Control method suitable for tilting wing logistics unmanned aerial vehicle

Abstract

The invention discloses a control method suitable for a tilting-wing logistics unmanned aerial vehicle, and the method comprises the steps: S1) supposing that a controlled tilting-power logistics unmanned aerial vehicle has a power tilting angle, a rotor wing is controllable, and a control surface is controllable, and building a dynamic model of the tilting-rotor unmanned aerial vehicle; s2) selecting a controlled quantity; s3) setting a kinetic equation according to the controlled variable and the kinetic model, and performing Taylor expansion on the kinetic equation at a certain state reference point; s4) calculating the increment of the control quantity through the position acceleration, the attitude angular acceleration and feedback; according to the control method suitable for the tilting-wing logistics unmanned aerial vehicle, a unified control idea is provided, and the key control problem of the tilting-wing logistics unmanned aerial vehicle in multi-mode switching is effectively solved through local linearization and real-time increment feedback.

Description

TECHNICAL FIELD

[0001] The present application belongs to the field of unmanned aerial vehicle control, and particularly relates to a control method suitable for a tilt-wing logistics unmanned aerial vehicle. BACKGROUND

[0002] The tilt-wing logistics unmanned aerial vehicle combines the vertical take-off and landing capability of a multi-rotor and the high-speed cruising advantage of a fixed-wing, and is suitable for logistics transportation of medium and long distances and high timeliness, but the multi-modal flight characteristics (vertical take-off and landing, transition conversion, fixed-wing cruising) bring complex control challenges.

[0003] Traditional mode-based control will cause stability problems, power distribution conflicts and efficiency losses during switching, and it is difficult to dynamically coordinate the rotor thrust and rudder deflection, cannot guarantee smooth transition, stable energy consumption and robustness, and is prone to safety problems of logistics tasks.

[0004] Therefore, the above problems need to be solved. SUMMARY

[0005] The purpose of the present application is to overcome the above shortcomings, and the purpose of the present application is to provide a control method suitable for a tilt-wing logistics unmanned aerial vehicle, and a unified control idea is proposed, which effectively solves the key control problems of the tilt-wing logistics unmanned aerial vehicle in multi-modal switching through local linearization and real-time incremental feedback.

[0006] Technical scheme: In order to achieve the above purpose, the present application provides a control method suitable for a tilt-wing logistics unmanned aerial vehicle, comprising:

[0007] S1) : assuming that the controlled tilt power logistics unmanned aerial vehicle has a power tilt angle, a rotor controllable and a rudder controllable, and establishing a dynamics model of the tilt rotor unmanned aerial vehicle;

[0008] S2) : selecting x = [u, w, p, q, r] T as the controlled variable, wherein u is the forward speed in the body coordinate system, w is the vertical speed in the body coordinate system, p, q and r are roll, pitch and yaw angular velocities respectively; it is equivalent to controlling the angular acceleration of three axes and the acceleration of the forward and vertical directions at the same time, while ensuring that the pitch attitude of the aircraft is fixed and unchanged; improve the flight experience, and fully utilize the advantages of multiple actuators;

[0009] S3) : setting a dynamics equation according to the controlled variable and the dynamics model, and performing Taylor expansion on the dynamics equation at a certain state reference point (x0, u0), and ignoring the last term of the Taylor expansion as a small perturbation, thereby simplifying the Taylor expansion of the certain state reference point (x0, u0) ; due to the high sampling frequency, the last term of the Taylor expansion is ignored as a small perturbation, and its value is approximately 0, which is omitted and not considered, thereby simplifying the Taylor expansion;

[0010] S4):Through position acceleration and attitude angle acceleration and feedback, the increment of control quantity is calculated;

[0011] S401):Set the second order reference model;

[0012] S402):Set the forward speed in the body coordinate system as u, the forward speed command as u cmd , the feedback signal as u back , the forward speed command u cmd , the reference speed u ref obtained through the second order reference model, and the feedforward of the reference speed; The ideal command and its derivative generated by the reference model can compensate the system dynamics and greatly improve the tracking speed;

