Global flight control method, system and equipment for double-flying-wing vertical take-off and landing unmanned aerial vehicle

Abstract

The invention belongs to the technical field of unmanned aerial vehicle flight control, and particularly relates to a global flight control method, system and equipment for a double-flying-wing vertical take-off and landing unmanned aerial vehicle, and the global flight control method comprises the steps: firstly constructing a T-S fuzzy model of the double-flying-wing vertical take-off and landing unmanned aerial vehicle facing external disturbance; a flight controller is designed based on the obtained T-S fuzzy model, the flight controller comprises a state feedback controller and a nonlinear feedforward controller, and full-speed-domain flight control of the double-flying-wing vertical take-off and landing unmanned aerial vehicle is achieved through the flight controller. Stable flight control in the transition process can be achieved under external disturbance, disturbance resisting capacity is achieved, full-speed-domain flight control can be achieved, and flexible speed changing capacity is achieved.

Description

Technical Field

[0001] The present invention belongs to the technical field of unmanned aerial vehicle (UAV) flight control, and in particular relates to a global flight control method, system, equipment and medium for a dual-wing vertical take-off and landing UAV. Background Art

[0002] Vertical take-off and landing (VTOL) aircraft combine the advantages of traditional fixed-wing aircraft and rotary-wing flight. In addition to common tailseat, tilt-rotor, and combined VTOL configurations, many novel configurations have been developed in recent years. Among them, the new twin-wing VTOL drone for electric power systems is a configuration with great development potential. The twin-wing VTOL drone achieves the transition between vertical take-off and landing and cruising by changing the angle of the fuselage. Due to its tandem-wing distributed propulsion system, most of the wings are immersed in the propeller slipstream, greatly enhancing the aircraft's aerodynamic force and control torque, allowing the aircraft to fly at any track angle without worrying about traditional stall issues. The twin-wing VTOL drone also uses a curved landing gear configuration, which greatly reduces the terrain restrictions on the aircraft's take-off and landing site, while also effectively addressing the issue of attitude changes during landing.

[0003] Twin-wing vertical take-off and landing (VTOL) drones achieve mode transitions between vertical take-off and landing (VTOL) and cruise level flight by changing the thrust direction. During this transition, the aircraft must fly under off-design conditions, such as low speed and high angle of attack. The aerodynamic forces of the wing under off-design conditions are severely nonlinear. Existing technologies, such as the invention patent application number 202211723162.9, which describes a tail-seat vertical take-off and landing drone attitude control method, use a feedforward controller described by a linear model. This controller essentially compensates and corrects through adjustable parameters and is not suitable for severely nonlinear transition states. Therefore, achieving smooth and flexible flight control during transitions in the face of external disturbances presents challenges. Summary of the Invention

[0004] The purpose of the present invention is to address the above-mentioned problems existing in the prior art and to provide a global flight control method and system for a double-wing vertical take-off and landing UAV that can achieve smooth flight control during the transition process under external disturbances and has flexible speed change capabilities.

[0005] To achieve the above objectives, the technical solutions of the present invention are as follows:

[0006] In a first aspect, the present invention provides a global flight control method for a twin-wing vertical take-off and landing UAV, the global flight control method comprising:

[0007] Construct a TS fuzzy model of a twin-wing vertical take-off and landing UAV facing external disturbances;

[0008] Designing a flight controller based on the TS fuzzy model, wherein the flight controller includes a state feedback controller and a nonlinear feedforward controller;

[0009] The flight controller is used to realize full-speed flight control of the twin-wing vertical take-off and landing UAV.

