A method for estimating the response characteristics of an unmanned aerial vehicle (UAV) pod to firing disturbances.

Abstract

This invention relates to the field of aircraft control technology and discloses a method for estimating the response characteristics of an unmanned aerial vehicle (UAV) pod under impact disturbance. The method involves establishing a rigid body model of the UAV pod; establishing a disturbance model to generate transient impact disturbances; establishing a flight control system model and a pod control system model; and inputting the transient impact disturbance generated by the disturbance model, the UAV control commands generated by the flight control system model, and the pod control commands generated by the pod control system model into the rigid body model to drive iterative state updates, thereby estimating the response characteristics of the UAV and pod after being disturbed. This invention solves the problems of existing technologies relying on empirical testing and lacking systematic theoretical modeling methods. It can quickly, accurately, and economically estimate disturbance response characteristics, reduce experimental costs, and lower safety risks.

Description

Technical Field

[0001] This invention relates to the field of aircraft control technology, and in particular to a method for estimating the response characteristics of an unmanned aerial vehicle (UAV) pod to firing disturbances. Background Technology

[0002] With the widespread application of UAV technology in industrial inspection, moving target tracking, and aerial operations, UAV-borne pods, as an important mission execution carrier, have the core requirement of ensuring UAV attitude stability and pod pointing accuracy when external equipment is activated (such as the release of impact loads) to guarantee continuous target tracking accuracy during operations. However, the transient impact disturbances generated by the activation of external equipment can significantly affect the flight stability of UAVs, leading to two prominent problems: First, the stabilization waiting time after a single activation is prolonged, requiring the UAV to wait for its attitude to stabilize after load release before re-entering the aiming or tracking process, severely restricting the UAV's continuous operation capability; second, reduced stability during continuous activation, with sudden changes in angular rate making it difficult for the pod to continuously lock onto the target, resulting in excessive pointing deviation and affecting operational effectiveness.

[0003] To mitigate the aforementioned adverse effects, it is necessary to analyze the response characteristics of the UAV after being subjected to transient impact disturbances, and then derive the pod servo compensation amount. Currently, existing research on the impact of external loads on UAVs mainly relies on empirical analysis or experimental testing, lacking systematic theoretical modeling and prediction methods; especially under complex flight conditions, the dynamic response characteristics of UAV-borne pods are difficult to accurately assess and predict through simple experimental means.

[0004] Therefore, there is an urgent need for a theoretical modeling-based method that can quickly and accurately evaluate the disturbance response characteristics of the UAV-borne pod platform during the impact of external loads, so as to verify the attitude compensation control of the UAV and the attitude compensation algorithm of the pod, reduce the consumption of test materials during the test, and reduce the potential safety risks to personnel and equipment. Summary of the Invention

[0005] The purpose of this invention is to provide a method for estimating the response characteristics of UAV-borne pods under impact, which solves the problem in the prior art that relies on empirical analysis or experimental testing and lacks a systematic theoretical modeling method, making it difficult to quickly and accurately evaluate the response characteristics of UAV-borne pods under external load impact.

[0006] To achieve the above objectives, the present invention provides a method for estimating the response characteristics of an unmanned aerial vehicle (UAV) pod during firing disturbances, comprising the following steps: A rigid body model of the UAV-borne pod is established, which is used to describe the dynamic characteristics of the UAV and the pod. A disturbance model is established to generate transient impact disturbances, including impact disturbances generated when external equipment is activated. A flight control system model is established, which is used to generate UAV control commands based on the UAV state variables output by the rigid body model. A pod control system model is established, which is used to generate pod control commands based on the pod state variables output by the rigid body model. The transient impact disturbance generated by the disturbance model, the UAV control command generated by the flight control system model, and the pod control command generated by the pod control system model are all input into the rigid body model to drive the rigid body model to iteratively update its state, thereby estimating the response characteristics of the UAV and pod after being subjected to the transient impact disturbance.

[0007] In the rigid body model, the pod rigid body model is established using the Lagrange dynamics method, and the UAV rigid body model is established using the Newton-Euler method. The pod rigid body model uses the pod's azimuth joint angle and pitch joint angle as generalized coordinates, and the UAV rigid body model ignores the UAV's position changes, friction, damping, and blade deformation.