[0013] S403):According to the reference speed and the feedback signal, the speed error can be calculated, and the speed deviation is added to the feedforward of the second order reference model through PI control, so that the forward acceleration can be obtained; the tilt unmanned aerial vehicle adopts the second order reference model to filter or shape the speed command, which is mainly based on the second order characteristics of its kinematics and dynamics, can naturally match the acceleration dynamic process, and ensure that the command is smooth and physically feasible;

[0014] S404):Replace the forward speed in S401-S403 with the speed and angular velocity of each position of the position and attitude, and calculate the position and attitude acceleration and angular acceleration of each position, denoted as A ctrl , and subtract the feedback of the acceleration and angular acceleration A back , that is, the acceleration error △A=A ctrl -A back ;

[0015] S5):Calculate the total control quantity.

[0016] Further, the dynamics model in S1 is specifically as follows:

[0017]

[0018] Wherein, u is the forward speed in the body coordinate system, w is the vertical speed in the body coordinate system, p, q and r are roll, pitch and yaw angular velocities, g is the acceleration of gravity, m is the mass, θ and φ are pitch and roll angles, I xx , I yy , I zz , I zx and I xz are the moments of inertia along different axes, F x , F zL, M and N are the forces in the X, Z body axes, roll moment, pitch moment, and yaw moment, respectively. By introducing the parameters of forward speed, vertical speed, roll angular speed, pitch angular speed, and yaw angular speed, the motion state of the aircraft in three-dimensional space, including translation and rotation, can be comprehensively described, and the dynamic behavior of the aircraft in a complex flight environment can be accurately reflected.

[0019] Further, the dynamics equation set in S3) according to the controlled variable is as follows:

[0020]

[0021] wherein u k is the control input, and x is the controlled variable. By dynamically coordinating the rotor thrust and the rudder deflection through a single control framework, seamless switching and stable control of the full flight envelope (including vertical take-off and landing, transition conversion, and fixed-wing cruising) are achieved.

[0022] Further, the Taylor expansion of the dynamics equation at a certain state reference point (x0, u0) is as follows:

[0023]

[0024] Let Since the higher the sampling frequency, the smaller the value, this term is ignored as a small perturbation term when designing the controller, and the simplified Taylor expansion is as follows:

[0025]

[0026] Set the control efficiency matrix ΔU = (u-u0), and the model after ignoring the above small perturbation term due to high sampling frequency is as follows:

[0027] That is,

[0028] Therefore, the increment of the control variable can be calculated through the position acceleration and the attitude angle acceleration and the feedback.

[0029] Further, the second-order reference model set in S401 is as follows:

[0030]

[0031] wherein s is the Laplace operator, ζ is the damping ratio, and ω cThe frequency is. Compared with the first-order model, the second-order reference model avoids acceleration mutation, improves control stability, and compared with the third-order model, while ensuring response speed, reduces system complexity, avoids high-frequency oscillation or actuator saturation risk, and further, the second-order model can better cooperate with the underlying attitude control, optimize the dynamic performance of the tilting mechanism in mode switching, thereby enhancing the robustness and control accuracy of the overall system.

[0032] Further, the calculation process of the forward acceleration in S403 is as follows:

[0033] According to the reference speed u ref and the feedback signal u back , the speed error e=u ref -u back is calculated, and the deviation of the speed is added to the feedforward of the second-order reference model through PI control, so that the forward acceleration A x is obtained, and the formula is as follows:

[0034]

[0035] Wherein, k p , k I and are proportional gain, integral gain and feedforward generated by the second-order reference model instruction respectively.

