Variable stability flight control method based on fixed time increment dynamic inversion

Abstract

The invention relates to the technical field of flight simulation, in particular to a variable stability flight control method based on fixed time increment dynamic inversion, and the method comprises the steps: firstly building an aircraft six-degree-of-freedom dynamics and kinematics affine nonlinear model; secondly, establishing an airplane longitudinal and transverse course tracking reference model according to a flight quality evaluation criterion; and finally, designing an outer ring controller and an inner ring controller by utilizing a fixed-time convergence incremental dynamic inverse control method, and driving the airplane model to quickly and accurately track the control response characteristics of the reference model. According to the method, the capability of dynamically simulating different levels of flight quality in the same set of flight simulation model is realized, and the limitation of one type and one quality of a traditional flight simulation model is avoided; meanwhile, the scheduling work that a nonlinear model of the airplane needs to configure a controller at a plurality of trim points is reduced; the problem that after the model deviates from the trim point, the control response under the expected flight quality is difficult to generate is solved.

Description

Technical Field

[0001] This invention relates to the field of flight simulation technology, specifically to a variable stability flight control method based on fixed time increment dynamic inverse, which supports changing the aircraft's handling response characteristics within the same flight simulation model to achieve dynamic simulation of different levels of flight quality. Background Technology

[0002] A flight simulation model is a simulation system that simulates the flight motion of an aircraft. Traditional flight simulation models are characterized by being "one-type-one-quality," meaning they can only simulate the flight qualities of a single aircraft type. To support pilot quality evaluation training scenarios, it is necessary to provide simulations of the handling response characteristics of different aircraft. Since establishing multiple flight simulation models would significantly increase training costs, variable stability flight simulation models are needed. These models can change the aircraft's handling response characteristics within the same system, providing simulations of different flight quality characteristics.

[0003] Existing variable stability flight simulations are mainly achieved through two control methods: one utilizes the feedback principle to directly adjust the feedback gain, thereby altering flight stability; the other uses feedback to make the simulation model track the control response of a reference model. However, both methods require linearizing the simulation model. Since aircraft are nonlinear systems, multiple linearization controllers need to be configured at multiple trim points, resulting in a huge workload for gain scheduling. Therefore, a control method is needed that can reduce gain scheduling workload while utilizing existing nonlinear aerodynamic data packages, enabling the flight simulation model to produce the desired control response.

[0004] Incremental dynamic inverse control (IVR) is widely used in the control of nonlinear systems due to its strong robustness to model uncertainties and external disturbances. By using IVR to counteract the inherent nonlinear dynamic characteristics of high-fidelity aircraft models, complex nonlinear systems can be transformed into globally linearized "pseudo-linear systems." Traditional IVR methods can only guarantee asymptotic or finite-time convergence of the closed-loop system; introducing fixed-time convergence IVR can improve the convergence speed of the closed-loop system. Summary of the Invention

[0005] The purpose of this invention is to provide a variable stability flight control method based on fixed-time incremental dynamic inverse. This method utilizes a fixed-time convergent incremental dynamic inverse control law to drive a simulated aircraft to rapidly track the handling response characteristics of a pre-built reference model, thereby achieving the ability to dynamically simulate different levels of flight quality within the same flight simulation model. The technical solution of this invention is as follows.

[0006] A variable stability flight control method based on fixed-time-increment dynamic inverse includes the following steps:

[0007] Step 1: Establish a nonlinear model of aircraft dynamics and kinematics;

[0008] Step 2: Express the aircraft dynamics and kinematics models established in Step 1 in affine nonlinear form;

[0009] Step 3: Establish a tracking reference model based on flight quality evaluation criteria. In the longitudinal direction, select the CAP criterion to measure short-period characteristics and establish a low-order equivalent system model with single fitting for short-period. In the lateral direction, consider the Dutch roll mode, roll mode and spin mode and establish a low-order equivalent system model with double fitting for roll angle and sideslip angle.

