A method for estimating external wind force of a quadrotor drone

Abstract

The invention relates to the technical field of wind force estimation, and specifically refers to a method for estimating external wind force of a quad-rotor unmanned aerial vehicle, comprising: constructing a kinematic model of the quad-rotor unmanned aerial vehicle, constructing a twelve-dimensional state quantity model of the quad-rotor unmanned aerial vehicle based on a nonlinear relationship between the angular velocity in an inertial coordinate system of the quad-rotor unmanned aerial vehicle and in a body coordinate system, and converting the model into a state space equation expression; constructing an extended state observer under a dynamic event triggering mechanism, wherein the extended state observer adds an external wind force estimation item to the external wind force change rate and calculates the external wind force estimation quantity; when the dynamic event triggering mechanism takes effect, the extended state observer receives the true value of the state measured by the sensor of the quad-rotor unmanned aerial vehicle at the current moment, and corrects the state estimation value at the current moment; the invention is in line with reality and improves the accuracy of modeling; takes the external wind force as an additional state quantity to solve the problem of external wind force jitter; adopts the dynamic event triggering mechanism to reduce communication requirements and improve the accuracy of external wind force estimation.

Description

Technical Field

[0001] The present invention relates to the technical field of wind force estimation, and in particular to an external wind force estimation method for a quad-rotor unmanned aerial vehicle. Background Art

[0002] In recent years, due to the progress of control systems and the miniaturization of instruments, unmanned aerial vehicles (UAVs) have grown and developed greatly; as a UAV system, quadrotor drones have many advantages such as simple structure, small size, operability both indoors and outdoors, vertical take-off and landing, agility, etc., and quadrotor drones are widely used in various environmental monitoring such as atmospheric measurement and air pollution tracking due to their advantages such as hovering ability and high maneuverability; in environmental monitoring activities, since the flight performance of quadrotor drones is easily affected by unpredictable wind conditions, and wind force is an important environmental information, wind information is usually required in many outdoor engineering applications, so wind force monitoring plays an important role, and in engineering practice, it is valuable to design quadrotor drones with wind force capabilities.

[0003] Installing wind sensors, such as anemometers and pitot tube probes, on quadrotors may be a direct way to solve the problem of measuring wind using quadrotors; however, anemometers and other auxiliary sensors are usually large and heavy, in contrast to the payload of quadrotors; in order to save payload and space for other sensors required for environmental monitoring (such as gas sensors), components with additional weight should be avoided, so it is not appropriate to install anemometers and other auxiliary sensors on quadrotors; in addition, although pitot tubes are usually small, their measurement accuracy is often low when the drone is flying at low speeds; in addition, the turbulence caused by the rotor will seriously deteriorate the sensor output, which will seriously affect the flight performance and stability of the quadrotor itself; therefore, the method of directly installing wind sensors on quadrotors does not produce reliable results.

[0004] At present, researchers have introduced various external disturbance estimation methods for quadrotor drones to improve the control performance of quadrotor drones, and use quadrotor drones as detectors to output the size of external wind force; scholars have found that the state of the system itself and the amount of external disturbance can be obtained simultaneously through the observer method. In the literature [Azid SI, Ali SA, Kumar M, et al. Precise Trajectory Tracking of Multi-Rotor UAVs Using Wind Disturbance Rejection Approach[J]. IEEE Access, 2023.], the traditional Lomborg observer is used to estimate and feedback the position and speed of the quadrotor drone, and estimate the external wind force at the same time; however, the Lomborg observer is only applicable to some linear models or rational motion environments, while the quadrotor drone has extremely strong nonlinearity, and there are external disturbances, uncertainties and measurement noise. Therefore, it is difficult for this type of Lomborg observer to ensure that the ideal estimation accuracy can be maintained, and it is difficult to be applied in practice; in the literature [Li R, Zhu Q, Nemati H, et al. Trajectory tracking of a quadrotor using extend state observer based U-model enhanced double sliding mode control[J]. Journal of the Franklin Institute, 2023, 360(4): 3520-3544.], an extended state observer is used to estimate the external disturbance of the motion state of a quadrotor drone; the observer estimates the disturbance as a new state; however, due to the need to adopt a time trigger mechanism, it is very likely that the communication load of the quadrotor drone is too large and the communication is overloaded when performing tasks; and in practical applications, the external wind force estimated by the extended state observer may fluctuate around the true value, that is, there is a vibration error; in addition, most studies have not taken into account that due to the small size and light weight of the quadrotor drone, the onboard communication resources are easily subject to height restrictions, and a lot of communication resources will be consumed in practical applications, resulting in unsatisfactory estimation results.

