Stability enhancing system for lateral hierarchical control method of airplane

Abstract

The invention provides a stability enhancing system for an aircraft transverse hierarchical control method, belongs to the technical field of automatic flight control, and relates to the technical field of automatic flight control. And the design standard of a civil aviation IIIa-level control system is met. The system adopts a hierarchical control architecture combining outer ring PID (Proportion Integration Differentiation) track tracking control and inner ring transverse course model predictive control (MPC). The outer ring PID control is responsible for basic tracking of the track, and the inner ring MPC is used for fine adjustment of the course angle and the track so as to ensure that the aircraft is accurately aligned with the runway and flies stably. By combining the simplicity of PID control and the multivariable optimization capability of MPC, the method not only improves the control precision and the response speed, but also significantly reduces the calculation burden, and enhances the robustness and the anti-interference capability of the system. The system can effectively improve the stability of transverse control of the aircraft in a complex flight environment, and ensures the safety and reliability of the aircraft when the aircraft executes an automatic landing task.

Description

Technical Field

[0001] The invention belongs to the technical field of automatic flight control and designs a stability enhancement system for an aircraft lateral layered control method. Background Art

[0002] Fixed-wing aircraft, including civil airliners, military aircraft, and drones, all need to perform takeoff and landing procedures. Especially the landing process, which is a complex and challenging task, often involves many accidents. Therefore, designing an automatic landing system with robustness and precise control capabilities to combat external interference has become an urgent task in the aviation field. With the continuous advancement of aviation technology and the growing demand for civil aviation, highly automated flight control systems, especially automatic landing systems, are gradually becoming the focus of research. These systems can significantly improve flight safety and operational efficiency under complex flight conditions such as low visibility and bad weather.

[0003] During the automatic landing process, the importance of lateral control (such as track tracking and crosswind compensation) is particularly prominent. Lateral control is not only directly related to the precise heading tracking of the aircraft, but is also crucial to key tasks such as ensuring a smooth landing and avoiding runway deviation. It is an indispensable part of the automatic landing system, especially in complex environments, and can effectively ensure that the aircraft moves stably and safely along the predetermined route during flight.

[0004] Model predictive control (MPC) is becoming the mainstream method for automatic landing system research due to its superior constraint processing capabilities and optimization performance, especially its application in automatic landing control of fixed-wing aircraft, which has attracted widespread attention. Future research is expected to make greater breakthroughs in the integration and optimization of MPC and other advanced control strategies to cope with more complex and dynamic flight environments, further improve the accuracy and robustness of lateral control, and ensure flight safety. Summary of the invention

[0005] The purpose of the present invention is to solve the need for an automatic landing system with robust and precise control capabilities against external interference in the prior art. The present invention provides an aircraft lateral layered control method stability enhancement system. The specific control method adopts a control mode combining outer loop PID control with inner loop MPC control to improve the effectiveness of safe automatic landing of the aircraft.

[0006] In order to achieve the above-mentioned purpose, the present invention specifically adopts the following technical solution: a stability enhancement system for a lateral layered control method of an aircraft, further comprising the following steps:

[0007] S1: Establish a mathematical model for automatic landing of aircraft lateral motion;

[0008] S2: After the aircraft is ready to land, obtain the lateral motion trajectory tracking instructions of the aircraft at each stage, namely, the localizer deviation ξ, the heading ψ, and the runway heading ψ rw , real-time height H. These signals are sent to the outer loop PID controller for accurate tracking and generation of the target roll angle φ g instruction;

[0009] S3: The target roll angle φ output by the outer loop PID controller g and the target speed V of the aircraft g Sent to the inner loop MPC controller as the input of the inner loop control, and the command δ to control the aircraft aileron rudder is obtained a and the command to release the rudder r ;

[0010] S4: According to the control instructions output by the controller and the mathematical model of automatic landing of the aircraft lateral motion described, the real-time dynamic signal of the aircraft is obtained to realize the control of the automatic landing of the aircraft.

[0011] According to the stability enhancement system of the aircraft lateral layered control method of claim 1, further, in said S1, when designing the flight control system, whether it is using the traditional classical control theory PID control or using many modern control theories to control the aircraft, it is necessary to obtain the approximate dynamic linearization equation of the aircraft equation. The linear model is determined by the nonlinear model of the aircraft body. The most commonly used method is to linearize the nonlinear state equation according to the principle of small disturbance. According to the principle of separation of linear disturbance motion, linearization and decoupling are performed at the equilibrium point to obtain the continuous domain lateral motion state space equation:

[0012]

[0013] Among them, Δβ, Δp, Δr, Δφ are the aircraft's sideslip angle increment, roll angular velocity increment, yaw angular velocity increment, and roll angle increment, respectively. Δδ a Input increment for the aircraft aileron deflection angle, Δδ r Enter the increment for the aircraft's rudder deflection angle. β , Y p , Y r , Y φ , L β , L p , L r 、N β , is the aircraft lateral state matrix coefficient.

