A multi-mode adaptive switching control method and system for composite wing unmanned aerial vehicle

Abstract

The present invention discloses a multi-mode adaptive switching control method and system for a composite wing unmanned aerial vehicle. The method comprises: constructing a controller based on a flight dynamics model by using a frame inversion method; the controller is used to output a frame virtual control torque; constructing a control allocation model based on the controller; iteratively solving the control allocation model to obtain a frame control output of an actuator; correcting the frame control output by using a deviation control matrix to obtain a corrected frame control output; under a set flight mode switching strategy, taking the sum of the control output output of the actuator at the previous moment and the corrected frame control output at the current moment as the control output output of the actuator at the current moment, thereby realizing control of the composite wing unmanned aerial vehicle at the current moment. The present invention can reduce costs while improving control stability.

Description

Technical Field

[0001] The present invention relates to the field of unmanned aerial vehicle flight attitude control, and in particular to a multi-mode adaptive switching control method and system for a composite wing unmanned aerial vehicle. Background Art

[0002] Unmanned aerial vehicle flight control is one of the main research topics of traditional aircraft control. It not only needs to ensure the flight quality of the aircraft during flight, but also needs to design a reasonable take-off and landing process. Due to the shortcomings of fixed-wing unmanned aerial vehicles, such as large requirements for take-off sites and equipment and short cruising time of rotary-wing unmanned aerial vehicles, control methods for new aircraft have also become the research focus of domestic and foreign designers. At present, with the expansion of urban convenience, the complexity of airspace, the miniaturization of unmanned aerial vehicle landing areas, the popularization of civilian unmanned aerial vehicles, and the non-professionalization of pilots, a set of highly robust composite-wing unmanned aerial vehicle attitude control systems has become extremely important.

[0003] The compound-wing UAV is different from the traditional single-mode UAV. It is an UAV that has the characteristics of both rotorcraft and fixed-wing UAVs. This enables it to have vertical take-off and landing capabilities while having a high cruising speed. It has a wide range of applications in aerial surveying, line inspection, reconnaissance, and express delivery. The compound-wing UAV has two different control mechanisms of rotorcraft and fixed-wing aircraft, and switches between the two modes through the action of the actuator. During the flight mode transition process of the compound-wing UAV: ​​(1) The aerodynamic characteristics are complex, the modeling is difficult, and the model accuracy is low, which requires the controller to have stronger robustness to the uncertainty of the model. (2) The control mechanism is redundant and needs to be allocated and reconstructed online. (3) The control mechanism and control methods are diverse, and the strategy needs to be analyzed.

[0004] At present, the control system stability of existing composite wing aircraft is relatively poor. Usually, the rotor and fixed wing are formed into two closed-loop systems to solve the stability problem during flight. This is not only expensive and unsuitable for the popularization of civil aircraft, but also greatly hinders the progress of large-scale composite wing unmanned aerial vehicles. Summary of the invention

[0005] Based on this, an embodiment of the present invention provides a multi-mode adaptive switching control method and system for a composite-wing unmanned aerial vehicle, so as to improve control stability while reducing costs.

[0006] To achieve the above object, the present invention provides the following solutions:

[0007] A multi-mode adaptive switching control method for a composite wing unmanned aerial vehicle, comprising:

[0008] Obtaining attitude data of composite wing unmanned aerial vehicle;

[0009] constructing a flight dynamics model based on the attitude data;

[0010] Based on the flight dynamics model, a controller is constructed by adopting a frame inversion method; the controller is used to output a frame virtual control torque;

[0011] Based on the controller, construct a control allocation model;

[0012] Iteratively solving the control allocation model to obtain the frame control output of the actuator;

[0013] Using a deviation control matrix to correct the frame control output to obtain a corrected frame control output;

[0014] Under the set flight mode switching strategy, the sum of the control output of the actuator at the previous moment and the corrected frame control output at the current moment is used as the control output of the actuator at the current moment to achieve control of the composite wing unmanned aerial vehicle at the current moment.

[0015] Optionally, the controller is:

[0016]

[0017] Among them, ΔM c represents the frame virtual control torque; J represents the inherent rigid body moment of inertia of the composite wing unmanned aerial vehicle; z 1 Indicates the difference between the attitude angle and the attitude angle command; z 2 Represents the difference between the attitude angular velocity and the virtual control function; k 2 Represents controller parameters; represents the derivative of the virtual control function; is the measured value of angular acceleration at the previous moment; g(ξ) represents the angle matrix function; ξ represents the attitude angle.