[0010] Step 4: Determine the target to be tracked by the controller based on the tracking reference model established in Step 3: pitch angular velocity target. Roll angle target Sideslip angle target ;

[0011] Step 5: Design the outer and inner loop controllers using the incremental dynamic inverse control method with fixed-time convergence, and calculate the outer loop angle tracking error. The outer loop control law input is obtained; the inner loop angular velocity tracking error is calculated. The inner loop control law input is obtained;

[0012] Preferably, the dynamic model equations in step one are:

[0013] (1)

[0014] In the formula, The angular velocities of the aircraft's three axes; For the aerodynamic torque of the engine system; A coefficient related to the engine's angular momentum and moment of inertia; to The coefficient related to the aircraft's inertia;

[0015] Preferably, the kinematic model equations in step one are:

[0016] (2)

[0017] In the formula, These are the aircraft's roll angle, pitch angle, and sideslip angle; Angle of attack; Vacuum speed; Acceleration of the aircraft's airframe system;

[0018] Preferably, the affine nonlinear form of the dynamic model in step two is:

[0019] (3)

[0020] In the formula, ; For commands to control the aileron, elevator, and rudder deflection angles, it is necessary to obtain aerodynamic moments from the dynamic equations. Separated from; The matrix formed by the aerodynamic derivative terms related to the control surfaces depends on the specific aircraft model;

[0021] Preferably, the affine nonlinear form of the kinematic model in step two is:

[0022] (4)

[0023] In the formula, , , ;

[0024] Preferably, the short-period single-fit low-order equivalent system model in step three is:

[0025] (5)

[0026] In the formula, To manipulate the desired parameters, It is a short-period frequency; For short-cycle damping ratio; Equivalent gain; ;

[0027] Preferably, the roll angle fitting low-order equivalent system model in step three is as follows:

[0028] (6)

[0029] In the formula, The time constant of the helical mode; The time constant of the roll mode; The frequency of the Dutch rolling mode; The damping ratio for the Dutch rolling mode; Equivalent gain; The natural frequency of the equivalent zero; This is the equivalent zero-point damping ratio;

[0030] Preferably, the low-order equivalent system model for fitting the sideslip angle in step three is as follows:

[0031] (7)

[0032] In the formula, Equivalent gain; The equivalent molecular time constant;

[0033] Preferably, the pitch angular velocity target in step four for:

[0034] (8)

[0035] Preferably, the target roll angle in step four for:

[0036] (9)

[0037] Preferably, the sideslip angle target in step four for:

[0038] (10)

[0039] Preferably, the outer ring angle tracking error in step five for:

[0040] (11)

[0041] In the formula, since the longitudinal tracking target is the pitch angular velocity... This is achieved through the inner-loop control law, therefore the outer-loop... Only the target values ​​for roll angle and sideslip angle are provided. Feedback on roll angle and sideslip angle;

[0042] Preferably, the outer-loop control law input in step five is:

[0043] (12)

[0044] In the formula, These are the derivatives of the roll angle and sideslip angle of the previous time step; These are the roll rate and yaw rate of the previous time step; , The control gain matrix is ​​the fixed-time convergent incremental dynamic inverse outer loop control law. To track the target using roll rate and yaw rate;

[0045] Preferably, the inner loop angular velocity tracking error in step five for:

[0046] (13)

[0047] In the formula, ,in, , Depend on get, Obtained from a longitudinal low-order equivalent model;

[0048] Preferably, the inner-loop control law input in step five is:

[0049] (14)

[0050] In the formula, This represents the angular acceleration at the previous time step; This is the control input for the previous time step; , The control gain matrix is ​​the fixed-time convergent incremental dynamic inverse inner-loop control law.

[0051] The beneficial effects of this invention are as follows:

[0052] 1) It avoids the limitation of traditional flight simulation models being "one type, one quality" and realizes the ability to adjust different levels of flight quality on a single simulation platform, providing an efficient and flexible simulation environment for scenarios such as pilot quality evaluation training, flight control law design and verification;

[0053] 2) It can make full use of existing nonlinear aerodynamic data packages, eliminating the need to configure multiple linearization controllers at multiple trim points, thus reducing the scheduling work required for controller configuration; it solves the problem that the model is difficult to produce the desired flight quality control response after deviating from the trim point.

[0054] 3) The introduction of a fixed-time convergent incremental dynamic inverse control method improves the convergence speed of the closed-loop system, enabling the aircraft model to quickly track the response of the reference model and realize rapid dynamic simulation of responses to different handling characteristics. Attached Figure Description

[0055] Figure 1 This is a schematic diagram of a variable stability flight control law based on a fixed time increment dynamic inverse.

[0056] Figure 2 The simulation results are shown in the figure for different short-cycle damping ratios.

[0057] Figure 3 The simulation results are shown in the figure for configuring different short-period manipulation desired parameters.

[0058] Figure 4 Simulation results for different Dutch rolling damping ratios are shown in the figure.

[0059] Figure 5 The simulation results are shown in the figure for different Dutch roll frequencies.

[0060] Figure 6 The simulation results are shown in the figure for configuring different roll mode time constants.