[0008] In the disturbance model, the transient impact disturbance is described by a piecewise function, wherein the rising phase of the impact disturbance is represented by a polynomial model and the decay phase of the impact disturbance is represented by an exponential model.

[0009] The piecewise function is expressed as:

[0010] in: The amplitude of the impact disturbance; Indicates the peak time of the impact disturbance; n represents the shape factor of the rising phase; This represents the time constant during the decay phase; Indicates the total duration; This refers to the transient impact disturbance generated by the operation of external devices.

[0011] The disturbances generated by the disturbance model include the reaction torque generated by the pod rotation on the airframe, external environmental disturbances, and the tension and torque generated by the rotation of the UAV propellers.

[0012] The reaction torque generated by the rotation of the pod on the aircraft body is obtained in the following way: The motor torques of the pod's azimuth and pitch joints are obtained, and the disturbance torque in the body coordinate system is calculated by coordinate transformation in combination with the joint angles.

[0013] The formula for calculating the reaction torque is as follows:

[0014] in: and These are the motor torques for the pod's azimuth and pitch joints, respectively. , These are the joint angles for the azimuth and pitch joints, respectively. This represents the disturbance torque generated by the rotation of the pod joint in the body coordinate system.

[0015] The flight control system model adopts a three-level architecture of position control, attitude control, and control allocation. Position control and attitude control are composed of PID controllers connected in series. The control allocation is used to calculate the expected rotational speed of each rotor based on the expected thrust output of position control and the expected torque in the pitch, yaw, and roll directions output of attitude control.

[0016] The formula for calculating the desired rotational speed is as follows:

[0017] in: ~ For the expected rotational speed of each rotor, The desired pulling force for position control output. , , These represent the expected torques in the pitch, yaw, and roll directions of the attitude control output, respectively.

[0018] The pod control system model is based on a servo three-loop control system with added angle stabilization control and angular velocity stabilization control. The servo three-loop control system includes a current loop, a velocity loop, and a position loop, with the angle stabilization control and angular velocity stabilization control superimposed on the velocity loop and the position loop.

[0019] This invention discloses a method for estimating the response characteristics of an unmanned aerial vehicle (UAV) pod under impact disturbance. First, a rigid body model is established to describe the dynamic characteristics of the UAV and pod. Then, a disturbance model for generating transient impact disturbances, a flight control system model for generating control commands based on the UAV state variables output from the rigid body model, and a pod control system model for generating control commands based on the pod state variables output from the rigid body model are also established. Next, the transient impact disturbance generated by the disturbance model, the UAV control commands generated by the flight control system model, and the pod control commands generated by the pod control system model are all input into the rigid body model, driving iterative updates to its state. This allows for the estimation of the response characteristics of the UAV and pod after being subjected to transient impact disturbances. This method solves the problem in existing technologies that rely on empirical analysis or experimental testing and lack systematic theoretical modeling methods, making it difficult to quickly and accurately assess the disturbance response characteristics of an UAV pod under external load impact. It achieves rapid, accurate, and economical estimation of the disturbance response, effectively reducing the consumption of experimental materials and lowering safety risks to personnel and equipment. Attached Figure Description

[0020] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the accompanying drawings used in the description of the embodiments or the prior art will be briefly introduced below.

[0021] Figure 1 This is a schematic diagram of the UAV-borne pod of the present invention.

[0022] Figure 2 This is a schematic diagram of the blade arrangement of the six-rotor UAV of the present invention.

[0023] Figure 3 This is a simplified structural diagram and coordinate system diagram of the external pod of the present invention.

[0024] Figure 4 This is a block diagram of the unmanned aerial vehicle (UAV) flight control system of the present invention.

[0025] Figure 5 This is a block diagram of the pod control system of the present invention.

[0026] Figure 6 This is a comparison chart of the pitch attitude disturbance response of the UAV of the present invention and three repeated tests.

[0027] Figure 7 This is a comparison diagram of the pod servo pitch attitude disturbance response of the present invention and three repeated tests.

[0028] Figure 8 This is a flowchart illustrating the steps of the method for estimating the response characteristics of the unmanned aerial vehicle (UAV) pod to firing disturbances according to the present invention. Detailed Implementation

[0029] The embodiments of the present invention are described in detail below. Examples of the embodiments are shown in the accompanying drawings. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain the present invention, but should not be construed as limiting the present invention.

