Adaptive Control Method and Medium for Aircraft Main Wheel Coordinated Turning System

Abstract

The present invention provides an adaptive control method and medium for an aircraft main wheel coordinated turning system. The method includes the following steps: performing a force analysis on the process of the aircraft main wheel coordinated with the front wheel turning, and establishing an aircraft main wheel coordinated turning system model; setting an adaptive dynamic observer to realize the real-time estimation of the wheel side slip stiffness and the system state during the aircraft turning process; setting an event-triggered mechanism for the aircraft main wheel coordinated turning system based on random fault injection to achieve high-precision path tracking. The adaptive dynamic observer set in the present invention can accurately identify the side slip stiffness of the aircraft wheels during the turning process, effectively improving the control performance of the system. At the same time, the event-triggered mechanism set reduces unnecessary signal transmission, greatly saving the communication and computing resources of the system, and ensuring the safety and reliability of the aircraft main wheel coordinated turning system.

Description

Technical Field

[0001] The present invention relates to the technical field of aircraft turning control, and particularly relates to an adaptive control method and medium for an aircraft main wheel cooperative turning system. Background Art

[0002] The R & D and manufacturing capabilities of large airliners are important symbols of a country's aviation level. As one of the most core technologies in the aircraft ground maneuvering process, the aircraft turning technology directly affects the ground maneuvering efficiency, safety and reliability of the aircraft. Currently, aircraft ground turning control mainly relies on the front wheel (front landing gear) for steering. However, the steering angle provided by the front wheel is limited, and the movement direction of the main wheels is consistent with the fuselage. When the aircraft travels along a large curvature path, the turning radius is large, the path tracking error is large, and the turning time is long. The main wheel cooperative front wheel turning technology, that is, configuring the main landing gear with the main wheel cooperative turning function, generates a turning angle opposite to that of the front wheel through the main wheels, so as to reduce the turning radius of the fuselage, and thus complete the fast and accurate tracking of the path with a smaller overshoot.

[0003] Generally speaking, the side slip stiffness of the wheels dynamically changes during the turning process, and it is difficult to obtain its accurate value through measurement, that is, the dynamic model of the aircraft main wheel cooperative front wheel turning is inaccurate, which affects the control performance of the turning system. On the other hand, inevitable failures such as hysteresis loss, solenoid valve core offset, piston rod jamming, damper failure, detection device failure, aging, etc. occur in airborne electromechanical actuators, detection devices, etc., posing a huge challenge to the reliable operation and health management of the system. In addition, the research and development of large equipment are gradually developing towards the directions of networking, digitization, and low carbonization. However, the control signals of the aircraft turning system are generally updated periodically following the system sampling frequency. Frequent manipulation of the controller consumes high energy, which is not conducive to cost reduction; too high sampling frequency is likely to cause problems such as network congestion and large computational burden.

[0004] In view of the problems of complex main wheel cooperative front wheel turning technology, inaccurate side slip stiffness of the wheels, fault signals, and large communication and computational burdens caused by too high sampling frequency, there is currently no similar method / technology applied to the aircraft cooperative turning control system. Summary of the Invention

[0005] The purpose of the present invention is: aiming at the deficiencies in the above background art, to provide a control scheme for an aircraft main wheel cooperative turning system to solve the problems of modeling of the aircraft main wheel cooperative turning system, difficult accurate measurement of the side slip stiffness of the wheels, fault signals, and waste of communication and computing resources.

[0006] To achieve the above purpose, the present invention provides an adaptive control method for an aircraft main wheel cooperative turning system, including the following steps:

[0007] S1. Analyze the forces acting on the main wheels of the aircraft during coordinated turning with the front wheels, and establish a model of the aircraft's main wheel coordinated turning system;

[0008] S2. Set up an adaptive dynamic observer to achieve real-time estimation of the tire side slip stiffness and system state during the aircraft turning process;

[0009] S3. Set up an event-triggered mechanism for the aircraft's main wheel coordinated turning system based on random fault injection to achieve high-precision path tracking.

[0010] Furthermore, the model of the aircraft's main wheel coordinated turning system in S1 is:

[0011]

[0012] z = Cx

[0013] where the system state variables The system control input u = [δ f δ m T , the control output The disturbance vector d = [d 1 V x ρ(σ) d 2 d 3 T , χ represents the distance between the center of gravity of the actual aircraft and the virtual aircraft, represents the yaw error, V y represents the lateral speed of the aircraft, r represents the yaw rate, δ f , δ m represent the steering angles of the front wheel and the left and right main wheels respectively, d 1 , d 2 , d 3 represent the combined effect of system modeling errors and external disturbances, ρ(σ) is the curvature of the center point of the virtual aircraft on the desired path, and

[0014] D = I 4

[0015] where, V x is kept constant by the aircraft braking device.