[0061] Figure 7 The simulation results are shown in the figure to compare the dynamic inverse with the fixed-time increment and the traditional asymptotic increment. Detailed Implementation

[0062] The present invention will now be described in further detail with reference to the accompanying drawings and embodiments.

[0063] This invention discloses a variable stability flight control method based on fixed-time-increment dynamic inverse, comprising the following steps:

[0064] Step 1: Establish a nonlinear model of aircraft dynamics and kinematics.

[0065] Dynamic model: (15)

[0066] In the formula, The angular velocities of the aircraft's three axes; For the aerodynamic torque of the engine system; A coefficient related to the engine's angular momentum and moment of inertia; to The coefficient related to the aircraft's inertia;

[0067] Kinematic model: (16)

[0068] In the formula, These are the aircraft's roll angle, pitch angle, and sideslip angle; Angle of attack; Vacuum speed; Acceleration of the aircraft's airframe system;

[0069] Step 2: Express the aircraft dynamics and kinematics models established in Step 1 in affine nonlinear form.

[0070] Affine nonlinear form of the dynamic model: (17)

[0071] In the formula, ; For commands to control the aileron, elevator, and rudder deflection angles, it is necessary to obtain aerodynamic moments from the dynamic equations. Separated from; The matrix formed by the aerodynamic derivative terms related to the control surfaces depends on the specific aircraft model;

[0072] Affine nonlinear form of the kinematic model: (18)

[0073] In the formula, , , ;

[0074] Step 3: Establish a tracking reference model based on flight quality evaluation criteria.

[0075] By selecting the CAP criterion, which measures short-period characteristics, and establishing a low-order equivalent system model with a single fit for short periods:

[0076] (19)

[0077] In the formula, To manipulate the desired parameters, It is a short-period frequency; For short-cycle damping ratio; Equivalent gain; ;

[0078] Laterally, the Dutch roll mode, roll angle mode, and spiral mode are considered. A low-order equivalent system model with double fitting for roll angle and sideslip angle is established:

[0079] Roll angle fitting low-order equivalent system model: (20)

[0080] In the formula, The time constant of the helical mode; The time constant of the roll mode; The frequency of the Dutch rolling mode; The damping ratio for the Dutch rolling mode; Equivalent gain; The natural frequency of the equivalent zero; This is the equivalent zero-point damping ratio;

[0081] Sideslip angle fitting low-order equivalent system model: (twenty one)

[0082] In the formula, Equivalent gain; The equivalent molecular time constant;

[0083] Step 4: Determine the tracking target of the controller based on the tracking reference model established in Step 3:

[0084] Pitch angular velocity tracking target: (twenty two)

[0085] The target for roll angle tracking is: (twenty three)

[0086] The target for sideslip angle tracking is: (twenty four)

[0087] Step 5: Design the outer and inner loop controllers using the incremental dynamic inverse control method with fixed-time convergence.

[0088] Calculate the outer ring angle tracking error: (25)

[0089] In the formula, since the longitudinal tracking target is the pitch angular velocity... This is achieved through the inner-loop control law, therefore the outer-loop... Only the target values ​​for roll angle and sideslip angle are provided. Feedback on roll angle and sideslip angle;

[0090] The outer loop control law input is obtained as follows: (26)

[0091] In the formula, These are the derivatives of the roll angle and sideslip angle of the previous time step; These are the roll rate and yaw rate of the previous time step; , The control gain matrix is ​​the fixed-time convergent incremental dynamic inverse outer loop control law. To track the target using roll rate and yaw rate;

[0092] Calculate the inner loop angular velocity tracking error: (27)

[0093] In the formula, ,in, , Depend on get, Obtained from a longitudinal low-order equivalent model;

[0094] : (28)

[0095] In the formula, This represents the angular acceleration at the previous time step; This is the control input for the previous time step; , The control gain matrix is ​​the fixed-time convergent incremental dynamic inverse inner-loop control law.

[0096] A schematic diagram of a variable stability flight control law based on fixed-time-increment dynamic inverse established according to the above steps is shown below. Figure 1 As shown.

[0097] The variable stability flight control method based on fixed time increment dynamic inverse established according to the above steps can be verified by the following simulation.