[0030] Please refer to Figures 1 to 8 This invention provides a method for estimating the response characteristics of an unmanned aerial vehicle (UAV) pod to firing disturbances, comprising the following steps: S101: Establish a rigid body model of the UAV-borne pod, which is used to describe the dynamic characteristics of the UAV and the pod; S102: Establish a disturbance model, which is used to generate transient impact disturbances, including impact disturbances generated when external equipment is activated; S103: Establish a flight control system model, which is used to generate UAV control commands based on the UAV state variables output by the rigid body model; S104: Establish a pod control system model, which is used to generate pod control commands based on the pod state quantities output by the rigid body model. S105: The transient impact disturbance generated by the disturbance model, the UAV control command generated by the flight control system model, and the pod control command generated by the pod control system model are all input into the rigid body model to drive the rigid body model to iteratively update its state, thereby estimating the response characteristics of the UAV and pod after being subjected to the transient impact disturbance.

[0031] Specifically, a rigid body model of the UAV-borne pod is established: The drone-borne pod consists of two main modules: a hexacopter drone and the pod. Its basic structure is as follows: Figure 1 The following is given. Since the change in the UAV's position during the operation of the external attachment has a relatively small impact on pointing accuracy, to simplify calculations, the pod model ignores the influence of the UAV's position change; that is, the angles of the two-axis joints of the pod are selected as generalized coordinates to establish the pod's Lagrangian dynamic equations; the UAV's position is ignored. To mitigate the impact of friction, damping, and blade deformation, a rigid body model of the UAV is established using the Newton-Euler method. The system model is established as follows:

[0032] This refers to the pod's orientation and the joint angles of the pitch joint. The selected generalized coordinates; For inertial force, Joint angular acceleration, For Coriolis force and centrifugal force terms, Joint angular velocity, For gravity, This is the driving torque for the pod joint; This indicates the mass of the yaw and pitch joints of the drone and its pod. The total mass of the drone and its pod; The inertial tensor representing the yaw and pitch joints of the drone and its pod. The sum of the inertial tensors of the azimuth and pitch joints of the UAV and its pod in the UAV's body coordinate system; ∑τ represents the driving torque generated in the body coordinate system by the rotation of the UAV propellers, external disturbances, and the rotation of the pod joints; ∑τ is the sum of the aforementioned three driving torques. This is the sum of the three driving torques mentioned above; This represents the forces generated by the rotation of the multirotor blades and external disturbances in the airframe coordinate system. This represents the coordinate transformation from the UAV's body coordinate system to the inertial coordinate system; This represents the acceleration due to gravity in an inertial coordinate system. Accelerate the movement of the drone; The term represents the gyroscopic torque of the motor rotor and propeller rotating about their axis of rotation; This represents the angular velocity of the UAV in the body coordinate system. This represents the angular acceleration of the UAV in the body coordinate system.

[0033] Among them, for the PNPNPN standard layout hexacopter drone, Figure 2 This refers to the blade arrangement. The driving force generated by the rotation of the blades in the airframe coordinate system. and driving torque It is represented in the following form.

[0034]

[0035] in, ω1~ω6 represent the rotational speeds of the individual propeller blades of the UAV. d represents the total tension generated by the rotation of the propellers at the coordinate center of the UAV body. This indicates the distance from the center of the propeller blade's rotation to the center of the fuselage. , This indicates the thrust coefficient and torque coefficient of the propeller.

[0036] Further calculations .

[0037]

[0038] in, This represents the sum of the rotational inertia of the individual motor rotor and propeller of a multi-rotor aircraft. , This represents the angular velocity of the UAV's rotation around the x and y axes of the body coordinate system.

[0039] Based on the Denavit-Hartenberg convention, a coordinate relationship is established, and a simplified structural diagram of the under-mounted external pod for the hexarotor UAV is shown below. Figure 3 .in,( (xyz) is the coordinate system of the UAV's body center frame. It is fixed to a six-rotor drone. x1-y1-z1) is the bracket system, fixedly connected to the external pod bracket, ( (x2-y2-z2) is the load system, fixed to the external equipment. θ1 and θ2 are the joint rotation angles in the azimuth and pitch directions of the servo pod, respectively, with the positive rotation direction following the right-hand screw rule.