[0010] The TS fuzzy model of the twin-wing vertical take-off and landing UAV facing external disturbances is constructed according to the following steps:

[0011] Construct the dynamic motion equations of a twin-wing vertical take-off and landing UAV facing external disturbances:

[0012]

[0013] In the above formula, U and w are the forward and vertical velocity components of the UAV body axis respectively; θ is the pitch angle; q is the pitch angle rate; F aero,x 、F d,x are respectively the aerodynamic force component and the disturbance force component of the body in the ox axis direction; F aero,z 、F d,z are respectively the aerodynamic force component and the disturbance force component of the body in the oz-axis direction; M aero,y 、M d M is the pitching moment and disturbance moment of the aircraft in the oy-axis direction; T Represents the pitching moment generated by propeller thrust; I yy represents the longitudinal moment of inertia of the drone along the body axis, m and g are the total mass and gravity acceleration of the drone respectively; x E 、z E represents the horizontal forward and vertical upward displacement of the aircraft after the geodetic coordinate system is rotated to the same direction as the forward axis of the aircraft body; F T The thrust generated by the propeller; Represent U, w, θ, q, x respectively E 、z E rate of change;

[0014] The dynamic equation of motion is rewritten as the following first equation:

[0015]

[0016] In the above formula, x=[θ,u,w,q,h], represents the displacement of x, which is used to achieve tracking purposes; x* represents the desired state of x; h is the flight altitude; d represents the external disturbance; u is the control variable; A, B, and D are all state space matrices; express rate of change;

[0017] Introduce a nonlinear feedforward controller u into the first equationff And through simulation calculation method, the full speed range flight data table is constructed to make the equation Ax * +Bu ff = 0, the propeller thrust and pitching moment generated by the propeller thrust in the full-speed flight data table are used as control outputs, and the pitch angle, forward speed, and vertical speed in the full-speed flight data table are used as state quantities;

[0018] Introducing u ff Then, rewrite the first equation into the second equation Then according to the equation Ax * +Bu ff =0 and the second equation Rewrite as And perform fuzzy expansion on the B matrix to obtain the following TS fuzzy model:

[0019]

[0020] In the above formula, B i is the i-th fuzzy matrix; h i B i The weight function of ; i∈{1,2,…,N}, N represents the total number of elements in the fuzzy set.

[0021] Design the flight controller according to the following steps:

[0022] Define the error signal e as The matrix C is Adding integration to the TS fuzzy model to eliminate the steady-state error, we get the fuzzy representation of the TS fuzzy model and the error signal:

[0023]

[0024] In the above formula, the subscript L represents the corresponding parameter representation generated by fuzzy logic after the fuzzy system adds the integral; express rate of change;

[0025] Based on the TS fuzzy model and the fuzzy representation of the error signal, the following flight controller u is designed. During flight control, the error signal e is made to converge to zero over time through the flight controller u to achieve error tracking:

[0026]

[0027] In the above formula, u b 、u ff are state feedback controller and nonlinear feedforward controller respectively; K Li To control the gain.

[0028] The full-speed range flight data table includes flight data of the UAV in different flight states, where the flight state includes at least one of climbing, level flight, level flight acceleration, and level flight deceleration.

[0029] In a second aspect, the present invention provides a global flight control system for a twin-wing vertical take-off and landing UAV, the global flight control system comprising:

[0030] The UAV mathematical model construction module is used to construct the TS fuzzy model of a twin-wing vertical take-off and landing UAV under external disturbances;

[0031] A flight controller design module, used to design a flight controller based on the TS fuzzy model, wherein the flight controller includes a state feedback controller and a nonlinear feedforward controller;

[0032] The flight control module is used to realize full-speed flight control of the twin-wing vertical take-off and landing UAV using a flight controller.

[0033] The UAV mathematical model construction module is used to construct a TS fuzzy model of a twin-wing vertical take-off and landing UAV facing external disturbances according to the following steps:

[0034] Construct the dynamic motion equations of a twin-wing vertical take-off and landing UAV facing external disturbances:

[0035]

[0036] In the above formula, U and w are the forward and vertical velocity components of the UAV body axis respectively; θ is the pitch angle; q is the pitch angle rate; F aero,x 、F d,x are respectively the aerodynamic force component and the disturbance force component of the body in the ox axis direction; F aero,z 、F d,z are respectively the aerodynamic force component and the disturbance force component of the body in the oz-axis direction; M aero,y 、M d M is the pitching moment and disturbance moment of the aircraft in the oy-axis direction; T Represents the pitching moment generated by propeller thrust; I yy represents the longitudinal moment of inertia of the drone along the body axis, m and g are the total mass and gravity acceleration of the drone respectively; x E 、z E represents the horizontal forward and vertical upward displacement of the aircraft after the geodetic coordinate system is rotated to the same direction as the forward axis of the aircraft body; F T The thrust generated by the propeller; Represent U, w, θ, q, x respectively E 、z E rate of change;