[0018] Optionally, the control allocation model is:

[0019]

[0020] Among them, ΔM c represents the frame virtual control torque; B * represents the modified control matrix; Δu' represents the frame control output, ΔM cdes represents the target frame control torque; W represents the parameter matrix; ε represents the adjustment parameter; ||W(ΔM cdes -B * Δu')|| p represents the p-norm of the error between the target frame control torque and the frame virtual control torque; ||Δu'|| pIt represents the p-norm of the frame control output, where p=2 is selected.

[0021] Optionally, the iteratively solving the control allocation model to obtain the frame control output of the actuator specifically includes:

[0022] Under the current number of iterations, the pseudo-inverse of the control allocation model is obtained to obtain the frame control output under the current number of iterations;

[0023] Scaling the frame control output at the current iteration number to obtain the scaled frame control output at the current iteration number;

[0024] Determine whether there is a saturation control item in the scaling frame control output under the current iteration number, and obtain a first determination result;

[0025] If the first judgment result is no, the iteration is stopped, and the sum of the scaled frame control outputs under all iteration times is taken as the final frame control output of the actuator;

[0026] If the first judgment result is yes, then judging whether the saturation control item meets the control requirement, and obtaining a second judgment result;

[0027] If the second judgment result is yes, the iteration is stopped, and the sum of the scaled frame control outputs under all iteration times is taken as the final frame control output of the actuator;

[0028] If the second judgment result is no, the next iteration is performed until the set maximum number of iterations is reached.

[0029] Optionally, the modified frame control output is:

[0030] Δu=Δu'+Δu scor ;

[0031] Wherein, Δu represents the corrected frame control output; Δu scor represents the scaled correction signal; is the constraint of the correction signal; S represents the scaling function; represents the deviation control matrix; Δu' represents the frame control output; B * represents the modified control matrix, express The null space of Indicates B * and The transposed matrix of the product between .

[0032] Optionally, the set flight mode switching strategy is a rotor acceleration strategy, a propeller acceleration strategy or a gravity acceleration strategy.

[0033] Optionally, the thruster acceleration strategy is specifically:

[0034] When the composite-wing unmanned aerial vehicle is in the stage of switching from rotor mode to cruise mode, the fuel thrust system is started to enable the composite-wing unmanned aerial vehicle to obtain forward flight acceleration, and the pneumatic rudder control system controls the composite-wing unmanned aerial vehicle to maintain the set pitch angle. When the composite-wing unmanned aerial vehicle accelerates to the required cruise speed, the rotor control system controls the rotor to stop working and fix the rotor at the minimum wind resistance position, and then enters the cruise mode, and the pneumatic rudder control system realizes attitude control of the composite-wing unmanned aerial vehicle;

[0035] When the composite-wing unmanned aerial vehicle is in the stage of switching from cruise mode to rotor mode, the fuel thrust system stops working, the pneumatic rudder control system and the rotor control system control the composite-wing unmanned aerial vehicle to the set maximum resistance position, and after the composite-wing unmanned aerial vehicle gradually decreases to the required speed of the rotor mode, it enters the rotor mode, and the rotor control system realizes attitude control of the composite-wing unmanned aerial vehicle.

[0036] The present invention also provides a multi-mode adaptive switching control system for a composite wing unmanned aerial vehicle, comprising:

[0037] An attitude data acquisition module is used to acquire attitude data of the composite wing unmanned aerial vehicle;

[0038] A dynamics model building module, used to build a flight dynamics model according to the attitude data;

[0039] A controller construction module is used to construct a controller based on the flight dynamics model using a frame inversion method; the controller is used to output a frame virtual control torque;

[0040] A control allocation model building module, used for building a control allocation model based on the frame inversion controller;

[0041] An iterative solution module, used for iteratively solving the control allocation model to obtain the frame control output of the actuator;

[0042] A control amount correction module, used to correct the frame control output amount by using a deviation control matrix to obtain a corrected frame control output amount;

[0043] The flight control module is used to set the flight mode switching strategy, take the sum of the control output of the actuator at the previous moment and the corrected frame control output at the current moment as the control output of the actuator at the current moment, so as to realize the control of the composite wing unmanned aerial vehicle at the current moment.

