) method is used to generate initial sample points to ensure uniform coverage of the design space. The output response corresponding to each sample point is calculated using the established high-fidelity flight dynamics model to generate a sample dataset for the helicopter.

[0147] In one specific embodiment, the rotor load of a typical maneuver, symmetrical dive-pull-up, is analyzed, mainly considering medium- and high-speed forward flight states, such as... Figures 3-6 As shown.

[0148] Furthermore, step S2 specifically includes steps S21-S26. Wherein:

[0149] Step S21: Use real number encoding to encode the all-moving horizontal tail angle sequences corresponding to different velocities to generate multiple encoded individuals; one encoded individual corresponds to one all-moving horizontal tail angle sequence; multiple encoded individuals form the initial population.

[0150] Specifically, since genetic algorithms cannot directly process parameters in the problem space, they must encode the problem to be solved as chromosomes or individuals in the genetic space. In other words, the encoding process maps phenotypes (i.e., the fully moving flat-tail angle sequence) to genotypes. Encoding method: Real-number encoding is used, with each individual represented as a vector, indicating the fully moving flat-tail angle sequence at different velocities.

[0151] Step S22: Input all coded individuals into the surrogate model to obtain the hub load and maneuvering quality corresponding to each all-moving horizontal stabilizer angle in each coded individual.

[0152] Step S23: Based on the hub load and maneuvering qualities, calculate the fitness function value of all all-moving horizontal stabilizer angles in each coded individual using the fitness function.

[0153] Furthermore, the expression for the fitness function is:

[0154] F(θ)=ω1·L(θ)+ω2·Q(θ).

[0155] Where F(·) is the fitness function; θ is the all-moving horizontal stabilizer angle; ω1 and ω2 are both weighting coefficients; L(·) is the hub load; and Q(·) is the handling quality.

[0156] Step S24: Select the fully dynamic flat tail angles of each coded individual whose fitness function value is greater than the preset fitness function value, and obtain the selected coded individuals to generate the first population.

[0157] Step S25: Perform crossover and mutation on the coded individuals in the first population to obtain the second population.

[0158] Further, step S25 specifically includes: using a simulated binary crossover method to crossover the coded individuals in the first population to obtain crossover coded individuals; and using a Gaussian mutation method to mutate the crossover coded individuals to obtain the second population.

[0159] Specifically, the Simulated Binary Crossover (SBX) method is employed. This crossover operator, specifically designed for real-number encoding, simulates the distribution characteristics of binary crossover and is suitable for continuous space search. This applies to the parent individuals (i.e., the encoded individuals in the first group). and Generate offspring:

[0160]

[0161] in, Let be the angle of the i-th fully moving horizontal tail in the offspring, and β be a random factor. Let be the angle of the i-th fully moving horizontal tail in parent generation P1. Let β be the i-th all-moving horizontal tail angle in the parent generation P2. β is controlled by the distribution function, and the distribution index η determines the similarity between the offspring and the parent generation (the larger η is, the closer the offspring is to the parent generation).

[0162] Specifically, the Gaussian mutation method is used to add Gaussian distributed random perturbations to the gene values:

[0163]

[0164] in, For the mutated gene, θ i For individual genes (all-dynamic flat tail angle), N(·) is the distribution type identifier, representing Gaussian distribution (normal distribution), and σ is the variable asynchrony length (e.g., initial σ = 2, decaying with iteration).

[0165] Step S26: Determine whether the maximum number of iterations has been reached; if yes, then select the optimal all-moving flat-tail angle for each coded individual in the second population; the optimal all-moving flat-tail angle is the all-moving flat-tail angle with the highest fitness function value; if no, then perform screening, crossover and mutation on the coded individuals in the second population again.

[0166] In an exemplary embodiment, after optimizing the control of the helicopter's all-moving horizontal stabilizer angle, the optimal all-moving horizontal stabilizer angles corresponding to different speeds are stored. These optimal angles are then used as a static allocation strategy for the all-moving horizontal stabilizer angle. This optimized allocation strategy is embedded into the helicopter's flight control system with the all-moving horizontal stabilizer configuration. It can be triggered according to preset conditions (such as flight speed, overload coefficient, attitude angle, etc.), thus obtaining a control-optimized rotor hub load suppression control law. Figure 7 As shown, based on the lateral and longitudinal control structures and BIAS compensation mechanism of the "Black Hawk" helicopter, the flight speed, pitch attitude angle, and overload coefficient are incorporated as feedback quantities into the original all-moving horizontal stabilizer control law. To improve the longitudinal response quality of the helicopter, a pitch angular velocity signal is introduced to increase angular velocity damping. A lateral acceleration signal is also introduced to compensate for the movement of the pitch channel caused by sideslip. The horizontal stabilizer and collective pitch are linked to reduce the pitch motion caused by collective pitch and improve the trim attitude of the helicopter.