[0037] The dynamic equation of motion is rewritten as the following first equation:

[0038]

[0039] In the above formula, x=[θ,u,w,q,h], represents the displacement of x, which is used to achieve tracking purposes; x* represents the desired state of x; h is the flight altitude; d represents the external disturbance; u is the control variable; A, B, and D are all state space matrices; express rate of change;

[0040] S13, introduce the nonlinear feedforward controller uff into the first equation, and construct the full-speed range flight data table through simulation calculation method to make the equation Ax * +Bu ff = 0, the propeller thrust and pitching moment generated by the propeller thrust in the full-speed flight data table are used as control outputs, and the pitch angle, forward speed, and vertical speed in the full-speed flight data table are used as state quantities; the nonlinear feedforward controller u ff It is obtained based on the flight data table calculated a priori based on the flight state, and is also applicable to both linear and nonlinear states;

[0041] Introducing u ff Then, rewrite the first equation into the second equation Then according to the equation Ax * +Bu ff =0The second equation Rewrite as And perform fuzzy expansion on the B matrix to obtain the following TS fuzzy model:

[0042]

[0043] In the above formula, B i is the i-th fuzzy matrix; h i B i The weight function of ; i∈{1,2,…,N}, N represents the total number of elements in the fuzzy set.

[0044] The flight controller design module designs the flight controller by the following steps:

[0045] Define the error signal e as The matrix C is

[0046] Adding integration to the TS fuzzy model to eliminate the steady-state error, we get the fuzzy representation of the TS fuzzy model and the error signal:

[0047]

[0048] In the above formula, the subscript L represents the corresponding parameter representation generated by fuzzy logic after the fuzzy system adds the integral; express rate of change;

[0049] Based on the TS fuzzy model and the fuzzy representation of the error signal, the following flight controller u is designed. During flight control, the error signal e is made to converge to zero over time through the flight controller u to achieve error tracking:

[0050]

[0051] In the above formula, u b 、u ff are state feedback controller and nonlinear feedforward controller respectively; K Li To control the gain.

[0052] The full-speed range flight data table includes flight data of the UAV in different flight states, where the flight state includes at least one of climbing, level flight, level flight acceleration, and level flight deceleration.

[0053] In a third aspect, the present invention provides a global flight control device for a twin-wing vertical take-off and landing UAV, the global flight control device comprising a memory and a processor; the memory is used to store computer program code and transfer the computer program code to the processor; the processor is used to execute the aforementioned method according to the instructions in the computer program code.

[0054] In a fourth aspect, the present invention provides a computer-readable storage medium having a computer program stored thereon, and the computer program implements the aforementioned method when executed by a processor.

[0055] Compared with the prior art, the present invention has the following beneficial effects:

[0056] The global flight control method for a twin-wing vertical take-off and landing UAV described in the present invention first constructs a TS fuzzy model of the twin-wing vertical take-off and landing UAV facing external disturbances, and then designs a flight controller based on the obtained TS fuzzy model. The flight controller includes a state feedback controller and a nonlinear feedforward controller. The flight controller is used to achieve full-speed flight control of the twin-wing vertical take-off and landing UAV. The above-mentioned design can achieve smooth flight control during the transition process facing external disturbances, has anti-disturbance capability, and can achieve full-speed flight control with flexible speed change capability. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] Figure 1 This is a flow chart of the global flight control method described in the present invention.

[0058] Figure 2 Full speed domain flight data table constructed for the present invention.

[0059] Figure 3 This is the simulation analysis result.

[0060] Figure 4 This is a structural block diagram of the global flight control system described in the present invention.