[0044] Compared with the prior art, the present invention has the following beneficial effects:

[0045] The embodiment of the present invention proposes a multi-mode adaptive switching control method and system for a composite wing unmanned aerial vehicle. Based on the flight dynamics model, a controller is constructed by using the frame inversion method; based on the controller, a control allocation model is constructed; the control allocation model is iteratively solved to obtain the frame control output of the actuator; the frame control output is corrected by using the deviation control matrix to obtain the corrected frame control output; under the setting of the flight mode switching strategy, the sum of the control output output of the actuator at the previous moment and the corrected frame control output at the current moment is used as the control output output of the actuator at the current moment, so as to realize the control of the composite wing unmanned aerial vehicle at the current moment. The controller of the present invention can reduce the control error; the control allocation is adopted to solve the problem of unstable attitude of the aircraft. Compared with the method of solving the stability problem during flight by forming two closed-loop systems with the rotor and the fixed wing, it can improve the control stability while reducing the cost. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0047] Figure 1 A schematic diagram of the structure of a composite wing unmanned aerial vehicle provided by an embodiment of the present invention;

[0048] Figure 2 A flowchart of a multi-mode adaptive switching control method for a composite wing unmanned aerial vehicle provided by an embodiment of the present invention;

[0049] Figure 3 A flow chart of a control allocation process provided by an embodiment of the present invention;

[0050] Figure 4 A control schematic diagram of a composite wing unmanned aerial vehicle provided by an embodiment of the present invention;

[0051] Figure 5 A schematic diagram of an aircraft switching strategy provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0052] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0053] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0054] The composite wing unmanned aerial vehicle involved in this embodiment mainly includes: a fuel thrust system, an aerodynamic rudder control system and a rotor control system. The fuel thrust system is a diesel engine driving a wooden propeller, which is installed at the front end of the wing perpendicular to the wing plane. In order to ensure the cruising time of the aircraft, a fuel engine is used as the source of cruise thrust. The aerodynamic rudder control system is similar to that of a conventional fixed-wing aircraft, and consists of an elevator located on the horizontal tail, ailerons located at the end of the wing, and a rudder located on the vertical tail. The rotor control system is similar to a conventional four-rotor system, which is symmetrically distributed in front and behind the wing along the geometric center of the aircraft, and is connected to the wing through a rigid component to provide lift during takeoff. The structural diagram of the composite wing unmanned aerial vehicle is shown in the figure. Figure 1 shown.

[0055] Figure 2 Flow chart of the multi-mode adaptive switching control method of the composite wing unmanned aerial vehicle provided by the embodiment of the present invention. Figure 2 , the control method of this embodiment includes:

[0056] Step 101: Acquire attitude data of the composite-wing UAV.

[0057] Step 102: construct a flight dynamics model based on the attitude data. The flight dynamics model is used to obtain a subsequent controller.

[0058] The flight dynamics model is:

[0059]

[0060]

[0061]

[0062]

[0063]

[0064] ω∈R 3 is the angular velocity vector; J is the rigid body moment of inertia inherent in the UAV, which can be measured by ground testing; F represents the aerodynamic force F in the body coordinate system air , rotor force F lift , gravity F g Thrust F push and interference force F d The resultant force of the aircraft; M represents the aerodynamic moment M in the body coordinate system a , the control torque M generated by the control surfacec and disturbance torque M d The resultant torque of the UAV is ω; since the center of gravity of the sample UAV coincides with the geometric center, the direction of the thrust resultant coincides with the direction of the body axis, so the torque generated by gravity and thrust can be considered small and can be ignored. ω represents the angular velocity vector, p, q and r represent the roll, pitch and yaw angular velocities respectively. v represents the velocity of the UAV in the body coordinate system; ξ=[φ θ ψ] T , ξ represents the attitude angle vector, φ, θ and ψ represent the roll, pitch and yaw angles respectively. B represents the control matrix of the UAV actuator; u c is the control output of the actuator of the composite wing unmanned aerial vehicle, including the control output of the aileron δ a , elevator control output δ e and the rudder control output δ r ; δ T Represents the control output of the thruster; ω 1 ,ω 2 ,ω 3 and ω 4 They correspond to the speed of each rotor in the four rotors. m represents the mass of the composite wing UAV; J xx represents the moment of inertia along the x-axis; J yy represents the moment of inertia along the y-axis; J zz represents the moment of inertia along the z axis; J xz represents the product of the moments of inertia between the x-axis and the z-axis; J zx represents the product of the moments of inertia along the z-axis and the x-axis; v x Indicates the flight speed of the drone along the x-axis; v y Indicates the flight speed of the drone along the y-axis; v z Indicates the flight speed of the drone along the z-axis; f x Indicates the force on the x-axis of the drone; f y Indicates the force on the y-axis of the drone; f z It represents the force on the z-axis of the drone; L represents the rolling moment of the drone; M represents the pitch moment of the drone; N represents the yaw moment of the drone; g(ξ) represents the angle matrix function.