[0014] According to the aircraft lateral layered control method stability enhancement system of claim 1, further, the outer loop control rate of each stage designed in S2 is as follows:

[0015] 1) Course selection control law algorithm

[0016] The function of the altitude hold control law is to control the aircraft to turn and fly toward the center line of the localizer at a certain intercept angle until the localizer beam is intercepted.

[0017] φ g =K ψ (ψ g -ψ) (2)

[0018] In the formula, K ψ is the heading deviation coefficient.

[0019] 2) Localizer modal control law algorithm

[0020] The localizer control law is used to control the aircraft's horizontal beam centerline flight along the runway direction, mainly introducing LOC deviation and aircraft heading signal. In order to better meet the index requirements for the lateral control accuracy of the approach, the localizer modal control law needs to be designed in sections according to the initial capture and tracking sub-mode and the terminal tracking sub-mode.

[0021] Initial acquisition and tracking phase,

[0022] φ g =K ξ ξ+K ψ (ψ RH -ψ) (3)

[0023] In the formula, K ξ is the proportionality coefficient, K ψ is the proportionality coefficient.

[0024] The final tracking stage,

[0025]

[0026] In the formula, is the differential coefficient.

[0027] 3) Alignment with the runway control law

[0028] The runway alignment control law aligns the nose of the aircraft with the centerline of the runway by controlling the rudder and keeping the wings level.

[0029]

[0030] In the formula, δ r is the rudder command, K r It is the proportional coefficient of the heading angle and the runway heading deviation.

[0031] 4) Low nose control law

[0032] The nose-down control law will turn the nose of the airplane downward so that the nose gear touches the runway softly.

[0033] θ g =K θ (6)

[0034] In the formula, K θ is the target pitch angle.

[0035] 4. According to the aircraft lateral layered control method stability enhancement system of claim 1, further, the inner loop attitude MPC control rate in S3 is designed as follows: the continuous domain lateral aircraft state space equation in S1 is discretized with a mission cycle of 0.02 seconds. Fixed-wing aircraft automatic landing control belongs to typical trajectory tracking control, and the lateral and lateral state variable parameters are defined as:

[0036] x r =[ Δβ Δp Δr Δφ ] T (7)

[0037] Define the lateral control output parameters:

[0038] u r =[Δδ a Δδ r ] (8)

[0039] The tracking error of the instruction is defined as

[0040] e r =x r -x d (9)

[0041] In the formula, x d Indicates the desired target value. The aircraft can roll according to the target angle φ g In steady-state flight, the desired aircraft's Δβ, Δp, and Δr are generally set to 0, that is,

[0042] x d =[0 0 0 φ g ] (10)

[0043] Consider the roll angle tracking error e of the control system in the future r The minimum, and the aileron control surface and rudder output of the aircraft are the minimum. The cost function of the optimal lateral control is as follows:

[0044]

[0045] Here, considering the control performance and computational load, the model prediction interval cannot be too large. The model prediction interval of the lateral model predictive controller is defined as N = 20, that is, the prediction interval time is T = 20*0.02s. Define the lateral control state quantity weight coefficient Q r and the control quantity weight coefficient R r as follows:

[0046]

[0047] The lateral control constraint matrix is ​​as follows:

[0048] x r (k+1)=G r x r (k)+H r u r (k) (13)

[0049] in G r and H r As a known matrix, the model prediction interval of the lateral model predictive controller is also defined as N = 20, that is, the time of the prediction interval is T = 20*0.02s. Considering the upper and lower bounds of the control variables, the constraints of the matrix U are:

[0050]

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

[0052] The present invention adopts a hierarchical control method of outer loop trajectory tracking PID control and inner loop attitude model predictive control (MPC). As an advanced control strategy, MPC shows significant advantages in processing multivariable systems, optimizing target control and real-time scheduling under constraints. The model predictive control (MPC) method is particularly suitable for dynamically changing complex environments due to its powerful prediction ability and online optimization characteristics. The present invention designs a new automatic landing control system that can significantly improve the stability of automatic landing of aircraft. The system is not only easy to implement in engineering, but also can be converted into software requirements, which is convenient for coding and debugging, and has strong engineering practice value. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] Figure 1 is a flow chart of the method provided by the present invention;

[0054] Figure 2 is an architecture diagram for implementing the method provided by the present invention;

[0055] Figure 3 is a schematic diagram of the division of various stages of automatic landing of an aircraft in an embodiment of the present invention;

[0056] Figure 4 This is an effect diagram of the outer loop trajectory tracking control provided by an embodiment of the present invention;

[0057] Figure 5 This is a diagram showing the inner loop attitude control effect provided by an embodiment of the present invention;

[0058] Figure 6 A schematic diagram of flight trajectory control provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0060] To make the purpose, technical solution and advantages of the embodiments of the present invention more clear, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention.