[0061] Figure 5 This is a structural block diagram of the global flight control device described in the present invention. DETAILED DESCRIPTION

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

[0063] Example 1:

[0064] See also Figure 1 A global flight control method for a dual-wing vertical take-off and landing UAV is performed in the following steps:

[0065] S1. Construct a TS fuzzy model of a twin-wing vertical take-off and landing UAV facing external disturbances;

[0066] S11. Construct the dynamic motion equations of a twin-wing vertical take-off and landing UAV under external disturbances:

[0067]

[0068] In the above formula, U and w are the forward and vertical velocity components of the UAV body axis respectively; θ is the pitch angle; q is the pitch angle rate; F aero,x 、F d,x are respectively the aerodynamic force component and the disturbance force component of the body in the ox axis direction; F aero,z 、F d,z are respectively the aerodynamic force component and the disturbance force component of the body in the oz-axis direction; M aero,y 、M d M is the pitching moment and disturbance moment of the aircraft in the oy-axis direction; T Represents the pitching moment generated by propeller thrust; I yy represents the longitudinal moment of inertia of the drone along the body axis, m and g are the total mass and gravity acceleration of the drone respectively; x E 、z E represents the horizontal forward and vertical upward displacement of the aircraft after the geodetic coordinate system is rotated to the same direction as the forward axis of the aircraft body; F T The thrust generated by the propeller; Represent U, w, θ, q, x respectively E 、z E rate of change;

[0069] S12. Rewrite the dynamic motion equation described in S11 into the following first equation:

[0070]

[0071] In the above formula, x=[θ,u,w,q,h], represents the displacement of x, which is used to achieve state tracking; x* represents the desired state of x; h is the flight altitude; d represents the external disturbance, which includes the disturbance force component in the ox-axis direction of the body, the disturbance force component in the oz-axis direction of the body, and the disturbance torque in the oy-axis direction of the body; u is the control quantity; A, B, and D are all state space matrices; surface

[0072] shows the rate of change of x;

[0073] S13, introduce the nonlinear feedforward controller u into the first equation of S12 ff ,u ff It is the estimated control quantity required to achieve a given state, and the full-speed domain flight data table is constructed through simulation calculation to make the equation Ax * +Bu ff = 0 holds true; the full-speed flight data table includes flight data of the drone in different flight states, the flight states including but not limited to: climbing, level flight, level flight acceleration, level flight deceleration; the flight data including but not limited to: propeller thrust, pitching moment generated by propeller thrust, pitch angle, forward speed, vertical speed; for example, the simulation calculation method is used to construct the following Figure 2 The full speed range flight data table shown, Figure 2 Figures (a)-(e) correspond to the propeller thrust, pitching moment, forward velocity, vertical velocity, and pitch angle under different flight conditions, respectively. The first two flight data items are used as control outputs, and the last three flight data items are used as state quantities. To improve control accuracy, other flight data items such as rudder angle, angle of attack, and track angle can be further added.

[0074] S14, introduce u ff Then, rewrite the first equation into the second equation Then according to the equation Ax * +Buff=0 The second equation described in S12 Rewrite as And perform fuzzy expansion on the B matrix to obtain the following TS fuzzy model:

[0075]

[0076] In the above formula, B i is the i-th fuzzy matrix; hi B i The weight function of ; i∈{1,2,…,N}, N represents the total number of elements in the fuzzy set, i.e., the fuzzy subsystem; h i The following constraints must be met:

[0077] S2. Design the flight controller based on the TS fuzzy model obtained in S14;

[0078] S21, define the error signal e as The matrix C is S22, adding integration to the TS fuzzy model obtained in S14 to eliminate the steady-state error, and obtaining the fuzzy representation of the TS fuzzy model and the error signal:

[0079]

[0080] In the above formula, the subscript L represents the corresponding parameter representation generated by fuzzy logic after the fuzzy system adds the integral;

[0081] S23. Based on the TS fuzzy model and the fuzzy representation of the error signal described in S22, the following flight controller u is designed. During flight control, the error signal e is caused to converge to zero over time through the flight controller, gradually reaching a given state (desired state) to achieve error tracking.