[0040] Based on the coordinate system establishment method described above, the DH parameters of the external pod are given in the table below.

[0041] Table 1 External Pod Structure DH Parameters

[0042] Where d1 and a2 are the lengths of the pod connecting rods, and θ1 and θ2 are the angles of the pod joints.

[0043] Agreement c1 express cosθ1, s1 represents sinθ1 c2 represents cosθ2, s2 represents sinθ2, and the homogeneous transformation matrix between the above coordinate systems is:

[0044] in, , Let be the homogeneous transformation matrix of the pod joint.

[0045] Therefore, the coordinate transformation from the impact disturbance to the UAV body coordinate system .

[0046] definition This indicates the position of the center of mass of link i at... Augmented representation in a coordinate system. That is, the position of the bracket's center of mass is in the bracket coordinate system. The following augmented representation The position of the cradle's center of mass in the cradle coordinate system The following augmented representation They are respectively:

[0047] Based on the relationships between the aforementioned coordinate systems, the centers of mass of the bracket (link 1) and the cradle (link 2) lie in the coordinate system of the UAV's body center. Representation in coordinate system , As shown below.

[0048]

[0049] The position of the center of gravity of the bracket in the upper position. and the position of the cradle's center of mass Coordinates at In the coordinate system, they are represented as follows:

[0050]

[0051] further, and By taking the derivative with respect to time t, we can obtain the velocity of the link's center of mass in the UAV's body coordinate system.

[0052]

[0053]

[0054] The motion of the external pod includes both translational and rotational components, requiring further consideration of the rotational kinetic energy term. Let k be the unit coordinate vector. The rotational angular velocities of connecting rod 1 and connecting rod 2 are at The representation in coordinate system is as follows:

[0055] Since the kinetic energy of a rigid body is the sum of its translational kinetic energy when it contracts to its center of mass and its rotational kinetic energy about its center of mass, substituting the translational velocity and rotational angular velocity of the connecting rod about its center of mass, the kinetic energy of the external pod connecting rod i is finally expressed in the following form.

[0056]

[0057] in, , These are the translational velocity and rotational angular velocity of the center of mass of the pod linkage, respectively, E ki This represents the kinetic energy of the external pod linkage i.

[0058] The zero potential energy surface of the pod is located in the UAV body coordinate system. Take the plane where it is located The pod potential energy term is expressed as follows:

[0059] Where i is 1, This indicates the position of the bracket's center of mass. When i is 0, E represents the position of the cradle's center of mass. p Let be the total potential energy of the system.

[0060] A rigid body dynamic model of the pod is established based on the Lagrange dynamics method, and the equations of motion are expressed as follows:

[0061]

[0062] Where: L is the Lagrange operator. , These are the system's kinetic energy and potential energy, respectively.

[0063] Substituting into the aforementioned equations, the Lagrange equations for the servo pod are finally simplified to the following form: in, Inertial force term, Joint angular acceleration, For Coriolis force and centrifugal force terms, The joint angular velocity, For gravity, This is the driving torque for the pod joint.

[0064] Establish a model for recoil and pod joint torque disturbances: Analysis reveals that the changes in the drone's attitude are caused by four factors: (1) The effect of the pod rotation on the reaction force generated by the body; (2) Impact and disturbance generated during the operation of external equipment; (3) The impact of external environmental disturbances, such as wind disturbances; (4) The influence of tension and torque generated by the rotation of UAV propellers; The process by which the UAV drives the propeller to rotate in order to maintain its own motion state is affected by the characteristics of its own flight control system, and its effect is given in step 3.

[0065] To analyze the impact of the pod rotation on the reaction force generated by the airframe, TM1 and TM2 are used to represent the joint torque of the servo pod, respectively. This torque is calculated from the pod control system model, and its reaction disturbance torque in the airframe coordinate system is:

[0066] in: and These represent the motor torques for the servo pod's azimuth and pitch joints, respectively. , For the joint angles of the servo azimuth and pitch joints. This represents the driving torque generated by the rotation of the pod joint in the body coordinate system.

[0067] To analyze the impact of shock disturbances generated during the operation of external devices, a piecewise function is used to describe the shock disturbances. The disturbance rise phase is represented by a polynomial model, and the disturbance decay phase is represented by an exponential model.