[0167] Based on the above optimized rotor hub load suppression control law, flight performance maintenance analysis and speed index analysis are performed.

[0168] Flight performance maintenance analysis: First, the bandwidth and time delay of each channel in the typical forward flight state of the helicopter under the original control mode are calculated and analyzed, as well as the speed index in the maneuvering flight state, and evaluated according to the national military standard "Military Helicopter Flight Quality Specification".

[0169] Among them, bandwidth and phase delay analysis: The national military standard "Flight Quality Specifications for Military Helicopters" uses frequency domain requirements to measure the control response for small / medium-high frequencies, namely bandwidth (ω). BW ) and phase delay (τ) p As for bandwidth and phase delay, they can be determined from the Bode plot corresponding to the transfer function.

[0170] Figure 8 A method for determining bandwidth and phase delay based on Bode plots is presented. A 180° phase delay in attitude response to control input is considered the boundary where pilot-induced oscillations (PIOs) may occur. To avoid PIOs, a 45° safety margin is provided on the phase-frequency curve, defining the frequency with a 135° delay as the phase bandwidth. However, this only guarantees the absence of PIOs and does not guarantee sufficient response amplitude. To meet the requirements of both preventing PIOs and having sufficient response amplitude, the Chinese military standard "Military Helicopter Flight Quality Specifications" provides a 6dB margin on the amplitude-frequency curve and defines the frequency corresponding to this point as the gain bandwidth. The smaller of the phase bandwidth and the gain bandwidth is taken as the helicopter's bandwidth.

[0171] The phase delay characteristics of helicopter control response are directly related not only to bandwidth but also to the slope of the phase frequency curve. This slope depends on the helicopter's dynamic characteristics, the characteristics and defects of the control system (such as backlash, action delay, etc.). Pilots are very sensitive to the slope of the phase frequency curve; an excessively large slope makes it impossible to accurately judge the required control lead. To comprehensively consider both factors, the Chinese military standard "Military Helicopter Flight Quality Specifications" uses delay time to characterize the helicopter's phase delay, namely:

[0172]

[0173] Where, τ p For the phase delay of the helicopter, 2 times ω 180 The corresponding phase and ω 180 The corresponding phase difference ω 180 This is the frequency with a phase delay of 180°.

[0174] The bandwidth and phase delay of the helicopter at various forward speeds under different control conditions can be obtained from the phase frequency curve, and based on... Figure 8 Flight quality was evaluated for bandwidth and phase delay at each forward speed. Tables 1 and 2 show that the bandwidth and phase delay index levels remain unchanged under different control inputs, original control mode, and optimized control law mode.

[0175] Table 1 Flight Quality Levels of the Original Flight Control Mode

[0176]

[0177]

[0178] Table 2 Flight Quality Levels of Optimized Control Law Modes

[0179]

[0180] Quickness Index Analysis: For mid-amplitude / low-mid-frequency control response, the Chinese military standard "Military Helicopter Flight Quality Specifications" uses quickness as a metric. Quickness is defined as the peak angular velocity q. pk With the maximum attitude change Δθ pk The ratio of q pk / Δθ pk It reflects the helicopter's ability to change from one flight state to another, and is used to characterize the short duration of helicopter maneuvers, or the effectiveness of maneuvering to produce a maneuver response.

[0181] Figure 9 The diagram illustrates the meaning of the relevant parameters, and the figure represents the response when pulse control is applied. Since quickness emphasizes the transient nature of helicopter control response, when evaluating helicopter controllability using quickness, not only q should be considered. pk / Δθ pk The magnitude of q also needs to consider the attitude changes in the manipulation response. If for the same size q... pk / Δθ pk The degree of attitude angle oscillation varies during a helicopter's transition from one flight state to another, reflecting different levels of agility. The Chinese military standard "Military Helicopter Flight Quality Specifications" uses the minimum attitude change in control response (Δφ) as the standard. min This difference is reflected in the minimum attitude change. Different minimum attitude changes correspond to different speed.

[0182] In the symmetrical dive-pull maneuver, the pitch attitude indexes under both modes with and without the optimized control law can be obtained from the changes in the three-axis attitude angles and the three-axis angular velocities of the body axis at each forward speed. The flight quality is then evaluated for the pitch attitude quickness at each forward speed. As shown in Tables 3 and 4, the pitch attitude quickness index levels remain unchanged under both modes with and without the optimized control law when performing symmetrical dive-pull maneuvers at different forward speeds.