[0082]

[0083] In the above formula, u b 、u ff are state feedback controller and nonlinear feedforward controller respectively; K Li To control the gain;

[0084] The external disturbance d includes the disturbance force component of the body in the ox axis direction, the disturbance force component of the body in the oz axis direction, and the disturbance torque of the body in the oy axis direction;

[0085] S3. Use the flight controller to realize full-speed flight control of the twin-wing vertical take-off and landing UAV.

[0086] Performance Verification:

[0087] 1. No external interference analysis:

[0088] Get the nominal model of the fuzzy representation of the TS fuzzy model Among them B L i is B L The representation after fuzzy expansion;

[0089] Given a symmetric positive definite gain control matrix Q,R: Where J is the cost function; take the symmetric positive definite matrix P and the matrix K that satisfies the following formula L i:

[0090] min(Trace(M))

[0091]

[0092] In the above formula, define X=P -1 , Y j =K j X, K j It represents the feedback gain matrix of the jth fuzzy subsystem, which is obtained by solving the linear matrix inequality LMI. It should be noted that K j With K Lj The symbols belonging to different derivation stages are different, but they are essentially the same physical quantity, namely the feedback gain matrix. The matrix M is defined as a symmetric positive definite matrix, which is used to constrain the upper bound of the control performance index. The matrix inequality constraint relationship The original non-convex optimization problem is transformed into a solvable convex optimization problem, satisfying the minimization of Trace(M), where Trace(M) refers to the trace of the matrix M, thereby indirectly optimizing the system state error and weighted comprehensive index; I is the identity matrix;

[0093] Choose a Lyapunov function:

[0094] It can be proven that the following conditions are met:

[0095] The above can illustrate the asymptotic stability of the system.

[0096] Further, yes Integrating to infinity and taking advantage of the asymptotic stability of the system, we can obtain:

[0097]

[0098] When the cost function J is minimized, P has a unique solution.

[0099] 2. Analysis of external interference:

[0100] For the TS fuzzy model fuzzy representation H ∞ For robustness analysis, we take the symmetric positive definite matrix P and the matrix K that satisfies the following formula: i :

[0101]

[0102] In the above formula, X=P -1 , Y j =K LjX, Trace is the trace of the matrix M, I is the identity matrix; γ is the maximum disturbance suppression ratio;

[0103] Select Ω ij <0, multiply both sides by You can get:

[0104]

[0105] It can be proven that the following conditions are met:

[0106]

[0107]

[0108] The asymptotic stability of the system can be described by the Lyapunov function.

[0109] Furthermore, Ω ij <0 is equivalent to:

[0110]

[0111] In the case of zero initial state, consider the cost function:

[0112]

[0113] Due to the asymptotic stability of the system, when T→∞, ||e||2≤γ||d||2, and γ is taken as an integer greater than 0, it can be proved that the system has anti-interference ability.

[0114] Compared with H ∞ In the control, only the maximum disturbance suppression ratio γ is concerned. The present invention jointly designs M, X, Y j , achieving the closed-loop system dynamic performance (through Trace(M)) and anti-disturbance capability (through ||e||2≤γ||d||2).

[0115] 3. Simulation analysis:

[0116] In the flight speed range of the double-wing vertical take-off and landing UAV, multiple speed points from hovering to cruising speed are selected, and the double-wing vertical take-off and landing is accelerated and decelerated. The simulation results are as follows: Figure 3 shown.

[0117] from Figure 3As can be seen, the global flight control method described in this invention effectively controls a twin-wing vertical takeoff and landing aircraft, enabling timely and effective tracking of the desired trajectory. It switches between hovering mode and high-speed cruise mode while maintaining altitude, while also providing flexible speed changes, rather than simply transitioning from high to low speed and back again. It also achieves low-speed, high-angle-of-attack level flight control at 35 km / h.