[0061] This embodiment provides an aircraft lateral layering control method stability enhancement system, which is mainly used to solve the problem of automatic flight landing control and provides the following technical solutions. Figure 1-Figure 6 Make a detailed description:

[0062] The present invention is further described in detail below with reference to the accompanying drawings, the working process of the present invention:

[0063] S1: Establish a mathematical model for automatic landing of aircraft lateral motion;

[0064] S2: After the aircraft is ready to land, obtain the lateral motion trajectory tracking instructions of the aircraft at each stage, namely, the localizer deviation ξ, the heading ψ, and the runway heading ψ rw , real-time height H. These signals are sent to the outer loop PID controller for accurate tracking and generation of the target roll angle φ g instruction;

[0065] S3: The target roll angle φ output by the outer loop PID controller g and the target speed V of the aircraft g Sent to the inner loop MPC controller as the input of the inner loop control, and the command δ to control the aircraft aileron rudder is obtained a and the command to release the rudder r ;

[0066] S4: According to the control instructions output by the controller and the mathematical model of automatic landing of the aircraft lateral motion described, the real-time dynamic signal of the aircraft is obtained to realize the control of the automatic landing of the aircraft.

[0067] In some embodiments, the S1 includes:

[0068] When designing a flight control system, whether using traditional classical control theory PID control or many modern control theories to control the aircraft, it is necessary to obtain the linearized equations of the approximate dynamics of the aircraft equations. The most commonly used method is to linearize the nonlinear state equations based on the principle of small disturbances by determining its linear model from the nonlinear model of the aircraft body. According to the principle of separation of linear disturbance motion, linearization and decoupling are performed at the equilibrium point, and the continuous domain lateral motion state space equation is obtained as follows:

[0069]

[0070] Among them, Δβ, Δp, Δr, Δφ are the aircraft's sideslip angle increment, roll angular velocity increment, yaw angular velocity increment, and roll angle increment, respectively. Δδ a Input increment for the aircraft aileron deflection angle, Δδ r Enter the increment for the aircraft's rudder deflection angle. β , Y p , Y r , Y φ , L β , L p , L r 、N β , is the aircraft lateral state matrix coefficient.

[0071] In some embodiments, the outer loop control rates of each stage designed in S2 are as follows:

[0072] 1) Course selection control law algorithm

[0073] The function of the altitude hold control law is to control the aircraft to turn and fly toward the center line of the localizer at a certain intercept angle until the localizer beam is intercepted.

[0074] φ g =K ψ (ψ g -ψ) (2)

[0075] In the formula, K ψ is the heading deviation coefficient.

[0076] 2) Localizer modal control law algorithm

[0077] The localizer control law is used to control the aircraft's horizontal beam centerline flight along the runway direction, mainly introducing LOC deviation and aircraft heading signal. In order to better meet the index requirements for the lateral control accuracy of the approach, the localizer modal control law needs to be designed in sections according to the initial capture and tracking sub-mode and the terminal tracking sub-mode.

[0078] Initial acquisition and tracking phase,

[0079] φg =K ξ ξ+K ψ (ψ RH -ψ) (3)

[0080] In the formula, K ξ is the proportionality coefficient, K ψ is the proportionality coefficient.

[0081] The final tracking stage,

[0082]

[0083] In the formula, is the differential coefficient.

[0084] 3) Alignment with the runway control law

[0085] The runway alignment control law aligns the nose of the aircraft with the centerline of the runway by controlling the rudder and keeping the wings level.

[0086]

[0087] In the formula, δ r is the rudder command, K r It is the proportional coefficient of the heading angle and the runway heading deviation.

[0088] 4) Low nose control law

[0089] The nose-down control law will turn the nose of the airplane downward so that the nose gear touches the runway softly.

[0090] θ g =K θ (6)

[0091] In the formula, K θ is the target pitch angle.