[0005] In terms of modeling methods, quadcopters have various complex nonlinear terms, and the common processing method is to linearize the nonlinear terms; however, linear modeling ignores the influence of factors such as friction, load changes, external disturbances and measurement noise, resulting in a loss of modeling accuracy. Summary of the invention

[0006] To this end, the technical problem to be solved by the present invention is to overcome the problem that in the modeling method of the prior art, the nonlinear terms of the quadrotor UAV are linearized, resulting in loss of modeling accuracy and non-conformity with reality; in the study of external wind force estimation, it is difficult to ensure that the ideal estimation accuracy can be maintained using the Lomborg observer, and the external wind force value estimated by the extended state observer will have a vibration error problem; the communication limitations of the quadrotor UAV are not taken into account, resulting in the problem of unsatisfactory estimation results due to the consumption of communication resources in practical applications.

[0007] In order to solve the above technical problems, the present invention provides a method for estimating external wind force of a quad-rotor drone, comprising:

[0008] Construct a kinematic model of a quadrotor drone, and construct a twelve-dimensional state quantity model of the quadrotor drone based on the nonlinear relationship between the angular velocity in the inertial coordinate system of the quadrotor drone and the angular velocity in the body coordinate system; define the input, first state space matrix, and second state space matrix of the quadrotor drone system, combine the nonlinear terms of the quadrotor drone, consider the input saturation constraint, and convert the twelve-dimensional state quantity of the quadrotor drone into a state space equation expression;

[0009] Based on the state space equation expression, an extended state observer under the dynamic event trigger mechanism is constructed. The extended state observer adds an external wind force estimation item to the external wind force change rate, and calculates the external wind force estimation corresponding to the next sampling time according to the system sampling time, combined with the state estimation value, state measurement value and external wind force estimation corresponding to the current sampling time of the quadrotor drone; wherein the dynamic event trigger mechanism is: if the threshold function is greater than or equal to the preset dynamic event trigger adaptive variable, the dynamic event trigger condition is 1, the dynamic event trigger takes effect, the quadrotor drone mainboard transmits the operation instruction to the controller, the extended state observer receives the state true value measured by the quadrotor drone sensor at the current moment, and corrects the state estimation value at the current moment; if the threshold function is less than the preset dynamic event trigger adaptive variable, the dynamic event trigger condition is 0, the communication is closed, the quadrotor drone mainboard does not transmit the operation instruction to the controller, and the extended state observer does not receive the state true value measured by the quadrotor drone sensor at the current moment.

[0010] Preferably, a kinematic model of a quad-rotor drone is constructed, and its expression is:

[0011]

[0012] Among them, m t represents the total mass of the quadrotor drone; P e =[x,y,z] TIndicates the position of the quadrotor drone, x, y, z represent the three-axis position of the quadrotor drone; represents the acceleration in the x, y, and z directions, Respectively represent the acceleration in the x, y, and z directions; G e =[0,0,-m t g] represents the gravity acting on the quadrotor drone, g represents the gravitational acceleration; J e =[I xx ,I yy ,I zz ] represents the inertia matrix, I xx represents the moment of inertia in the X direction, I yy represents the moment of inertia in the Y direction, I zz represents the moment of inertia in the Z direction; Θ b represents the Euler angle of the quadrotor drone, Θ b =[φ,θ,ψ] T , φ, θ, ψ represent the roll angle, pitch angle, and yaw angle of the quadrotor UAV in the inertial coordinate system, respectively; It represents the angular velocity of the roll angle, pitch angle and yaw angle of the quadrotor drone in the inertial coordinate system. denote the angular velocities of φ, θ, and ψ respectively; Represents the angular acceleration of the roll angle, pitch angle and yaw angle of the quadrotor drone in the inertial coordinate system, Respectively represent the angular acceleration of φ, θ, ψ; τ f Represents the torque generated by the rotation of the propeller of the quadrotor fixed frame; F e The force from the propeller on the quadcopter in the inertial coordinate system is expressed as:

[0013]

[0014]

[0015]

[0016] Among them, F b K represents the force from the propeller on the quadcopter in the body coordinate system; f represents the thrust coefficient; ω1 represents the rotation speed of the first wing; ω2 represents the rotation speed of the second wing; ω3 represents the rotation speed of the third wing; ω4 represents the rotation speed of the fourth wing; Represents a rotation matrix.

[0017] Preferably, the nonlinear relationship between the angular velocity of the quadrotor drone in the inertial coordinate system and the angular velocity in the body coordinate system is:

[0018]

[0019] Among them, φ, θ, and ψ represent the roll angle, pitch angle, and yaw angle of the quadrotor drone in inertial coordinates, respectively; It represents the angular velocity of the roll angle, pitch angle and yaw angle of the quadrotor drone in the inertial coordinate system; p, q and r represent the angular velocity of the roll angle, pitch angle and yaw angle of the quadrotor drone in the body coordinate system.

[0020] Preferably, a twelve-dimensional state quantity model of a quad-rotor drone is constructed, and its expression is:

[0021]

[0022]

[0023]

[0024]

[0025]

[0026]

[0027]

[0028]

[0029]

[0030]

[0031]

[0032]

[0033] Among them, x, y, and z represent the three-axis positions of the quadrotor drone. represents the translational speed of the quadrotor drone in the x direction, represents the translational speed of the quadrotor drone in the y direction, Indicates the translational speed of the quadrotor drone in the z direction; u e 、v e 、w e Indicates the translational speed of the quadrotor drone in the x, y, and z directions; Indicates the translational acceleration of the quadrotor drone in the x, y, and z directions; F b Represents the force from the propeller on the quadcopter in the body coordinate system; m trepresents the total mass of the quadrotor drone; φ, θ, ψ represent the roll angle, pitch angle, and yaw angle of the quadrotor drone in inertial coordinates, respectively; represents the angular velocity of the roll angle, pitch angle, and yaw angle of the quadrotor drone in the inertial coordinate system; p, q, and r represent the angular velocity of the roll angle, pitch angle, and yaw angle of the quadrotor drone in the body coordinate system; τ φ Indicates that along τ φ The moment in the direction shown; τ θ represents the moment along the direction indicated by θ; τ ψ represents the moment along the direction indicated by ψ; I xx represents the moment of inertia in the X direction; I yy represents the moment of inertia in the Y direction; I zz represents the moment of inertia in the Z direction.

[0034] Preferably, the input, the first state space matrix and the second state space matrix of the quadrotor drone system are defined, the quadrotor drone nonlinear term is combined, the input saturation constraint is considered, and the twelve-dimensional state quantity of the quadrotor drone is converted into a state space equation expression, including:

[0035] Define the input U of the quadrotor drone system, and its expression is:

[0036]

[0037] Among them, U represents the input of the quadrotor drone system, u i ,i∈[1,4] represents the input of the i-th quadrotor drone system; F b Represents the force from the propeller on the quadcopter in the body coordinate system; τ φ represents the moment along the direction indicated by φ; τ θ represents the moment along the direction indicated by θ; τ ψ represents the moment along the direction indicated by ψ;

[0038] Define the first state space matrix A and the second space state matrix B(ξ(t)), whose expressions are:

[0039]

[0040]

[0041] Among them, I 3×3 represents the moment of inertia; I xx represents the moment of inertia in the X direction, I yy represents the moment of inertia in the Y direction, I zz represents the moment of inertia in the Z direction;

[0042] The nonlinear term f(ζ(t)) in the quadrotor UAV system is expressed as:

[0043]

[0044] Among them, φ, θ, ψ represent the roll angle, pitch angle and yaw angle of the quadrotor drone in the inertial coordinate system respectively; p, q, r represent the angular velocity of the roll angle, pitch angle and yaw angle of the quadrotor drone in the body coordinate system; g represents the acceleration of gravity;