[0068]

[0069] in: The amplitude of the impact disturbance; Indicates the peak time of the impact disturbance; n represents the shape factor of the rising phase; Indicates the decay time constant; Indicates the total duration; This refers to the transient impact disturbance generated by the operation of external devices.

[0070] Furthermore, use This represents the coordinate transformation from the impact disturbance to the UAV's body coordinate system. Considering the influence of wind disturbance, the disturbance generated at the center of the UAV body by the impact disturbance of the external equipment is shown below.

[0071]

[0072] in: and These represent the force and torque disturbance generated at the center of the UAV body by the impact disturbance of the external equipment's operation, respectively. and This indicates the force and torque effects of wind disturbance.

[0073] Establish a flight control system model: During operation with external equipment, the position and attitude changes of a drone are influenced not only by the system's own dynamic characteristics but also by the drone's flight control system. Therefore, modeling the drone's flight control system is necessary. The flight control system model discussed in this invention consists of three parts: position control, attitude control, and control allocation. Position control, the outermost loop, controls the drone's motion states, such as hovering position and flight speed, and its output is the desired angle of deflection of each of the drone's rotation axes. Attitude control, the intermediate loop, takes the output of position control as its input and aims to ensure that the deflection angles of each axis match the desired input angles. Control allocation, the final loop, determines the actual output to the desired speed of the brushless motor in the electronic speed controller.

[0074] The block diagram of the drone flight control system is as follows: Figure 4 As shown in the figure. The position control and attitude control are composed of basic PID controllers connected in series.

[0075] The desired tension output of the position control and the desired torque output of the attitude control in the pitch, yaw, and roll directions are controlled and distributed in the following way to achieve the desired brushless motor speed.

[0076]

[0077] in: ~ This is the calculated expected value of the brushless motor speed. This represents the desired pulling force output by the position control. , , This represents the expected torque in the pitch, yaw, and roll directions of the attitude control output.

[0078] Establish a pod control system model: Based on the aforementioned system modeling, and combined with practical considerations, a servo control algorithm model is developed. Angle and angular velocity stabilization control are superimposed on the basic servo three-loop control system. The control principle block diagram is shown below. Figure 5 The information is provided in the text.

[0079] To verify whether this invention can quickly, accurately, and economically analyze the impact of transient shock disturbances on multi-rotor UAVs and their pod platforms, a simulation example following the above method is given below.

[0080] The simulation conditions are set as follows: (1) The pod is equipped with external equipment. It operates once. During operation, the pod's azimuth and pitch angle are 0 degrees.

[0081] (2) The servo has no maximum torque output limit.

[0082] (3) The impact of environmental disturbances is not considered.

[0083] Under the above conditions, a numerical simulation model of the system was built using a visual simulation tool based on the above formula. Constant parameters such as the pod linkage length and inertia tensor, and UAV structural parameters were directly derived from the structural model. Control parameters such as flight control system parameters and pod control system parameters were obtained through experimental tuning. The pitch attitude disturbance response curves of the UAV and pod servo are consistent with the actual situation. The simulation results are compared with those of three repeated experiments under the same conditions. Figure 6 , Figure 7 Provided.

[0084] This invention establishes a rigid body model, a disturbance model, and a dual-closed-loop control system model for the UAV and its pod. It then inputs both the disturbance and control commands into the rigid body model for iterative updates, forming a systematic theoretical modeling and simulation estimation method. This method solves the problems of existing technologies that rely on empirical analysis or experimental testing and lack systematic theoretical modeling, making it difficult to quickly and accurately assess disturbance response characteristics. It can quickly, accurately, and economically estimate the response characteristics of the UAV and its pod under transient impact disturbances, providing a reliable basis for attitude compensation algorithms. Simultaneously, it effectively reduces experimental material consumption and lowers personnel and equipment safety risks.

[0085] The above-disclosed embodiments are merely one or more preferred embodiments of this application and should not be construed as limiting the scope of this application. Those skilled in the art can understand that all or part of the processes for implementing the above embodiments and equivalent changes made in accordance with the claims of this application still fall within the scope of this application.