[0092] In some embodiments, the inner loop attitude MPC control rate in S3 is designed as follows:

[0093] Discretize the continuous domain lateral aircraft state space equations in S1 with a mission period of 0.02 seconds. Fixed-wing aircraft automatic landing control is a typical trajectory tracking control, and the lateral and side state variable parameters are defined as:

[0094] x r =[ Δβ Δp Δr Δφ ] T (7)

[0095] Define the lateral control output parameters:

[0096] u r =[Δδ a Δδr ] (8)

[0097] The tracking error of the instruction is defined as

[0098] e r =x r -x d (9)

[0099] In the formula, x d Indicates the desired target value. The aircraft can roll according to the target angle φ g In steady-state flight, the desired aircraft's Δβ, Δp, and Δr are generally set to 0, that is,

[0100] x d =[0 0 0 φ g ] (10)

[0101] Consider the roll angle tracking error e of the control system in the future r The minimum, and the aileron control surface and rudder output of the aircraft are the minimum. The cost function of the optimal lateral control is as follows:

[0102]

[0103] Here, considering the control performance and computational load, the model prediction interval cannot be too large. The model prediction interval of the lateral model predictive controller is defined as N = 20, that is, the prediction interval time is T = 20*0.02s. Define the lateral control state quantity weight coefficient Q r and the control quantity weight coefficient R r as follows:

[0104]

[0105] The lateral control constraint matrix is ​​as follows:

[0106] x r (k+1)=G r x r (k)+H r u r (k) (13)

[0107] in G r and H r As a known matrix, the model prediction interval of the lateral model predictive controller is also defined as N = 20, that is, the time of the prediction interval is T = 20*0.02s. Considering the upper and lower bounds of the control variables, the constraints of the matrix U are:

[0108]

[0109] In some embodiments, the real-time dynamic signal of the aircraft is obtained according to the control instructions output by the controller and the mathematical model of the automatic landing of the aircraft lateral motion described, so as to realize the control of the automatic landing of the aircraft.

[0110] This implementation uses Matlab to carry out simulation experiments and draws the corresponding landing simulation diagram, as shown in the figure. Figure 4 The initial simulation flight parameters are as follows: 1. The initial calibrated airspeed of the aircraft is 75m / s; 2. The initial altitude of the aircraft is 500m; 3. The weight of the aircraft is 46000kg; 4. The initial flight heading is 0 degrees; 5. The target flight heading angle is -50 degrees; 6. The flaps are lowered to 35 degrees.

[0111] like Figure 4 and Figure 5 The figure shows the spatial position curve of the aircraft in the lateral plane and the time-varying curve of each lateral flight state in each stage of the automatic landing. In a stable atmospheric environment, the example aircraft initially flies at an approach speed of 65m / s in a level flight state at an altitude of 500m, while turning right and flying towards a target heading angle of -50 degrees, with an interception angle of 50 degrees with the centerline of the runway. When the angle between the aircraft and the centerline of the runway is less than 0.3 to 2 degrees, the localizer is intercepted and the flight direction is adjusted for heading tracking, with a maximum heading overshoot of 1 degree. When the angle between the aircraft and the centerline of the glide path is less than 0.05 to 0.2 degrees, the glide path is successfully intercepted and tracking is started, while the flight speed remains unchanged. In the leveling stage, when the altitude approaches 9m, the autothrottle is reduced to 0.3, and the lateral mode is switched from the localizer mode to the runway alignment mode. The aircraft finally lands at a distance of 180m to 227m from the intersection of the runway, and the lateral landing point is close to the centerline of the runway. During the entire flight, both MPC control and PID control showed satisfactory control effects, especially in the output actions of the elevator, aileron, rudder and throttle angle. MPC was able to achieve smoother control, ensuring accurate tracking of the localizer and glide path and safe landing.

[0112] In addition, from Figure 6 It can be seen that during the descent, the overall control of the aircraft is stable, the entire motion trajectory of the aircraft accurately tracks the centerline of the glide path, and does not exceed the boundary of the 2-degree glide beam line. After the aircraft has been gliding for a period of time, the aircraft begins to slowly approach the centerline of the glide path, and finally returns to the centerline of the glide path. In this process, both MPC control and PID control have achieved satisfactory control effects, and all indicators meet the relevant requirements of the civil aircraft industry standards, reflecting the effectiveness of the hierarchical control method designed by the present invention.