[0036] Further, the total control amount calculated in S5 includes:

[0037] S501):Calculate the increment of the control amount, and the formula is as follows:

[0038] △U=B -1 △A

[0039] Wherein, △U is the increment of the control amount; the inverse matrix is used to realize the collaborative optimization of multiple actuators (rotor tilting, speed regulation and rudder deflection), so as to ensure the reliability and efficient operation of the power redundant system;

[0040] S502):Calculate the total amount of the control amount, and the formula is as follows:

[0041] U=U0+△U

[0042] Wherein, U is the total amount of the control amount, U0 is the basic control amount, that is, U0 is the default control input when there is no additional adjustment demand.

[0043] The above technical scheme can be seen that the present application has the following beneficial effects:

[0044] 1. The control method for the tilt-wing logistics unmanned aerial vehicle, adopts local linearization technology, simplifies the nonlinear dynamic model near the state point, and combines with the incremental feedback control, calculates the control increment based on the real-time acceleration and angular acceleration error, so that the dynamic response ability of the system is improved and the actuator distribution is optimized.

[0045] 2. The control method for the tilt-wing logistics unmanned aerial vehicle, generates ideal instructions and their derivatives through a second-order reference model, effectively compensates for system dynamic delay, and improves tracking accuracy and disturbance rejection capability. BRIEF DESCRIPTION OF DRAWINGS

[0046] Figure 1 A tilt unmanned aerial vehicle in the control method for the tilt-wing logistics unmanned aerial vehicle;

[0047] Figure 2 A r-order reference model block diagram. DETAILED DESCRIPTION

[0048] The embodiments of the present application will be described in detail below, examples of which are shown in the accompanying drawings, wherein the same or similar reference signs represent the same or similar elements or elements having the same or similar functions throughout. The embodiments described below by referring to the accompanying drawings are exemplary and are intended to explain the present application, and cannot be understood as a limitation of the present application.

[0049] EMBODIMENT

[0050] In this embodiment, as Figure 1 The control method for the tilt-wing logistics unmanned aerial vehicle is disclosed, comprising:

[0051] S1): Assuming that the controlled tilt power logistics unmanned aerial vehicle has a power tilt angle, a controllable rotor and a controllable rudder surface, and establishing a dynamic model of the tilt rotor unmanned aerial vehicle;

[0052] S2): Select x=[u,w,p,q,r] T as the controlled variable, wherein u is the forward speed in the body coordinate system, w is the vertical speed in the body coordinate system, p, q and r are roll, pitch and yaw angular velocities respectively;

[0053] S3): According to the controlled variable and the dynamic model, the dynamic equation is set, and the Taylor expansion is carried out at a certain state reference point (x0, u0), and the last term of the Taylor expansion is ignored as a small disturbance term, so as to simplify the Taylor expansion of the certain state reference point (x0, u0);

[0054] S4): Calculate the increment of the control variable through position acceleration and attitude angular acceleration and feedback.

[0055] S401):Set the second order reference model;

[0056] S402):Set the forward velocity in the body coordinate system as u, the forward velocity command as u cmd , the feedback signal as u back , the forward velocity command u cmd , the reference velocity u ref and the feedforward of the reference velocity through the second order reference model;

[0057] S403):The error of the velocity can be calculated according to the reference velocity and the feedback signal, and the deviation of the velocity is added to the feedforward of the second order reference model through PI control, so that the forward acceleration can be obtained;

[0058] S404):The forward velocity in S401-S403 is replaced by the velocity and angular velocity of each position of the position and attitude, and the acceleration and angular acceleration of each position of the position and attitude are calculated, denoted as A ctrl , and the difference between the acceleration and angular acceleration feedback A back is obtained, i.e. the acceleration error ΔA=A ctrl -A back ;

[0059] S5):Calculate the total control amount.

[0060] Specifically, in S1, the real-time state data of the unmanned aerial vehicle is collected by sensors (such as accelerometers, gyroscopes, GPS, etc.), including position, velocity, attitude angle, angular velocity, etc., and the collected data is transmitted to the controller.