[0016] Furthermore, the adaptive dynamic observer in S2 is:

[0017]

[0018] where, is the state estimate value, L is the observer gain, and

[0019] ​​

[0020] Among them, respectively represent the estimated values of the cornering stiffness of the front wheel and the left and right main wheels.

[0021] Furthermore, the adaptive update rate of the cornering stiffness estimation error defined in S2 is:

[0022]

[0023] Among them, γ φ > 0, λ ∈ (0,1), F ∈ R 4×4 is a random fault matrix, P > 0, represents the mathematical expectation of the random fault of the device, K 1 K 2 is the state feedback matrix, represents the state error caused by the communication network, represents the state quantity at the previous event trigger moment.

[0024] Furthermore, the event trigger mechanism in S3 is:

[0025]

[0026] t k+1 = inf{(t - t k ≥ 0.001 | η ≤ 0) or (t - t k ≥ ι)}

[0027] Among them, ψ(t) represents the probability of the device having a random fault, taking values in the set {0,1}, that is, ψ(t) = 1 indicates that the device is faulty, and ψ(t) = 0 indicates that the device is normal, represents the randomly injected fault signal, F is the fault matrix, τ represents the time interval from the previous transmission moment to the current moment, ι represents the time upper limit of the event trigger mechanism, T represents the time lower limit of the event trigger mechanism, and η represents the internal variable of the event trigger mechanism.

[0028] Furthermore, the time lower limit T of the event trigger mechanism is expressed as:

[0029]

[0030] Among them, p ∈ (0,1), G ≥ 0.

[0031] Furthermore, the internal variable η of the event trigger mechanism is expressed as:

[0032]

[0033] where ε > 0, W(e) = λ||e||, The function is obtained from the following formula:

[0034]

[0035] where

[0036] The present invention also provides a computer-readable storage medium, on which a computer program is stored. The program, when executed by a processor, implements the adaptive control method of the aircraft main wheel coordinated turning system as described above.

[0037] The above solution of the present invention has the following beneficial effects:

[0038] Aiming at the problems of communication and computational resource waste in traditional time-triggered control, the present invention proposes an event-triggered adaptive control scheme for an aircraft main wheel coordinated turning system. The set adaptive dynamic observer can accurately identify the side slip stiffness of the aircraft wheels during the turning process, effectively improving the control performance of the system. At the same time, the set event-triggered mechanism reduces unnecessary signal transmission, greatly saving the communication and computational resources of the system, and ensuring the safety and reliability of the aircraft main wheel coordinated turning system.

[0039] Other beneficial effects of the present invention will be described in detail in the subsequent specific implementation part. Brief Description of the Drawings

[0040] Figure 1 is the flowchart of the steps of the present invention;

[0041] Figure 2 is a schematic diagram of the aircraft main wheel coordinated turning system;

[0042] Figure 3 is the force analysis diagram of the aircraft;

[0043] Figure 4 is the comparison diagram of the actual value and the estimated value of the system state when the mathematical expectation of the equipment failure is 0.1;

[0044] Figure 5 is the comparison diagram of the actual value and the estimated value of the system state when the mathematical expectation of the equipment failure is 0.9;

[0045] Figure 6 is the comparison diagram of the estimated value and the network transmission value of the system state when the mathematical expectation of the equipment failure is 0.1;

[0046] Figure 7Comparison chart of the system state estimation value and the network transmission value when the mathematical expectation of equipment failure is 0.9;

[0047] Figure 8 Comparison chart of the actual and estimated cornering stiffness values of the front wheel and the left and right main wheels when the mathematical expectation of equipment failure is 0.1;

[0048] Figure 9 Comparison chart of the actual and estimated cornering stiffness values of the front wheel and the left and right main wheels when the mathematical expectation of equipment failure is 0.9;

[0049] Figure 10 Comparison chart of the actual and ideal paths of the aircraft when the mathematical expectation of equipment failure is 0.1;

[0050] Figure 11 Comparison chart of the actual and ideal paths of the aircraft when the mathematical expectation of equipment failure is 0.9;

[0051] Figure 12 Trigger time when the mathematical expectation of equipment failure is 0.1;

[0052] Figure 13 Trigger time when the mathematical expectation of equipment failure is 0.9. Specific implementation mode

[0053] The following specific examples illustrate the implementation modes of the present disclosure. Those skilled in the art can easily understand other advantages and effects of the present disclosure from the content disclosed in this specification. Obviously, the described embodiments are only a part of the embodiments of the present disclosure, rather than all the embodiments. The present disclosure can also be implemented or applied through other different specific implementation modes, and various details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of the present disclosure. It should be noted that, without conflict, the following embodiments and the features in the embodiments can be combined with each other. All other embodiments obtained by those of ordinary skill in the art based on the embodiments in the present disclosure without creative efforts belong to the scope of protection of the present disclosure.