Claims

1. A method for estimating the response characteristics of an unmanned aerial vehicle (UAV) pod to firing disturbances, characterized in that, Includes the following steps: A rigid body model of the UAV-borne pod is established, which is used to describe the dynamic characteristics of the UAV and the pod. A disturbance model is established to generate transient impact disturbances, including impact disturbances generated when external equipment is activated. A flight control system model is established, which is used to generate UAV control commands based on the UAV state variables output by the rigid body model. A pod control system model is established, which is used to generate pod control commands based on the pod state variables output by the rigid body model. The transient impact disturbance generated by the disturbance model, the UAV control command generated by the flight control system model, and the pod control command generated by the pod control system model are all input into the rigid body model to drive the rigid body model to iteratively update its state, thereby estimating the response characteristics of the UAV and pod after being subjected to the transient impact disturbance.

2. The method for estimating the response characteristics of an unmanned aerial vehicle (UAV) pod during firing disturbances as described in claim 1, characterized in that, In the rigid body model, the pod rigid body model is established using the Lagrange dynamics method, and the UAV rigid body model is established using the Newton-Euler method. The pod rigid body model uses the pod's azimuth joint angle and pitch joint angle as generalized coordinates, and the UAV rigid body model ignores the UAV's position changes, friction, damping, and blade deformation.

3. The method for estimating the response characteristics of an unmanned aerial vehicle (UAV) pod during firing disturbances as described in claim 1, characterized in that, In the disturbance model, the transient impact disturbance is described by a piecewise function, wherein the rising phase of the impact disturbance is represented by a polynomial model and the decay phase of the impact disturbance is represented by an exponential model.

4. The method for estimating the response characteristics of an unmanned aerial vehicle (UAV) pod during firing disturbances as described in claim 3, characterized in that, The piecewise function is expressed as: ； in: The amplitude of the impact disturbance; Indicates the peak time of the impact disturbance; n represents the shape factor of the rising phase; This represents the time constant during the decay phase; Indicates the total duration; This refers to the transient impact disturbance generated by the operation of external devices.

5. The method for estimating the response characteristics of an unmanned aerial vehicle (UAV) pod during firing disturbances as described in claim 1, characterized in that, The disturbances generated by the disturbance model also include the reaction torque generated by the pod rotation on the airframe, external environmental disturbances, and the tension and torque generated by the rotation of the UAV propellers.

6. The method for estimating the response characteristics of an unmanned aerial vehicle (UAV) pod during firing disturbances as described in claim 5, characterized in that, The reaction torque generated by the rotation of the pod on the aircraft body is obtained in the following way: The motor torques of the pod's azimuth and pitch joints are obtained, and the disturbance torque in the body coordinate system is calculated by coordinate transformation in combination with the joint angles.

7. The method for estimating the response characteristics of an unmanned aerial vehicle (UAV) pod during firing disturbances as described in claim 6, characterized in that, The formula for calculating the reaction torque is: ； in: and These are the motor torques for the pod's azimuth and pitch joints, respectively. , These are the joint angles for the azimuth and pitch joints, respectively. This represents the disturbance torque generated by the rotation of the pod joint in the body coordinate system.

8. The method for estimating the response characteristics of an unmanned aerial vehicle (UAV) pod during firing disturbances as described in claim 1, characterized in that, The flight control system model adopts a three-level architecture of position control, attitude control, and control allocation. Position control and attitude control are composed of PID controllers connected in series. The control allocation is used to calculate the expected rotational speed of each rotor based on the expected thrust output of position control and the expected torque in the pitch, yaw, and roll directions output of attitude control.

9. The method for estimating the response characteristics of an unmanned aerial vehicle (UAV) pod during firing disturbances as described in claim 8, characterized in that, The formula for calculating the desired rotational speed is: ； in: ~ For the expected rotational speed of each rotor, The desired pulling force for position control output. , , These represent the expected torques in the pitch, yaw, and roll directions of the attitude control output, respectively.

10. The method for estimating the response characteristics of an unmanned aerial vehicle (UAV) pod during firing disturbances as described in claim 1, characterized in that, The pod control system model is based on a servo three-loop control system with added angle stabilization control and angular velocity stabilization control. The servo three-loop control system includes a current loop, a velocity loop, and a position loop, with the angle stabilization control and angular velocity stabilization control superimposed on the velocity loop and the position loop.

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