[0098] First, the changes in flight quality caused by externally configured longitudinal short-period modal parameters were verified. The initial flight conditions were selected as an altitude of 5000 meters and a speed of 150 m / s. The externally configured short-period damping ratio was... As shown in Table 1, the angle of attack under three operating conditions is compared under elevator pulse multiplier action. Pitch angular velocity and pitch angle Changes, such as Figure 2 As shown, it can be seen that with the increase of damping ratio, the angle of attack... Pitch angular velocity and pitch angle The reduced oscillations altered the aircraft's short-cycle damping ratio characteristics. Externally configured short-cycle control desired parameters... As shown in Table 2 This reflects the short-period frequency characteristics. Under elevator pulse multiplication, the angle of attack under three operating conditions is compared. Pitch angular velocity and pitch angle Changes, such as Figure 3 As shown in the figure, it can be seen that as the frequency decreases, the angle of attack... Pitch angular velocity and pitch angle The response slows down, the oscillation period lengthens, and the short-period frequency characteristics of the aircraft are altered.

[0099] surface External configuration short-cycle damping ratio

[0100] Operating conditions Short-period parameters Operating Condition 1 CAP = 2, short-cycle damping ratio = 0.1 Operating Condition 2 CAP = 2, short-cycle damping ratio = 0.2 Operating Condition 3 CAP = 2, short-cycle damping ratio = 0.3

[0101] surface External configuration short-cycle manipulation desired parameters

[0102] Operating conditions Short-period parameters Operating Condition 1 CAP = 20, short-cycle damping ratio = 0.3 Operating Condition 2 CAP = 10, short-cycle damping ratio = 0.3 Operating Condition 3 CAP = 2, short-cycle damping ratio = 0.3

[0103] Secondly, the changes in flight quality caused by externally configured lateral modal parameters were verified. The initial flight conditions were selected as an altitude of 5000 meters, a speed of 150 m / s, and an externally configured Dutch rolling damping ratio. As shown in Table 3, the yaw rate is compared under three operating conditions under rudder pulse multiplier action. Sideslip angle Changes, such as Figure 4 As shown in the figure, it can be seen that the yaw rate increases with increasing damping ratio. Sideslip angle The reduced oscillations altered the aircraft's Dutch roll mode damping ratio characteristics. The externally configured Dutch roll frequency... As shown in Table 4, the yaw rate is compared under three operating conditions under rudder pulse multiplier action. Sideslip angle Changes, such as Figure 5 As shown in the figure, the yaw rate decreases with decreasing frequency. Sideslip angle The slower response and longer oscillation period altered the frequency characteristics of the aircraft's Dutch roll mode. The externally configured roll mode time constant... As shown in Table 5, the roll angles under three operating conditions are compared when the aileron step command is applied. Roll angular velocity Changes, such as Figure 6 As shown in the figure, it can be seen that as the time constant decreases, the roll angular velocity... Faster response, roll angle The faster convergence alters the convergence characteristics of the aircraft's roll mode.

[0104] surface External configuration Dutch rolling damping ratio

[0105] Operating conditions Dutch rolling parameters Operating Condition 1 Dutch rolling frequency = 4, Dutch rolling damping ratio = 0.15 Operating Condition 2 Dutch rolling frequency = 4, Dutch rolling damping ratio = 0.3 Operating Condition 3 Dutch rolling frequency = 4, Dutch rolling damping ratio = 0.5

[0106] surface External configuration Dutch roll frequency

[0107] Operating conditions Dutch rolling parameters Operating Condition 1 Dutch rolling frequency = 1, Dutch rolling damping ratio = 0.5 Operating Condition 2 Dutch rolling frequency = 2, Dutch rolling damping ratio = 0.5 Operating Condition 3 Dutch rolling frequency = 4, Dutch rolling damping ratio = 0.5

[0108] surface External configuration of roll mode time constant

[0109] Operating conditions Rolling modal parameters Operating Condition 1 Roll mode time constant = 2 Operating Condition 2 Roll mode time constant = 1 Operating Condition 3 Roll mode time constant = 0.1

[0110] Furthermore, the control effects of the fixed-time convergent incremental dynamic inverse control method and the traditional asymptotically convergent incremental dynamic inverse control method are compared. Compared to the fixed-time convergent incremental dynamic inverse control laws of equations (26) and (28), the outer and inner loop control laws of the traditional asymptotically convergent incremental dynamic inverse control method can be expressed as equations (29) and (30), respectively. Simulation results are as follows: Figure 7 As shown, the aircraft's pitch angular velocity Sideslip angle Roll angle With the fixed-time convergent incremental dynamic inverse control method, the reference target can be tracked more quickly and accurately. , , This demonstrates the convergence superiority of the fixed-time convergent incremental dynamic inverse.

[0111] (29)

[0112] (30)

[0113] In summary, this invention provides a variable stability flight control method based on fixed-time incremental dynamic inverse. By utilizing a fixed-time convergent incremental dynamic inverse control law, the simulated aircraft is driven to quickly track the handling response characteristics of a pre-built reference model, thereby realizing the ability to rapidly and dynamically simulate different levels of flight quality within the same flight simulation model.