[0065] Step 103: Based on the flight dynamics model, a controller is constructed using a frame inversion method. The controller is a flight attitude controller, which is used to output a frame virtual control torque.

[0066] This controller combines the advantages of data-driven control and model-based control by converting the controller into a frame format, enhancing the anti-interference and anti-uncertainty of the traditional model-based controller and reducing the controller's dependence on the model. To facilitate the analysis and design of the attitude controller, the internal and external loops of the attitude model are analyzed and simplified. In the model, x1 is the attitude angle; x 2 is the attitude angular velocity; is the derivative of the attitude angle; is the derivative of the attitude angular velocity; the control input is the virtual control torque M c ;f 1 (x 1 ) represents the angle loop control state matrix; g 1 (x 1 ) is the angle loop control efficiency matrix; f 2 (x 1 ,x 2 ) is the angular acceleration control state matrix; g 2 (x 1 ,x 2 ) is the torque control efficiency matrix.

[0067]

[0068] x 1 =ξ

[0069] x 2 =ω

[0070] f 1 (x 1 )=0

[0071] g 1 (x 1 )=g(ξ)

[0072] f 2 (x 1 ,x 2 )=J -1 (ω×Jω+M a )

[0073] g 2 (x 1 ,x 2 )=J -1

[0074] M c =Bu c

[0075] u c =(δ a δ e δ r δ T ω 1 ω 2 ω 3 ω 4 ) T

[0076] Where g(ξ) represents the angle matrix function, and the dynamic equation is expressed in frame form to design the controller. The attitude differential equation is in the following affine nonlinear form:

[0077]

[0078] If the attitude angle ξ tracks the target ξ r The error function can be expressed as:

[0079]

[0080] Where α is the virtual control function, z 1 Indicates attitude angle ξ and attitude angle command ξ r The difference between 2 It represents the difference between the attitude angular velocity and the virtual control function α, and then the error differential function is:

[0081]

[0082] In t 0 The standard first-order approximate Euler expansion expression of the attitude differential equation at the time point is:

[0083]

[0084] Among them, M a0 is the aerodynamic torque at the previous moment, M c0 is the magnitude of the moment at the previous moment, Λ is a negligible high-order quantity higher than the first order, Indicates partial division, the above formula can be further rewritten as:

[0085]

[0086] in:

[0087]

[0088]

[0089]

[0090] Therefore, when the controller update frequency is high, the control output and angular acceleration can be considered as fast time scale variables, and the angular velocity and fuselage torque can be considered as slow time scale variables. 0 The change rate of ω is much lower than The formula can be simplified to:

[0091]

[0092] error satisfy:

[0093]

[0094] According to the control quantity, it can be expressed as:

[0095] α=g -1 (ξ)(-k 1 z 1 +ξ r )

[0096] Then the controller (system frame virtual control torque input) is:

[0097]

[0098] Among them, ΔM c represents the frame virtual control torque; J represents the inherent rigid body moment of inertia of the composite wing unmanned aerial vehicle; k 1 and k 2 All represent controller parameters, which can be modified according to actual conditions. 1 and k 2 Can take any number greater than 0; represents the derivative of the virtual control function; is the measured value of angular acceleration at the previous moment.

[0099] Step 104: construct a control allocation model based on the controller.

[0100] Scaling is proposed mainly to solve the problem of large angle deviation of the control vector. By scaling, it is ensured that the solution can be searched near the control quantity generated by the pseudo-inverse method, so that the pseudo control achieved is as consistent as possible with the direction of the desired control. c =BΔu links the virtual control torque with the actual actuator control output, B is the actuator control matrix, and u is the actuator control output. Since there are three flight states with large differences in the UAV flight envelope, the control matrix B also changes from under-actuated to redundantly driven to under-actuated. It is impossible to use a constant matrix for solution, so the control allocation method is required to allocate the virtual control amount to the actuator. However, it also puts forward higher requirements on the control allocation algorithm, which must meet the performance indicators of under-actuated and redundantly driven, and also meet the rate and amplitude constraints of the control mechanism.

[0101] First, since some control items are invalid in certain states, the control items with low control efficiency in the control matrix are set to zero. Second, control inversion will bring about the problem that the dynamic inverse is unsolvable, so when the control inversion item is detected, the item will be set to zero. Assume that the corrected control matrix is ​​B * ,satisfy is the deviation control matrix.