[0054] It should be noted that the following describes various aspects of embodiments within the scope of the appended claims. It will be apparent that the aspects described herein can be embodied in a wide variety of forms, and any specific structure and / or function described herein is for illustrative purposes only. Based on this disclosure, those skilled in the art should understand that one aspect described herein can be implemented independently of any other aspect, and two or more of these aspects can be combined in various ways. For example, any number of the aspects described herein can be used to implement a device and / or practice a method. Additionally, this device can be implemented and this method can be practiced using other structures and / or functionality in addition to one or more of the aspects described herein.

[0055] It should also be noted that the diagrams provided in the following embodiments only schematically illustrate the basic concept of the present disclosure. The diagrams only show the components related to the present disclosure and are not drawn according to the number, shape, and size of the components in actual implementation. The type, quantity, and ratio of each component in actual implementation can be arbitrarily changed, and the component layout type may also be more complex. Additionally, in the following description, specific details are provided to facilitate a thorough understanding of the examples. However, those skilled in the art will understand that the aspects described herein can be practiced without these specific details.

[0056] As Figure 1 shown, an embodiment of the present invention provides an adaptive control method for an aircraft main wheel coordinated turning system, including the following steps:

[0057] S1, aircraft main wheel coordinated turning system modeling.

[0058] Figure 1 is a schematic diagram of the aircraft ground turning system. Figure 2 On the right in

[0059]

[0060] is the actual aircraft, and on the left is the virtual aircraft, which is the expected position during the aircraft coordinated turning process. Considering the curvature change of the aircraft moving along the expected path, we can obtain: x , V y respectively represent the longitudinal and lateral speeds of the aircraft, χ represents the distance between the centers of gravity of the actual aircraft and the virtual aircraft, represents the yaw error, and respectively represent the heading angles of the actual aircraft and the virtual aircraft.

[0061] According to the Serret - Frenet formula, we can obtain:

[0062]

[0063] Since the yaw error is small, equation (2) can be simplified as:

[0064]

[0065] Where r represents the yaw rate, d 1 Represents the combined effect of modeling errors and external disturbances.

[0066] Figure 3 This is the force analysis diagram of the aircraft. Assuming that the left main wheel and the right main wheel of the aircraft have the same lateral stiffness and always turn at the same angle, according to Newton's second law and the law of rigid body rotation, we can get:

[0067]

[0068] Among them, F yf , F yml , F ymr They represent the lateral forces of the front wheel, left main wheel, and right main wheel, respectively; m represents the mass of the aircraft, and I z Denotes the heading deflection inertia, d 2 and d 3 represents the superposition effect of modeling error and external disturbance, F yf , F yml , F ymr Respectively expressed as:

[0069]

[0070] Among them, c f , c m Represent the cornering stiffness of the front wheel and the left and right main wheels, α f , α m Represent the sideslip angles of the front wheel and the left and right main wheels respectively:

[0071]

[0072] Among them, δ f , δ m Represent the steering angles of the front wheel and the left and right main wheels respectively, The side slip angle of the aircraft's center of gravity, l f , l m Respectively represent the distance from the front landing gear and the main landing gear to the center of gravity of the aircraft.

[0073] Combining formulas (3) to (6), we can obtain the aircraft main wheel coordinated turning system model:

[0074]

[0075] Among them, the system state quantity System control input \(u = [\delta f \delta m \ T , the control output Interference vector \(d = [d 1 V x \rho(\sigma)d 2 d 3 \ T , \(\chi\) represents the distance between the center of gravity of the actual aircraft and the virtual aircraft, represents the yaw error, \(V y represents the lateral speed of the aircraft, \(r\) represents the yaw rate, \(\delta f , \(\delta m respectively represent the steering angles of the front wheel and the left and right main wheels, \(d 1 , \(d 2 , \(d 3 represent the superposition effect of system modeling errors and external disturbances, \(\rho(\sigma)\) is the curvature of the center point of the virtual aircraft on the desired path, and

[0076] \(D = I 4

[0077] wherein, V x can be kept constant by the aircraft braking device.