[0114] It is understood that those skilled in the art can make equivalent substitutions or modifications to the technical solutions and inventive concepts of the present invention, and all such substitutions or modifications should fall within the protection scope of the appended claims.

Claims

1. A variable stability flight control method based on fixed-time-increment dynamic inverse, characterized in that, Includes the following steps: Step 1: Establish a nonlinear model of aircraft dynamics and kinematics; Step 2: Express the aircraft dynamics and kinematics models established in Step 1 in affine nonlinear form; Step 3: Establish a tracking reference model based on flight quality evaluation criteria. In the longitudinal direction, select the CAP criterion to measure short-period characteristics and establish a low-order equivalent system model with single fitting for short-period. In the lateral direction, consider the Dutch roll mode, roll mode and spin mode and establish a low-order equivalent system model with double fitting for roll angle and sideslip angle. Step 4: Determine the target to be tracked by the controller based on the tracking reference model established in Step 3: pitch angular velocity target. Roll angle target Sideslip angle target ; Step 5: Design the outer and inner loop controllers using the incremental dynamic inverse control method with fixed-time convergence, and calculate the outer loop angle tracking error. The outer loop control law input is obtained; the inner loop angular velocity tracking error is calculated. The inner loop control law input is obtained.

2. The variable stability flight control method based on fixed-time-increment dynamic inverse as described in claim 1, characterized in that, In step one: The dynamic model equations are: （1） In the formula, The angular velocities of the aircraft's three axes; For the aerodynamic torque of the engine system; A coefficient related to the engine's angular momentum and moment of inertia; to The coefficient related to the aircraft's inertia; The kinematic model equations are: （2） In the formula, These are the aircraft's roll angle, pitch angle, and sideslip angle; Angle of attack; Vacuum speed; Accelerate the aircraft's airframe system.

3. The variable stability flight control method based on fixed-time-increment dynamic inverse as described in claim 1, characterized in that, In step two: The affine nonlinear form of the dynamic model is: （3） In the formula, ; For commands to control the aileron, elevator, and rudder deflection angles, it is necessary to obtain aerodynamic moments from the dynamic equations. Separated from; The affine nonlinear form of the kinematic model is: （4） In the formula, , , .

4. The variable stability flight control method based on fixed-time-increment dynamic inverse as described in claim 1, characterized in that, In step three: The short-period monofit low-order equivalent system model is as follows: （5） In the formula, To manipulate the desired parameters, It is a short-period frequency; For short-cycle damping ratio; Equivalent gain; ; The roll angle fitting low-order equivalent system model is as follows: （6） In the formula, The time constant of the helical mode; The time constant of the roll mode; The frequency of the Dutch rolling mode; The damping ratio for the Dutch roll mode; Equivalent gain; The natural frequency of the equivalent zero; This is the equivalent zero-point damping ratio; The low-order equivalent system model for sideslip angle fitting is as follows: （7） In the formula, Equivalent gain; This is the equivalent molecular time constant.

5. The variable stability flight control method based on fixed-time-increment dynamic inverse as described in claim 1, characterized in that, In step four: Pitch angular velocity target for: （8） Roll angle target for: （9） Sideslip angle target for: （10）。 6. The variable stability flight control method based on fixed-time-increment dynamic inverse as described in claim 1, characterized in that, In step five: Outer ring angle tracking error for: （11） In the formula, since the longitudinal tracking target is the pitch angular velocity... This is achieved through the inner-loop control law, therefore the outer-loop... Only the target values ​​for roll angle and sideslip angle are provided. Feedback on roll angle and sideslip angle; The input to the outer loop control law is: （12） In the formula, These are the derivatives of the roll angle and sideslip angle of the previous time step; These are the roll rate and yaw rate of the previous time step; , The control gain matrix is ​​the fixed-time convergent incremental dynamic inverse outer loop control law. To track the target using roll angular velocity and yaw angular velocity.

7. The variable stability flight control method based on fixed-time-increment dynamic inverse as described in claim 1, characterized in that, In step five: Inner ring angular velocity tracking error for: （13） In the formula, ,in, , Depend on get, Obtained from a longitudinal low-order equivalent model; The input to the inner loop control law is: （14） In the formula, This represents the angular acceleration at the previous time step; This is the control input for the previous time step; , The control gain matrix is ​​the fixed-time convergent incremental dynamic inverse inner-loop control law.

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