[0102] Therefore, the torque error and the actuator variation are optimized as optimization targets, and the weighted minimum variance optimization model is obtained. The control allocation model is:

[0103]

[0104] Among them, ΔM c represents the frame virtual control torque; B * represents the modified control matrix; Δu' represents the frame control output, ΔM cdes represents the target frame control torque; W represents the parameter matrix; ε represents the adjustment parameter. The two parts of the optimization objective function are: ||W(ΔM cdes -B * Δu')|| p represents the error p norm between the target frame control torque and the frame virtual control torque, p can be 2, and this part is the optimization goal of making the control torque generated by the output signal close to the virtual control torque; ||Δu'|| p It represents the p-norm of the frame control output, where p can be 2. This part is the secondary optimization goal of minimizing the change in the actuator signal.

[0105] Here the controller is in frame form. Through analysis, it can be seen that the control allocation problem is actually the allocation problem of the frame control amount Δu when the control mechanism has rate and amplitude constraints. The constraints on the actuator input u are:

[0106]

[0107]

[0108]

[0109]

[0110] in, Indicates the constraints on the control output; Δt indicates the single-step update time of the control signal; represents an m-dimensional space; u 0 is the existing actuator control signal, Δu is the actual frame control output signal, and L is the objective function to be optimized. and They represent the upper and lower limits of the actuator change rate, respectively. and Δ u They represent the upper and lower limits of the control input amplitude of the single-step actuator respectively. The upper limit (lower limit) is the smaller (larger) value of the difference between the upper (lower limit) amplitude and the existing signal and the product of the upper (lower limit) change rate and the single-step time length.

[0111] Here, the scaling function of the actuator is introduced, The actuator constraint is When the control output signal Δm is scaled to the Δm obtained within the constraint range, * The scaling function of .

[0112] Step 105: Iteratively solve the control allocation model to obtain the frame control output of the actuator. Specifically:

[0113] First, let the control matrix, constraints and pseudo-inverse solution in the equation be B *1 , and Find the pseudo-inverse of the equation and get the control solution Δu '1 . Using the scaling function Δu '1 Scaling to the constraint range to obtain the updated actuator output Δu ”1 ,at this time If the solution satisfies the control constraints, the iteration step is exited. ”1 If one or more of the control variables are saturated, the target torque of the second iteration is Then, using the removal of B *1 and B obtained after the saturation column *2 and right Calculate the pseudo-inverse to obtain a new pseudo-inverse solution Δu ”2 , and then iterate step by step in a similar way to finally achieve target control.

[0114] When the following three situations occur, the iteration ends and the control allocation calculation is exited: (1) There is still no solution after reaching the maximum number of iterations. (2) The target control amount can be achieved after redistribution. (3) There is no saturated control amount after scaling. The first situation is to ensure that when the solution cannot meet the optimal goal, the computing resources and control update cycle are within the range required by the discrete controller. The latter two situations have met the expected control requirements. Within the range allowed by computing power, the more iterations, the better the effect achieved by the controller. The final control output signal is:

[0115]

[0116] Where n is the number of iterations.

[0117] From the above description, see Figure 3 , step 105 can be summarized as:

[0118] At the current number of iterations, the pseudo-inverse of the control allocation model is calculated to obtain the frame control output at the current number of iterations; the frame control output at the current number of iterations is scaled to obtain the scaled frame control output at the current number of iterations; it is determined whether there is a saturated control item in the scaled frame control output at the current number of iterations to obtain a first judgment result; if the first judgment result is no, the iteration is stopped, and the sum of the scaled frame control outputs at all iterations is used as the final frame control output of the actuator; if the first judgment result is yes, it is determined whether the saturated control item meets the control requirements to obtain a second judgment result; if the second judgment result is yes, the iteration is stopped, and the sum of the scaled frame control outputs at all iterations is used as the final frame control output of the actuator; if the second judgment result is no, the next iteration is performed until the set maximum number of iterations is reached.

[0119] Step 106: Use the deviation control matrix to correct the frame control output to obtain a corrected frame control output.

[0120] Since the above control signals are obtained by solving the modified control matrix, the actual control output is not equal to the expected virtual control torque. In order to ensure that the control distribution result satisfies the virtual control torque signal, it is necessary to use the deviation control matrix Correct the frame control output and add the correction signal Δu cor The post-control output should meet the following requirements:

[0121]

[0122] Will Constraints Inside the null space of a matrix:

[0123]

[0124] set up for The null space of the matrix, k is the function to be solved, then the correction signal Δu cor satisfy:

[0125]

[0126]

[0127] then

[0128]

[0129]

[0130] To ensure that the control output is within the constraints, Scaling gives:

[0131]

[0132]

[0133] The actual output control distribution signal, that is, the corrected frame control output is:

[0134] Δu=Δu'+Δu scor ;

[0135] Wherein, Δu represents the corrected frame control output; Δu cor Indicates the correction signal; Δu scor represents the scaled correction signal; is the constraint of the correction signal; S represents the scaling function; represents the deviation control matrix; Δu' represents the frame control output; B * represents the modified control matrix, express The null space of Indicates B * and The transposed matrix of the product between .