[0078] As a preferred embodiment, this embodiment takes the following specific data as an example: \(m = 17690\ kg\), \(l f = 3.81\ m\), \(l m = 0.58\ m\), \(V x = 20\ m / s\), \(c f = 1301500 + 10 3 \sin(0.2t)\), \(c m = 4824700 + 10 3 \cos(0.2t)\), \(x(0, 0, 0, 0)=[2 -0.01 1 0.02] T , d 1 = 0.002\cos(10t)\), \(d 2 = 0.005\cos(10t)\),

[0079] S2, set the adaptive dynamic observer.

[0080] Considering the uncertainty of the cornering stiffness of the front wheel and the left and right main wheels during the coordinated turning of the aircraft main wheels, set the adaptive dynamic observer:

[0081]

[0082] wherein, is the state estimation value, L is the observer gain, and

[0083]

[0084] wherein, respectively represent the estimated values of the cornering stiffness of the front wheel and the left and right main wheels.

[0085] Define the state estimation error the cornering stiffness estimation error Establish a state error dynamics model:

[0086]

[0087] wherein, A L = A + L, and

[0088]

[0089] Define the adaptive update rate of the cornering stiffness estimation error as:

[0090]

[0091] wherein, γ φ > 0 is the adaptive gain, λ ∈ (0,1) is a given scalar, F ∈ R 4×4 is the random fault matrix, P is a positive definite matrix, represents the mathematical expectation of the random fault of the device, K 1 , K 2 is the state feedback matrix, represents the state error caused by the communication network, represents the state quantity at the previous event trigger moment, that is, the network transmission state quantity.

[0092] This embodiment takes the following specific data as an example: γ φ = 1, λ = 10 -3 , F = diag{0.11, 0.25, 0.13, 0.04},

[0093]

[0094]

[0095] S3. Set up a random fault tolerance mechanism for the main wheel cooperative turning system of the aircraft based on event triggering.

[0096] Define the event trigger time series as t 0,t 1 ,…,t k …, where t k represents the triggering moment of the k-th event. The controller output signal is updated at the triggering moment and remains unchanged between two adjacent moments. Considering the equipment failures inside the aircraft and the waste of communication and computing resources, an event-triggering mechanism is set as follows:

[0097]

[0098] t k+1 = inf{(t - t k ≥ 0.001 | η ≤ 0) or (t - t k ≥ ι)}

[0099] where, ψ(t) represents the probability of random equipment failures, taking values in the set {0, 1}, i.e., ψ(t) = 1 indicates equipment failure and ψ(t) = 0 indicates normal equipment, represents the randomly injected fault signal, F is the fault matrix, τ represents the time interval from the previous transmission moment to the current moment, ι represents the time upper limit of the event-triggering mechanism, T represents the time lower limit of the event-triggering mechanism, and η represents the internal variable of the event-triggering mechanism.

[0100] The time lower limit T of the event-triggering mechanism is expressed as:

[0101]

[0102] where, p = 10 -3 is the contraction degree of the Lyapunov function in the transmission time in the event-triggering mechanism, G ≥ 0 is the expansion degree of the Lyapunov function in the transmission time in the event-triggering mechanism,

[0103] The internal variable η of the event-triggering mechanism is expressed as:

[0104]

[0105] where, ε = 0.0184 is the system tuning parameter, W(e) = λ||e|| is the state error of the system, The function can be obtained by the following formula:

[0106]

[0107] where,

[0108] In this embodiment, two specific cases are considered: the mathematical expectations of the equipment failures inside the aircraft are 0.1 and 0.9, i.e., and

[0109]

[0110]

[0111]

[0112]

[0113] Meanwhile,

[0114] In this embodiment, the simulation is carried out based on MATLAB software, and the sampling time is set to 0.001 s. The simulation research results are as Figures 4 to 13 shown Figures 4 to 9 Figure for comparing the results of the adaptive dynamic observer under different equipment failure probabilities. It can be seen that the set adaptive dynamic observer can accurately estimate the system state variables and the cornering stiffness of the front wheel and the left and right main wheels under random equipment failures, and its estimation error is within a reasonable range, laying a foundation for improving the control performance of the aircraft main wheel coordinated turning system. Figure 10 and Figure 11 Schematic diagram of aircraft path tracking under event-triggered control. It can be seen that the proposed control scheme can achieve high-precision path tracking under random equipment failures. Figure 12 and Figure 13 Figure for the event trigger time during the simulation. It can be seen that the event trigger time interval is much larger than the sampling time, greatly saving the communication and computing resources of the system.