[0061] Specifically, in S404, the forward velocity can be controlled by controlling the force, and the size of the force is equal to the acceleration multiplied by the mass, so the acceleration error can be controlled by controlling the acceleration error.

[0062] Specifically, in S5, the total control amount is calculated, and the speed change command of the rotor and the deflection angle command of the rudder surface are generated, and the control commands are sent to the actuators (such as motors, rudders, etc.) to realize control.

[0063] In this embodiment, the dynamic model in S1 is as follows:

[0064]

[0065] Wherein, u is the forward velocity in the body coordinate system, w is the vertical velocity in the body coordinate system, p, q and r are the roll, pitch and yaw angular velocities, g is the gravitational acceleration, m is the mass, θ and φ are the pitch and roll angles, I xx , I yy , I zz, I zx and I xz I x , F z , L, M and N are force in X direction of body axis system, force in Z direction of body axis system, roll moment, pitch moment, yaw moment, respectively.

[0066] Specifically, the IMU and GPS modules installed on the unmanned aerial vehicle are used to measure the speed, angular velocity and attitude angle, to feed back the state of the aerial vehicle in real time, and to adjust the control input according to the feedback error.

[0067] In this embodiment, the dynamics equation set in S3) according to the controlled variable is specifically as follows:

[0068]

[0069] wherein u k is the control input, and x is the controlled variable.

[0070] Specifically, the dynamics model described in S1 is simplified here for subsequent derivation.

[0071] In this embodiment, the Taylor expansion of the dynamics equation at a certain state reference point (x0, u0) is specifically as follows:

[0072]

[0073] Let This term is ignored as a small perturbation term, and the simplified Taylor expansion is as follows:

[0074]

[0075] The control efficiency matrix is set as △U = (u-u0), and the model after ignoring the above small perturbation term because of high sampling frequency is as follows:

[0076] That is,

[0077] Specifically, by Taylor expanding the dynamics equation at a certain state reference point (x0, u0) and ignoring the small perturbation term, the Such a linearized model provides a basis for subsequent introduction of a second-order reference model.

[0078] In this embodiment, the second-order reference model set in S401 is as follows:

[0079]

[0080] wherein s is the Laplace operator, ζ is the damping ratio, and ωc is the frequency.

[0081] Specifically, the reference model is as shown in the figure, wherein y Figure 2 is the command control instruction, r is the order of the reference model, k is a coefficient ensuring that the generated reference trajectory is within the capability range of the aircraft, y cmd is a reference instruction generated according to the reference model; the present application selects a second-order reference model, and therefore r is set to 2. ref is the frequency.

[0082] In the embodiment, the calculation process of the forward acceleration in S403 is as follows:

[0083] According to the reference speed u ref and the feedback signal u back , the speed error e = u ref -u back is calculated; the deviation of the speed is subjected to PI control and the feedforward of the second-order reference model, so that the forward acceleration A x is obtained, and the formula is as follows:

[0084]

[0085] wherein k p , k I and k are proportional gain, integral gain and feedforward of the instruction generated by the second-order reference model respectively.

[0086] Specifically, the feedback signal u back is obtained by the IMU installed on the unmanned aerial vehicle.

[0087] In the embodiment, the total control amount calculated in S5 includes:

[0088] S501): the increment of the control amount is calculated, and the formula is as follows:

[0089] ΔU = B -1 ΔA

[0090] wherein ΔU is the increment of the control amount.

[0091] S502): the total amount of the control amount is calculated, and the formula is as follows:

[0092] U = U0 + ΔU

[0093] wherein U is the total amount of the control amount, and U0 is the basic control amount.

[0094] Specifically, in the present application, U0 is the control input preset according to the flight plan and the initial flight condition.

[0095] The above merely describes the preferred embodiments of the present application, and it should be pointed out that those skilled in the art can make several improvements without departing from the principles of the present application, and these improvements should also be considered as the protection scope of the present application.