[0136] Step 107: Under the set flight mode switching strategy, the sum of the control output of the actuator at the previous moment and the corrected frame control output at the current moment is used as the control output of the actuator at the current moment to achieve control of the composite wing unmanned aerial vehicle at the current moment.

[0137] Let u 0 is the control output of the actuator at the previous moment, then the control output of the actuator at the current moment is: u = u 0 +Δu. The control principle diagram of the composite wing unmanned aerial vehicle of this embodiment is as follows Figure 4 shown.

[0138] The above steps 101-106 obtain the full envelope attitude controller of the composite wing unmanned aerial vehicle, but the transition of the composite wing unmanned aerial vehicle is a control process combining control and method, and it is necessary to pre-design an acceleration strategy and control mechanism action strategy for the transition phase. The controller designed in this embodiment can meet the setting of the flight mode switching strategy, and the flight mode switching strategy is set to a rotor acceleration strategy, a propeller acceleration strategy or a gravity acceleration strategy.

[0139] Rotor acceleration strategy: After the rotor accelerates to a fixed speed, it switches to cruise flight mode. The switching process will cause a large drop in altitude.

[0140] Thruster acceleration strategy: The horizontal attitude thrusters are accelerated to a specified speed and then the mode is changed. This transition method uses the quadrotor for attitude control and requires the pitch attitude angle of the transition process to be specified.

[0141] Gravity acceleration strategy: Utilize the acceleration component of the composite wing UAV’s own weight in the forward flight direction to fully accelerate the aircraft. This type of switching strategy requires sufficient experimental support for the value of the pitch attitude angle.

[0142] The above three strategies always have some shortcomings in practical applications, so this embodiment draws on the second transition method, modifies it on its basis and proposes a composite acceleration method. In the entire composite mode, the rotor and the aerodynamic rudder maintain the aircraft attitude at a predetermined attitude by adjusting the weight distribution, and the thrust engine can achieve the speed change of the aircraft by adjusting the throttle size. In the design of this embodiment, the composite mode cannot achieve the change of the aircraft attitude, and only exists as a variable speed flight mode during the flight process. Adding a restricted composite mode not only meets the switching requirements of the aircraft between the two modes, but also controls the distribution to achieve the optimization of the distribution target. The transition process is a flight trajectory that flies forward at a fixed speed in a predetermined direction after taking off along a vertical path, which ensures that the trajectory of the aircraft is knowable during the transition process, reducing the flight risk brought to the composite wing unmanned aerial vehicle due to the incomplete knowability of the aircraft's own flight trajectory. Therefore, see Figure 5 The improved thruster acceleration strategy of this embodiment is specifically as follows:

[0143] When the composite wing unmanned aerial vehicle is in the stage of switching from rotor mode to cruise mode, the rotor is in a rotating state at the beginning to provide lift for the aircraft. When switching, the fuel thrust system is first started to enable the composite wing unmanned aerial vehicle to obtain forward flight acceleration, and the composite wing unmanned aerial vehicle maintains the set pitch angle by changing the rotor speed and speed difference combined with the pneumatic rudder control system by changing the deflection angle. When the composite wing unmanned aerial vehicle accelerates to the required cruise speed, the rotor control system controls the rotor to stop working and fixes the rotor at the minimum wind resistance position, and then enters the cruise mode, and the pneumatic rudder control system realizes the attitude control of the composite wing unmanned aerial vehicle.

[0144] When the composite-wing unmanned aerial vehicle is in the stage of switching from cruise mode to rotor mode, the fuel thrust system stops working, the pneumatic rudder control system and the rotor control system control the composite-wing unmanned aerial vehicle to the set maximum resistance position, and after the composite-wing unmanned aerial vehicle gradually decreases to the required speed of the rotor mode, it enters the rotor mode, and the rotor control system realizes attitude control of the composite-wing unmanned aerial vehicle.