[0183] Table 3. Pitch Attitude Quickness in Original Flight Control Mode

[0184]

[0185]

[0186] Table 4. Optimized Control Law Mode Pitch Attitude Quickness

[0187] Speed ​​(m / s) <![CDATA[q pk ]]> <![CDATA[Δθ pk ]]> <![CDATA[Δφ min ]]> <![CDATA[q pk / Dth pk ]]> grade 40 24.2 35.4 2.6 0.684 2 60 19.3 31.1 6.1 0.621 2 70 18.2 29.2 9.3 0.623 2 75 17.6 28.8 10.1 0.611 2 80 17.1 27.6 11.2 0.620 2

[0188] The beneficial effects of the helicopter all-moving horizontal stabilizer angle optimization method proposed in this application are mainly reflected in:

[0189] This application proposes a method combining genetic algorithms and surrogate models to quickly and accurately optimize the all-moving horizontal stabilizer angle for helicopters at different speeds. The global search capability of the genetic algorithm ensures that the surrogate model calculates the all-moving horizontal stabilizer angle sequence for different speeds, achieving global optimization at different speeds and guaranteeing the accuracy of the optimal all-moving horizontal stabilizer angle for each speed. Furthermore, the kernel function of the surrogate model effectively reduces the dimensionality of computation, improving the optimization efficiency of the helicopter's all-moving horizontal stabilizer angle. This enables control of helicopter flight at the optimal all-moving horizontal stabilizer angle, thereby reducing rotor hub load and extending rotor hub lifespan while maintaining consistent flight performance.

[0190] Based on the same inventive concept, this application also provides a system for optimizing the angle of a helicopter's all-moving horizontal stabilizer. The solution provided by this system is similar to the solution described in the above method. Therefore, the specific limitations of one or more embodiments of the helicopter's all-moving horizontal stabilizer angle optimization system provided below can be found in the limitations of the helicopter's all-moving horizontal stabilizer angle optimization method described above, and will not be repeated here.

[0191] In one exemplary embodiment, such as Figure 10 As shown, a helicopter all-moving horizontal stabilizer angle optimization system is provided, comprising:

[0192] The all-moving horizontal stabilizer angle generation module is used to randomly generate a sequence of all-moving horizontal stabilizer angles corresponding to different speeds within the constraint range of the all-moving horizontal stabilizer angle of the helicopter.

[0193] The optimization module is used to optimize the allocation of all-moving horizontal stabilizer angles based on the all-moving horizontal stabilizer angle sequences corresponding to different speeds, using a genetic algorithm and a surrogate model to obtain the optimal all-moving horizontal stabilizer angles for different speeds, thus completing the control optimization of the helicopter's all-moving horizontal stabilizer angles. The surrogate model is obtained by fitting and training the Kriging model using a kernel function.

[0194] In one exemplary embodiment, a computer device is provided, which may be a server or a terminal, and its internal structure diagram may be as follows. Figure 11As shown, the computer device includes a processor, memory, input / output (I / O) interfaces, and a communication interface. The processor, memory, and I / O interfaces are connected via a system bus, and the communication interface is also connected to the system bus via the I / O interfaces. The processor provides computational and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and a database. The internal memory provides the environment for the operating system and computer programs in the non-volatile storage media to run. The database stores the all-moving horizontal stabilizer angle sequences corresponding to different speeds. The I / O interfaces are used for information exchange between the processor and external devices. The communication interface is used for communication with external terminals via a network connection. When the computer program is executed by the processor, it implements an all-moving horizontal stabilizer angle optimization method for helicopters.

[0195] Those skilled in the art will understand that Figure 11 The structures shown are merely block diagrams of some structures related to the present application and do not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than shown in the figures, or combine certain components, or have different component arrangements. In an exemplary embodiment, a computer device is provided, including a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the steps in the above-described method embodiments.

[0196] In one exemplary embodiment, a computer-readable storage medium is provided storing a computer program that, when executed by a processor, implements the steps in the above-described method embodiments.

[0197] In one exemplary embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the steps in the above-described method embodiments.

[0198] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of the relevant data must comply with relevant regulations.

[0199] 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. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM).

[0200] The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

[0201] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0202] This document uses specific examples to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the methods and core ideas of this application. Furthermore, those skilled in the art will recognize that, based on the ideas of this application, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A method for optimizing the angle of the all-moving horizontal stabilizer of a helicopter, characterized in that, The method for optimizing the all-moving horizontal stabilizer angle of the helicopter includes: Within the constraint range of the helicopter's all-moving horizontal stabilizer angle, a sequence of all-moving horizontal stabilizer angles corresponding to different speeds is randomly generated; Based on the all-moving horizontal stabilizer angle sequence corresponding to different speeds, a genetic algorithm and a surrogate model are used for allocation optimization to obtain the optimal all-moving horizontal stabilizer angle corresponding to different speeds, thus completing the control optimization of the helicopter's all-moving horizontal stabilizer angle; the surrogate model is obtained by fitting and training the Kriging model using a kernel function.