[0118] Example 2:

[0119] See also Figure 4 A global flight control system for a twin-wing vertical take-off and landing UAV includes a UAV mathematical model construction module and a flight controller design module. The UAV mathematical model construction module is used to construct a TS fuzzy model of the twin-wing vertical take-off and landing UAV under external disturbances. Specifically, the UAV mathematical model construction module is used to construct the TS fuzzy model of the twin-wing vertical take-off and landing UAV under external disturbances according to the following steps:

[0120] S11. Construct the dynamic motion equations of a twin-wing vertical take-off and landing UAV under external disturbances:

[0121]

[0122] In the above formula, U and w are the forward and vertical velocity components of the UAV body axis respectively; θ is the pitch angle; q is the pitch angle rate; F aero,x 、F d,x are respectively the aerodynamic force component and the disturbance force component of the body in the ox axis direction; F aero,z 、F d,z are respectively the aerodynamic force component and the disturbance force component of the body in the oz-axis direction; M aero,y 、M d M is the pitching moment and disturbance moment of the aircraft in the oy-axis direction; T Represents the pitching moment generated by propeller thrust; I yy represents the longitudinal moment of inertia of the drone along the body axis, m and g are the total mass and gravity acceleration of the drone respectively; x E 、z E represents the horizontal forward and vertical upward displacement of the aircraft after the geodetic coordinate system is rotated to the same direction as the forward axis of the aircraft body; F T The thrust generated by the propeller; Represent U, w, θ, q, x respectively E 、z E rate of change;

[0123] S12. Rewrite the dynamic motion equation described in S11 into the following first equation:

[0124]

[0125] In the above formula, x = [θ, u, w, q, h], x represents the displacement of x, which is used to achieve tracking purposes; x* represents the desired state of x; h is the flight altitude; d represents the external disturbance, including the disturbance force component of the body in the ox-axis direction, the disturbance force component of the body in the oz-axis direction, and the disturbance torque of the body in the oy-axis direction; u is the control variable; A, B, and D are all state space matrices; express rate of change;

[0126] S13, introduce a nonlinear feedforward controller uff into the first equation in S12, and construct a full-speed flight data table by simulation calculation method to make the equation Ax * +Bu ff =0, the full-speed flight data table includes flight data of the UAV in different flight states, including climb, level flight, level flight acceleration, and level flight deceleration. The propeller thrust and the pitching moment generated by the propeller thrust in the full-speed flight data table are used as control outputs, and the pitch angle, forward speed, and vertical speed in the full-speed flight data table are used as state quantities;

[0127] S14. After introducing uff, rewrite the first equation into the second equation Then according to the equation Ax * +Bu ff =0Rewrite the second equation as And perform fuzzy expansion on the B matrix to obtain the following TS fuzzy model:

[0128]

[0129] In the above formula, B i is the i-th fuzzy matrix; h i B i The weight function of ; i∈{1,2,...,N}, N represents the total number of elements in the fuzzy set;

[0130] The flight controller design module designs the flight controller by the following steps:

[0131] S21, define the error signal e as The matrix C is

[0132] S22, adding integration to the TS fuzzy model obtained in S14 to eliminate the steady-state error, and obtaining the fuzzy representation of the TS fuzzy model and the error signal:

[0133]

[0134] In the above formula, the subscript L represents the corresponding parameter representation generated by fuzzy logic after the fuzzy system adds the integral;

[0135] S23. Based on the TS fuzzy model and the fuzzy representation of the error signal described in S22, the following flight controller u is designed. During flight control, the error signal e is made to converge to zero over time through the flight controller to achieve error tracking:

[0136]

[0137] In the above formula, u b 、u ff are state feedback controller and nonlinear feedforward controller respectively; K Li To control the gain;

[0138] The flight control module is used to realize full-speed flight control of the twin-wing vertical take-off and landing UAV using a flight controller.

[0139] Example 3:

[0140] See also Figure 5 , a global flight control device for a double-wing vertical take-off and landing UAV, comprising a memory and a processor; the memory is used to store computer program code and transmit the computer program code to the processor; the processor is used to execute the global flight control method described in Example 1 according to instructions in the computer program code.

[0141] Example 4:

[0142] A computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the global flight control method described in Example 1.