[0145] The multi-mode adaptive switching control method for a composite wing unmanned aerial vehicle of this embodiment has the following advantages: (1) The present invention adopts a frame control method and combines the flight attitude information of the IMU to reduce the aerodynamic interference caused by the additional configuration in the rotor mode, transition mode and cruise mode of the aircraft, as well as the modeling error of the actuator and the influence of model uncertainty. (2) The present invention solves the problem of unstable aircraft attitude during the transition process caused by large changes in model state and drastic changes in the control matrix during the transition process of the aircraft by controlling the distribution. (3) The present invention designs a mode change transition strategy with smaller trajectory changes, which reduces the difficulties brought by the unknown trajectory of the aircraft to aircraft control and trajectory planning.

[0146] The present invention also provides a multi-mode adaptive switching control system for a composite wing unmanned aerial vehicle, comprising:

[0147] The attitude data acquisition module is used to acquire the attitude data of the composite wing unmanned aerial vehicle.

[0148] The dynamics model building module is used to build a flight dynamics model according to the attitude data.

[0149] A controller construction module is used to construct a controller based on the flight dynamics model using a frame inversion method; the controller is used to output a frame virtual control torque.

[0150] The control allocation model building module is used to build a control allocation model based on the controller.

[0151] The iterative solution module is used to iteratively solve the control allocation model to obtain the frame control output of the actuator.

[0152] The control amount correction module is used to correct the frame control output amount by using a deviation control matrix to obtain a corrected frame control output amount.

[0153] The flight control module is used to set the flight mode switching strategy, take the sum of the control output of the actuator at the previous moment and the corrected frame control output at the current moment as the control output of the actuator at the current moment, so as to realize the control of the composite wing unmanned aerial vehicle at the current moment.

[0154] In this specification, each embodiment is described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the embodiments can be referred to each other. For the system disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referred to the method part.

[0155] The principles and implementation methods of the present invention are described in this article using specific examples. The description of the above embodiments is only used to help understand the method and core idea of ​​the present invention. At the same time, for those skilled in the art, according to the idea of ​​the present invention, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting the present invention.

Claims

1. A multi-mode adaptive switching control method for a composite wing unmanned aerial vehicle, characterized in that: include: Obtaining attitude data of composite wing unmanned aerial vehicle; constructing a flight dynamics model based on the attitude data; Based on the flight dynamics model, a controller is constructed using a frame inversion method; The controller is used to output a frame virtual control torque; Based on the controller, construct a control allocation model; Iteratively solving the control allocation model to obtain the frame control output of the actuator; Using a deviation control matrix to correct the frame control output to obtain a corrected frame control output; Under the set flight mode switching strategy, the sum of the control output of the actuator at the previous moment and the corrected frame control output at the current moment is used as the control output of the actuator at the current moment, so as to realize the control of the composite wing unmanned aerial vehicle at the current moment; The flight dynamics model is: M c =This c you c =(δ a d e d r d T (ω1ω2ω3ω4) T ; ω∈R 3 is the angular velocity vector; J is the rigid body moment of inertia inherent in the UAV, measured by ground testing; F represents the aerodynamic force F in the body coordinate system air , rotor force F lift , gravity F g Thrust F push and interference force F d The resultant force of the aircraft; M represents the aerodynamic moment M in the body coordinate system a , the control torque M generated by the control surface c and disturbance torque M d The resultant torque of the UAV is: ω represents the angular velocity vector, p, q and r represent the roll, pitch and yaw angular velocities respectively; v represents the velocity in the UAV body coordinate system; ξ=[φ θ ψ] T , ξ represents the attitude angle vector, φ, θ and ψ represent the roll, pitch and yaw angles respectively; B represents the control matrix of the UAV actuator; u c is the control output of the actuator of the composite wing unmanned aerial vehicle, including the control output of the aileron δ a , elevator control output δ e and the rudder control output δ r ; δ T represents the control output of the thruster; ω1, ω2, ω3 and ω4 respectively represent the individual rotation speed of each of the four rotors; m represents the mass of the composite wing UAV; J xx represents the moment of inertia along the x-axis; J yy represents the moment of inertia along the y-axis; J zz represents the moment of inertia along the z axis; J xz represents the product of the moments of inertia between the x-axis and the z-axis; J zx represents the product of the moments of inertia along the z-axis and the x-axis; v x Indicates the flight speed of the drone along the x-axis; v y Indicates the flight speed of the drone along the y-axis; v z Indicates the flight speed of the drone along the z-axis; f x Indicates the force on the x-axis of the drone; f y Indicates the force on the y-axis of the drone; f z Indicates the force on the z-axis of the drone; L indicates the rolling moment of the drone; M indicates the pitch moment of the drone; N indicates the yaw moment of the drone; g(ξ) indicates the angle matrix function; The controller is: Among them, ΔM c represents the frame virtual control torque; z1 represents the difference between the attitude angle and the attitude angle command; z2 represents the difference between the attitude angular velocity and the virtual control function; k2 represents the controller parameter; represents the derivative of the virtual control function; is the measured value of angular acceleration at the previous moment; ξ represents the attitude angle; The control allocation model is: Among them, B * represents the modified control matrix; Δu' represents the frame control output, ΔM cdes represents the target frame control torque; W represents the parameter matrix; ε represents the adjustment parameter; ||W(ΔM cdes -B * Δu')|| p represents the p-norm of the error between the target frame control torque and the frame virtual control torque; ||Δu'|| p represents the p-norm of the frame control output; The modified frame control output is: Δu=Δu'+Δu scor ; Wherein, Δu represents the corrected frame control output; Δu scor represents the scaled correction signal; is the constraint of the correction signal; S represents the scaling function; represents the deviation control matrix; express The null space of Indicates B * and The transposed matrix of the product between .