2. The method for optimizing the angle of the all-moving horizontal stabilizer of a helicopter according to claim 1, characterized in that, The process of constructing the proxy model specifically includes: Construct a sample dataset for helicopters; the sample dataset includes: sample velocity, sample all-moving horizontal stabilizer angle, sample rotor hub load, and sample handling qualities; Using the sample velocity and the sample all-moving horizontal stabilizer angle as inputs, and the sample rotor hub load and the sample maneuvering quality as outputs, the Kriging model is fitted and trained using a kernel function to obtain a surrogate model.

3. The method for optimizing the angle of the all-moving horizontal stabilizer of a helicopter according to claim 2, characterized in that, Constructing a sample dataset of helicopters, specifically including: Construct a flight dynamics model for the helicopter; Within the speed constraints of the helicopter, an initial velocity is randomly generated; Within the constraint range of the helicopter's all-moving horizontal stabilizer angle, the initial all-moving horizontal stabilizer angle is randomly generated; The initial velocity and the initial all-moving horizontal stabilizer angle are input into the flight dynamics model to obtain the initial rotor hub load and the initial control qualities. Based on the initial velocity, the initial all-moving horizontal stabilizer angle, the initial rotor hub load, and the initial control qualities, a Latin hypercube sampling method is used to generate sample velocities, sample all-moving horizontal stabilizer angles, sample rotor hub loads, and sample control qualities.

4. The method for optimizing the angle of the all-moving horizontal stabilizer of a helicopter according to claim 1, characterized in that, Based on the sequence of all-moving horizontal stabilizer angles corresponding to different velocities, a genetic algorithm and a surrogate model are used for allocation optimization to obtain the optimal all-moving horizontal stabilizer angles for different velocities, specifically including: Real-number encoding is used to encode the all-moving horizontal tail angle sequences corresponding to different velocities, generating multiple coded individuals; each coded individual corresponds to one all-moving horizontal tail angle sequence; multiple coded individuals form the initial population; Input all coded individuals into the surrogate model to obtain the hub load and handling qualities corresponding to each all-moving horizontal stabilizer angle in each coded individual; Based on the hub load and the maneuvering qualities, the fitness function values ​​of all all-moving horizontal stabilizer angles in each coded individual are calculated using a fitness function. The angles of the fully moving horizontal tail in each coded individual with a fitness function value greater than the preset fitness function value are selected to obtain the selected coded individuals and generate the first population; Crossover and mutation are performed on the coded individuals in the first population to obtain the second population; Determine if the maximum number of iterations has been reached; If so, then the optimal all-moving flat-tail angle for each coded individual in the second population is selected; the optimal all-moving flat-tail angle is the all-moving flat-tail angle with the highest fitness function value; If not, then the encoded individuals in the second population are screened, crossovered, and mutated again.

5. The method for optimizing the angle of the all-moving horizontal stabilizer of a helicopter according to claim 4, characterized in that, The expression for the fitness function is: F(θ)=ω1·L(θ)+ω2·Q(θ); Where F(·) is the fitness function; θ is the all-moving horizontal stabilizer angle; ω1 and ω2 are both weighting coefficients; L(·) is the hub load; and Q(·) is the handling quality.

6. The method for optimizing the all-moving horizontal stabilizer angle of a helicopter according to claim 4, characterized in that, Crossover and mutation are performed on the coded individuals in the first population to obtain the second population, which specifically includes: The coded individuals in the first population are cross-crossed using a simulated binary cross-crossing method to obtain the cross-crossed coded individuals. The crossover-coded individuals were mutated using the Gaussian mutation method to obtain the second population.

7. A helicopter all-moving horizontal stabilizer angle optimization system, characterized in that, The helicopter's all-moving horizontal stabilizer angle optimization system includes: The all-moving horizontal stabilizer angle generation module is used to randomly generate a sequence of all-moving horizontal stabilizer angles corresponding to different speeds within the all-moving horizontal stabilizer angle constraint range of the helicopter. The optimization module is used to optimize the allocation of the all-moving horizontal stabilizer angle based on the all-moving horizontal stabilizer angle sequence corresponding to different speeds, using a genetic algorithm and a surrogate model to obtain the optimal all-moving horizontal stabilizer angle corresponding to different speeds, thereby completing the control optimization of the helicopter's all-moving horizontal stabilizer angle; the surrogate model is obtained by fitting and training the Kriging model using a kernel function.

8. A computer device, comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that the processor executes the computer program to implement the all-moving horizontal stabilizer angle optimization method for the helicopter according to any one of claims 1-6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by a processor, the computer program implements the method for optimizing the all-moving horizontal stabilizer angle of the helicopter as described in any one of claims 1-6.

10. A computer program product, comprising a computer program, characterized in that, When executed by a processor, the computer program implements the method for optimizing the all-moving horizontal stabilizer angle of the helicopter as described in any one of claims 1-6.

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