[0115] Based on the same inventive concept, this embodiment also provides a computer-readable storage medium, on which a computer program is stored. When the program is executed by a processor, it implements the control method of the aircraft main wheel coordinated turning system described above.

[0116] The computer-readable medium includes, but is not limited to, any type of disk (including floppy disk, hard disk, optical disk, CD-ROM, and magneto-optical disk), ROM, RAM, EPROM (Erasable Programmable Read-Only Memory), EEPROM, flash memory, magnetic card, or optical card. That is to say, the readable medium includes any medium that stores or transmits information in a form that can be read by a device (such as a computer).

[0117] The beneficial effects of the computer-readable storage medium are similar to those of the foregoing method, and will not be elaborated here.

[0118] The above are the preferred embodiments of the present invention. It should be noted that for those of ordinary skill in the art, without departing from the principle of the present invention, several improvements and modifications can be made, and these improvements and modifications should also be regarded as the protection scope of the present invention.

Claims

1. An adaptive control method for the aircraft main wheel coordinated turning system, characterized in that, it includes the following steps: S1. Analyze the forces acting on the aircraft main wheel during the coordinated turning with the front wheel, and establish an aircraft main wheel coordinated turning system model; S2. Set an adaptive dynamic observer to achieve real-time estimation of the wheel side slip stiffness and the system state during the aircraft turning process; S3. Set an event-triggered mechanism for the aircraft main wheel coordinated turning system based on random fault injection to achieve high-precision path tracking; The event-triggered mechanism is: t k+1 = inf{(t - t k ≥ 0.001 | η ≤ 0) or (t - t k ≥ ι)} Among them, ψ(t) represents the probability of random faults occurring in the device, taking values in the set {0, 1}, that is, ψ(t) = 1 indicates that the device has a fault, and ψ(t) = 0 indicates that the device is normal. represents the randomly injected fault signal, F is the fault matrix, τ represents the time interval from the previous transmission moment to the current moment, ι represents the time upper limit of the event trigger mechanism, T represents the time lower limit of the event trigger mechanism, η represents the internal variable of the event trigger mechanism, K 1 , K 2 is the state feedback matrix.

2. The adaptive control method for the aircraft main wheel coordinated turning system according to claim 1, characterized in that, the aircraft main wheel coordinated turning system model in S1 is: z = Cx Among them, the system state variables The system control input u = [δ f δ m T , the control output The disturbance vector d = [d 1 V x ρ(σ)d 2 d 3 T , χ represents the distance between the centers of gravity of the actual aircraft and the virtual aircraft, represents the yaw error, V y represents the lateral velocity of the aircraft, r represents the yaw rate, δ f , δ m respectively represent the steering angles of the front wheel and the left and right main wheels, d 1 , d 2 , d 3 represents the superposition effect of the system modeling error and external disturbances, ρ(σ) is the curvature of the center point of the virtual aircraft on the desired path, and​​ D = I 4 Among them, V x is kept constant by the aircraft braking device.

3. The adaptive control method for the aircraft main wheel coordinated turning system according to claim 2, characterized in that, the adaptive dynamic observer in S2 is: wherein, is the state estimated value, L is the observer gain, and Among them, respectively represent the estimated values of the cornering stiffness of the front wheel and the left and right main wheels.

4. The adaptive control method for the aircraft main wheel coordinated turning system according to claim 3, characterized in that, Define the adaptive update rate of the side slip stiffness estimation error in S2 as follows: where γ φ > 0, λ ∈ (0, 1), F ∈ R 4×4 is a random failure matrix, P > 0, represents the mathematical expectation of the random failure of the device, K 1 , K 2 is the state feedback matrix, represents the state error caused by the communication network, represents the state quantity at the previous event triggering moment.

5. The adaptive control method for the aircraft main wheel coordinated turning system according to claim 4, characterized in that, the lower time limit T of the event-triggered mechanism is expressed as: where p ∈ (0, 1), G ≥ 0.

6. The adaptive control method for the aircraft main wheel coordinated turning system according to claim 5, characterized in that, the internal variable η of the event-triggered mechanism is expressed as: where ε > 0, W(e) = λ||e||, function is obtained by the following formula: Among them, 7. A computer-readable storage medium, on which a computer program is stored, characterized in that, when the program is executed by a processor, it implements the adaptive control method for the aircraft main wheel coordinated turning system according to any one of claims 1-6.

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