[0143] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may take the form of a complete hardware embodiment, a complete software embodiment, or a combination of software and hardware embodiments. Furthermore, the present application may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0144] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems) and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0145] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0146] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0147] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents. Any modification or equivalent replacement that does not depart from the spirit and scope of the present invention should be covered by the scope of protection of the claims of the present invention.

Claims

1. A global flight control method for a twin-wing vertical take-off and landing UAV, characterized by: The global flight control method includes: Construct a TS fuzzy model of a twin-wing vertical take-off and landing UAV facing external disturbances; Designing a flight controller based on the TS fuzzy model, wherein the flight controller includes a state feedback controller and a nonlinear feedforward controller; The flight controller is used to realize full-speed flight control of the twin-wing vertical take-off and landing UAV.

2. The global flight control method for a twin-wing vertical take-off and landing UAV according to claim 1, characterized in that: The TS fuzzy model of the twin-wing vertical take-off and landing UAV facing external disturbances is constructed according to the following steps: Construct the dynamic motion equations of a twin-wing vertical take-off and landing UAV facing external disturbances: In the above formula, U and w are the forward and vertical velocity components of the UAV body axis respectively; θ is the pitch angle; q is the pitch angle rate; F aero,x 、F d,x are respectively the aerodynamic force component and the disturbance force component of the body in the ox axis direction; F aero,z 、F d,z are respectively the aerodynamic force component and the disturbance force component of the body in the oz-axis direction; M aero,y 、M d M is the pitching moment and disturbance moment of the aircraft in the oy-axis direction; T Represents the pitching moment generated by propeller thrust; I yy represents the longitudinal moment of inertia of the drone along the body axis, m and g are the total mass and gravity acceleration of the drone respectively; x E 、z E represents the horizontal forward and vertical upward displacement of the aircraft after the earth coordinate system is rotated to the same direction as the forward axis of the aircraft body; F T The thrust generated by the propeller; Represent U, w, θ, q, x respectively E 、z E rate of change; The dynamic equation of motion is rewritten as the following first equation: In the above formula, x=[θ,u,w,q,h], Indicates the shift amount of x, which is used to achieve tracking purposes; x * represents the expected state of x; h is the flight altitude; d represents the external disturbance; u is the control quantity; A, B, and D are all state space matrices; express rate of change; Introduce a nonlinear feedforward controller u into the first equation ff And through simulation calculation method, the full speed range flight data table is constructed to make the equation Ax * +Bu ff = 0, the propeller thrust and pitching moment generated by the propeller thrust in the full-speed flight data table are used as control outputs, and the pitch angle, forward speed, and vertical speed in the full-speed flight data table are used as state quantities; Introducing u ff Then, rewrite the first equation into the second equation Then according to the equation Ax * +Bu ff =0Rewrite the second equation as And perform fuzzy expansion on the B matrix to obtain the following TS fuzzy model: In the above formula, B i is the i-th fuzzy matrix; h i For B i The weight function of ; i∈{1,2,...,N}, N represents the total number of elements in the fuzzy set.

3. The global flight control method for a dual-wing vertical take-off and landing UAV according to claim 2, characterized in that: Design the flight controller according to the following steps: Define the error signal e as The matrix C is Adding integration to the TS fuzzy model to eliminate the steady-state error, we get the fuzzy representation of the TS fuzzy model and the error signal: In the above formula, the subscript L represents the corresponding parameter representation generated by fuzzy logic after the fuzzy system adds the integral; express rate of change; Based on the TS fuzzy model and the fuzzy representation of the error signal, the following flight controller u is designed. During flight control, the error signal e is made to converge to zero over time through the flight controller u to achieve error tracking: In the above formula, u b 、u ff are state feedback controller and nonlinear feedforward controller respectively; K Li To control the gain.

4. The global flight control method for a dual-wing vertical take-off and landing UAV according to claim 2 or 3, characterized in that: The full-speed range flight data table includes flight data of the UAV in different flight states, where the flight state includes at least one of climbing, level flight, level flight acceleration, and level flight deceleration.