Claims

1. A control method for a tilt-wing logistics UAV, characterized by: include: S1): Assume that the controlled tilt-rotor powered logistics UAV has a powered tilt angle, controllable rotors, and controllable rudders, and establish a dynamic model of the tilt-rotor UAV; S2): Select x = [u,w,p,q,r] T As the controlled variable, u is the forward velocity in the body coordinate system, w is the vertical velocity in the body coordinate system, and p, q, and r are the roll, pitch, and yaw angular velocities, respectively; S3): Set the dynamic equation according to the controlled variable and the dynamic model, and perform Taylor expansion on the dynamic equation at a certain state reference point (x0, u0). Ignore the last term of the Taylor expansion as a small disturbance term, thereby simplifying the Taylor expansion of a certain state reference point (x0, u0); S4): Calculate the increment of the control amount through position acceleration, attitude angular acceleration and feedback; S401): Setting a second-order reference model; S402): Let the forward speed in the body coordinate system be u, and the forward speed command be u cmd , the feedback signal is u back , forward speed command u cmd The reference speed u is obtained through the second-order reference model ref and the reference speed feedforward S403): The speed error can be calculated based on the reference speed and the feedback signal, and the speed deviation is subjected to PI control and feedforward of the second-order reference model to obtain the forward acceleration; S404): Replace the forward velocity in S401 to S403 with the velocity and angular velocity of each position and attitude. Similarly, calculate the acceleration and angular acceleration of each position and attitude, which is recorded as A ctrl and compare it with the acceleration and angular acceleration feedback A back By doing the difference, we can get the acceleration error △A=A ctrl -A back ; S5): Calculate the total control quantity.

2. The control method for a tilt-wing logistics UAV according to claim 1, characterized in that: The dynamic model in S1 is as follows: Where u is the forward velocity in the body coordinate system, w is the vertical velocity in the body coordinate system, p, q and r are the roll, pitch and yaw angular velocities respectively, g is the acceleration of gravity, m is the mass, θ and φ are the pitch and roll angles, I xx , I yy , I zz , I zx and I xz is the moment of inertia along different axes, F x , F z , L, M and N are the force in the X direction of the body axis system, the force in the Z direction of the body axis system, the rolling moment, the pitching moment and the yaw moment respectively.

3. The control method for a tilt-wing logistics UAV according to claim 2, characterized in that: The dynamic equation set according to the controlled quantity in S3) is as follows: Among them, u k is the control input and x is the controlled variable.

4. The control method for a tilt-wing logistics UAV according to claim 3, characterized in that: The specific formula for Taylor expansion of the dynamic equation at a certain state reference point (x0, u0) is as follows: make This term is ignored as a small disturbance term, and the simplified Taylor expansion is as follows: Setting the control efficiency matrix △U=(u-u0), and the model obtained after ignoring the above small disturbance terms due to the high sampling frequency is as follows: Right now, 5. The control method for a tilt-wing logistics UAV according to claim 1, characterized in that: The second-order reference model formula set in S401 is as follows: Among them, s is the Laplace operator, ζ is the damping ratio, ω c is the frequency.

6. The control method for a tilt-wing logistics UAV according to claim 5, characterized in that: The forward acceleration calculation process in S403 is as follows: According to the reference speed u ref and the feedback signal is u back Calculate the speed error e = u ref -u back ; The speed deviation is controlled by PI and fed forward by the second-order reference model to obtain the forward acceleration A x , the formula is as follows: Among them, k p , k I and They are proportional gain, integral gain and feedforward that generates instructions through the second-order reference model.

7. The control method for a tilt-wing logistics UAV according to claim 4, characterized in that: The total control quantity calculated in S5 includes: S501): Calculate the increment of the control amount, the formula is as follows: △U=B -1 △A Among them, △U is the increment of the control quantity; S502): Calculate the total amount of control quantity, the formula is as follows: U=U0+△U Among them, U is the total amount of control quantity, and U0 is the basic control quantity.

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