[0113] The above description of the disclosed embodiments enables one skilled in the art to implement or use the present invention. Various modifications to these embodiments will be apparent to one skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but rather to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. An aircraft lateral layering control method stability enhancement system, characterized by: The steps include: S1: Establish a mathematical model for automatic landing of aircraft lateral motion; S2: After the aircraft is ready to land, obtain the lateral motion trajectory tracking instructions of the aircraft at each stage, namely, the localizer deviation ξ, the heading ψ, and the runway heading ψ rw , real-time height H. These signals are sent to the outer loop PID controller for accurate tracking and generation of the target roll angle φ g instruction; S3: The target roll angle φ output by the outer loop PID controller g and the target speed V of the aircraft g Sent to the inner loop MPC controller as the input of the inner loop control, and the command δ to control the aircraft aileron rudder is obtained a and the command to release the rudder r ; S4: According to the control instructions output by the controller and the mathematical model of automatic landing of the aircraft lateral motion described, the real-time dynamic signal of the aircraft is obtained to realize the control of the automatic landing of the aircraft.

2. The aircraft lateral layering control method stability enhancement system according to claim 1, characterized in that: In the above S1, when designing the flight control system, whether it is the traditional classical control theory PID control or many modern control theories to control the aircraft, it is necessary to obtain the linearized equation of the approximate dynamics of the aircraft equation. The most commonly used method to determine the linear model of the aircraft body is to linearize the nonlinear state equation according to the small disturbance principle. According to the principle of separation of linear perturbation motion, linearization and decoupling are performed at the equilibrium point, and the continuous domain lateral motion state space equation is obtained as follows: Among them, Δβ, Δp, Δr, Δφ are the aircraft's sideslip angle increment, roll angular velocity increment, yaw angular velocity increment, and roll angle increment, respectively. Δδ a Input increment for the aircraft aileron deflection angle, Δδ r Enter the increment for the aircraft's rudder deflection angle. β , Y p , Y r , Y φ , L β , L p , L r 、N β , is the aircraft lateral state matrix coefficient.

3. The aircraft lateral layering control method stability enhancement system according to claim 1, characterized in that: The outer loop control rates of each stage designed in S2 are as follows: 1) Course selection control law algorithm The function of the altitude hold control law is to control the aircraft to turn and fly toward the center line of the localizer at a certain intercept angle until the localizer beam is intercepted. f g =K ψ (ψ g -ψ) (2) In the formula, K ψ is the heading deviation coefficient. 2) Localizer modal control law algorithm The localizer control law is used to control the aircraft's horizontal beam centerline flight along the runway direction, mainly introducing LOC deviation and aircraft heading signal. In order to better meet the index requirements for the lateral control accuracy of the approach, the localizer modal control law needs to be designed in sections according to the initial capture and tracking sub-mode and the terminal tracking sub-mode. Initial acquisition and tracking phase, f g =K ξ ξ+K ψ (ψ RH -ψ) (3) In the formula, K ξ is the proportionality coefficient, K ψ is the proportionality coefficient. The final tracking stage, In the formula, is the differential coefficient. 3) Alignment with the runway control law The runway alignment control law aligns the nose of the aircraft with the centerline of the runway by controlling the rudder and keeping the wings level. In the formula, δ r is the rudder command, K r It is the proportional coefficient of the heading angle and the runway heading deviation. 4) Low nose control law The nose-down control law will turn the nose of the airplane downward so that the nose gear touches the runway softly. i g =K θ (6) In the formula, K θ is the target pitch angle.

4. The aircraft lateral layering control method stability enhancement system according to claim 1, characterized in that: The inner loop attitude MPC control rate in S3 is designed as follows: the continuous domain lateral aircraft state space equation in S1 is discretized with a mission period of 0.02 seconds. Fixed-wing aircraft automatic landing control belongs to typical trajectory tracking control, and the lateral and side state variable parameters are defined as: x r =[ ΔβΔp ΔrΔφ ] T (7) Define the lateral control output parameters: you r =[Dδ a Dd r ] (8) Define the tracking error of the instruction as e r =x r -x d (9) In the formula, x d Indicates the desired target value. The aircraft can roll according to the target angle φ g In steady-state flight, the desired aircraft's Δβ, Δp, and Δr are generally set to 0, that is, x d =[0 0 0 φ g ] (10) Consider the roll angle tracking error e of the control system in the future r The minimum, and the aileron control surface and rudder output of the aircraft are the minimum. The cost function of the optimal lateral control is as follows: Here, considering the control performance and computational load, the model prediction interval cannot be too large. The model prediction interval of the lateral model predictive controller is defined as N = 20, that is, the prediction interval time is T = 20*0.02s. Define the lateral control state quantity weight coefficient Q r and the control quantity weight coefficient R r as follows: The lateral control constraint matrix is ​​as follows: x r (k+1)=G r x r (k)+H r u r (k) (13) in G r and H r As a known matrix, the model prediction interval of the lateral model predictive controller is also defined as N = 20, that is, the time of the prediction interval is T = 20*0.02s. Considering the upper and lower bounds of the control variables, the constraints of the matrix U are:

Images