2. The multi-mode adaptive switching control method for a composite wing unmanned aerial vehicle according to claim 1 is characterized in that: The iterative solution of the control allocation model to obtain the frame control output of the actuator specifically includes: Under the current number of iterations, the pseudo-inverse of the control allocation model is obtained to obtain the frame control output under the current number of iterations; Scaling the frame control output at the current iteration number to obtain the scaled frame control output at the current iteration number; Determine whether there is a saturation control item in the scaling frame control output under the current iteration number, and obtain a first determination result; If the first judgment result is no, the iteration is stopped, and the sum of the scaled frame control outputs under all iteration times is taken as the final frame control output of the actuator; If the first judgment result is yes, then judging whether the saturation control item meets the control requirement, and obtaining a second judgment result; If the second judgment result is yes, the iteration is stopped, and the sum of the scaled frame control outputs under all iteration times is taken as the final frame control output of the actuator; If the second judgment result is no, the next iteration is performed until the set maximum number of iterations is reached.

3. The multi-mode adaptive switching control method for a composite-wing unmanned aerial vehicle according to claim 1, characterized in that: The flight mode switching strategy is set to be a rotor acceleration strategy, a propeller acceleration strategy or a gravity acceleration strategy.

4. The multi-mode adaptive switching control method for a composite wing unmanned aerial vehicle according to claim 3 is characterized in that: The thruster acceleration strategy is specifically: When the composite-wing unmanned aerial vehicle is in the stage of switching from rotor mode to cruise mode, the fuel thrust system is started to enable the composite-wing unmanned aerial vehicle to obtain forward flight acceleration, and the pneumatic rudder control system controls the composite-wing unmanned aerial vehicle to maintain the set pitch angle. When the composite-wing unmanned aerial vehicle accelerates to the required cruise speed, the rotor control system controls the rotor to stop working and fix the rotor at the minimum wind resistance position, and then enters the cruise mode, and the pneumatic rudder control system realizes attitude control of the composite-wing unmanned aerial vehicle; When the composite-wing unmanned aerial vehicle is in the stage of switching from cruise mode to rotor mode, the fuel thrust system stops working, the pneumatic rudder control system and the rotor control system control the composite-wing unmanned aerial vehicle to the set maximum resistance position, and after the composite-wing unmanned aerial vehicle gradually decreases to the required speed of the rotor mode, it enters the rotor mode, and the rotor control system realizes attitude control of the composite-wing unmanned aerial vehicle.

5. A multi-mode adaptive switching control system for a composite wing unmanned aerial vehicle, characterized in that: The multi-modal adaptive switching control system of the composite wing unmanned aerial vehicle is used to implement the multi-modal adaptive switching control method of the composite wing unmanned aerial vehicle according to any one of claims 1 to 4, and the multi-modal adaptive switching control system of the composite wing unmanned aerial vehicle comprises: An attitude data acquisition module is used to acquire attitude data of the composite wing unmanned aerial vehicle; A dynamics model building module, used to build a flight dynamics model according to the attitude data; A controller construction module, used to construct a controller based on the flight dynamics model using a frame inversion method; the controller is used to output a frame virtual control torque; A control allocation model building module, used to build a control allocation model based on the controller; An iterative solution module, used for iteratively solving the control allocation model to obtain the frame control output of the actuator; A control amount correction module, used to correct the frame control output amount by using a deviation control matrix to obtain a corrected frame control output amount; The flight control module is used to set the flight mode switching strategy, take the sum of the control output of the actuator at the previous moment and the corrected frame control output at the current moment as the control output of the actuator at the current moment, so as to realize the control of the composite wing unmanned aerial vehicle at the current moment.

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