5. The global flight control system of the twin-wing vertical take-off and landing UAV is characterized by: The global flight control system includes: The UAV mathematical model construction module is used to construct the TS fuzzy model of a twin-wing vertical take-off and landing UAV under external disturbances; A flight controller design module, used to design a flight controller based on the TS fuzzy model, wherein the flight controller includes a state feedback controller and a nonlinear feedforward controller; The flight control module is used to realize full-speed flight control of the twin-wing vertical take-off and landing UAV using a flight controller.

6. The global flight control system for a dual-wing vertical take-off and landing UAV according to claim 5, characterized in that: The UAV mathematical model construction module is used to construct a TS fuzzy model of a twin-wing vertical take-off and landing UAV facing external disturbances according to the following steps: Construct the dynamic motion equations of a twin-wing vertical take-off and landing UAV facing external disturbances: In the above formula, U and w are the forward and vertical velocity components of the UAV body axis respectively; θ is the pitch angle; q is the pitch angle rate; F aero,x 、F d,x are respectively the aerodynamic force component and the disturbance force component of the body in the ox axis direction; F aero,z 、F d,z are respectively the aerodynamic force component and the disturbance force component of the body in the oz-axis direction; M aero,y 、M d M is the pitching moment and disturbance moment of the aircraft in the oy-axis direction; T Represents the pitching moment generated by propeller thrust; I yy represents the longitudinal moment of inertia of the drone along the body axis, m and g are the total mass and gravity acceleration of the drone respectively; x E 、z E represents the horizontal forward and vertical upward displacement of the aircraft after the earth coordinate system is rotated to the same direction as the forward axis of the aircraft body; F T The thrust generated by the propeller; Represent U, w, θ, q, x respectively E 、z E rate of change; Rewrite the dynamic equation of motion as the first equation below: In the above formula, x=[θ,u,w,q,h], represents the displacement of x, which is used to achieve tracking purposes; x* represents the desired state of x; h is the flight altitude; d represents the external disturbance; u is the control variable; A, B, and D are all state space matrices; express rate of change; Introduce a nonlinear feedforward controller u into the first equation ff And through simulation calculation method, the full speed range flight data table is constructed to make the equation Ax * +Bu ff = 0, the propeller thrust and pitching moment generated by the propeller thrust in the full-speed flight data table are used as control outputs, and the pitch angle, forward speed, and vertical speed in the full-speed flight data table are used as state quantities; Introducing u ff Then, rewrite the first equation into the second equation Then according to the equation Ax * +Bu ff =0Rewrite the second equation as And perform fuzzy expansion on the B matrix to obtain the following TS fuzzy model: In the above formula, B i is the i-th fuzzy matrix; h i For B i The weight function of ; i∈{1,2,…,N}, N represents the total number of elements in the fuzzy set.

7. The global flight control system for a dual-wing vertical take-off and landing UAV according to claim 6, characterized in that: The flight controller design module designs the flight controller by the following steps: Define the error signal e as The matrix C is Adding integration to the TS fuzzy model to eliminate the steady-state error, we get the fuzzy representation of the TS fuzzy model and the error signal: In the above formula, the subscript L represents the corresponding parameter representation generated by fuzzy logic after the fuzzy system adds the integral; express rate of change; Based on the TS fuzzy model and the fuzzy representation of the error signal, the following flight controller u is designed. During flight control, the error signal e is made to converge to zero over time through the flight controller u to achieve error tracking: In the above formula, u b 、u ff are state feedback controller and nonlinear feedforward controller respectively; K Li To control the gain.

8. The global flight control system for a dual-wing vertical take-off and landing UAV according to claim 6 or 7, characterized in that: The full-speed range flight data table includes flight data of the UAV in different flight states, where the flight state includes at least one of climbing, level flight, level flight acceleration, and level flight deceleration.

9. A global flight control device for a twin-wing vertical take-off and landing UAV, characterized by: The global flight control device includes a memory and a processor; the memory is used to store computer program code and transmit the computer program code to the processor; the processor is used to execute the global flight control method as described in claims 1-4 according to instructions in the computer program code.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the global flight control method according to claims 1-4 is implemented.

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