[0045] Considering the input saturation constraint, its expression is:

[0046]

[0047] Among them, u i ,i∈[1,4] represents the input of the i-th quadrotor drone system; u Mi represents the input saturation of the i-th quadrotor UAV system;

[0048] Omitting the expression of time t, the state space expression of the quadrotor drone is:

[0049]

[0050] in, represents the derivative of the state quantity of the quadrotor UAV; ζ represents the state quantity of the quadrotor UAV; A represents the first state space matrix; B(ζ) represents the second state space matrix; M(U) represents the input of the quadrotor UAV system after considering the input saturation constraint; f(ζ) represents the nonlinear term in the quadrotor UAV system; d represents the external wind force.

[0051] Preferably, the extended state observer is expressed as:

[0052]

[0053]

[0054] in, represents the derivative of the state estimator of the quadrotor drone; represents the state estimation of the quadrotor drone; ζ(k i ) represents the kth i The state measurement value of the quadrotor drone at the moment; Indicates the kth i The state estimate of the quadrotor drone at time; Indicates the kth i The state error value of the quadrotor drone at the moment, A represents the first state space matrix; B(ζ(k i)) represents the second state space matrix; M(U) represents the input of the quadrotor UAV system after considering the input saturation constraint; f(ζ(k i )) represents the nonlinear term in the quadrotor UAV system; represents the derivative of the external wind force estimate, i.e., the rate of change of the external wind force; represents the external wind force estimate; represents the external wind estimation term; represents the error amount of the external wind force estimation, γ1, μ1, μ2 represent diagonal positive definite constant matrices.

[0055] Preferably, the dynamic event triggering mechanism includes:

[0056] k i It is expressed as the i-th triggering moment. At the i-th triggering moment, the dynamic event triggering mechanism is designed as follows:

[0057]

[0058] Among them, G DET Indicates the dynamic event triggering condition. When G(E ζ )<λ1ξ DET When G DET When G(E) is 1, the dynamic event trigger takes effect, the quadcopter mainboard transmits the operation instruction to the controller, and the extended state observer receives the real state value measured by the quadcopter sensor at the current moment and corrects the estimated state value at the current moment. ζ )≥λ1ξ DET When G DET If it is 0, the communication is closed, the dynamic event is not triggered, the operation command is not transmitted between the quadrotor drone mainboard and the controller, and the extended state observer does not receive the true value of the state measured by the quadrotor drone sensor at the current moment; E ζ Indicates the kth i The error of the drone state measurement transmitted by the sensor at any time, E ζ =ζ-ζ(k i ), ζ represents the state of the quadrotor drone, ζ(k i ) represents the kth i The state measurement value of the quadrotor drone at the time; λ1 represents the positive definite constant matrix;

[0059] G(E ζ ) represents the threshold function, and its expression is:

[0060]

[0061] Where Λ1=μ1γ1-2I 12;γ1,μ1 represent diagonal positive definite constant matrices; I 12 Represents the 12-dimensional identity matrix; α f , α B represents a positive parameter; A represents the first state space matrix; M(U) represents the input of the quadrotor UAV system after considering the input saturation constraint; β1 represents a positive constant less than 1;

[0062] ξ DET Represents the designed dynamic event adaptive variable, the value of which changes automatically according to the value of the following expression:

[0063]

[0064] Where λ2 represents a positive definite constant matrix; h represents a positive constant.

[0065] The present invention also provides an external wind force estimation device for a quad-rotor drone, comprising:

[0066] Memory for storing computer programs;

[0067] A processor is used to implement the steps of any of the above-mentioned methods for estimating external wind force of a quad-rotor unmanned aerial vehicle when executing the computer program.

[0068] The present invention also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the external wind force estimation method for a quad-rotor unmanned aerial vehicle as described above are implemented.

[0069] The above technical solution of the present invention has the following beneficial effects compared with the prior art:

[0070] The external wind force estimation method of a quad-rotor drone described in the present invention takes into account the possibility of large-scale attitude changes of the quad-rotor drone in terms of modeling method. Therefore, when modeling the angular velocity in two coordinate systems, linear processing is not performed, but nonlinear modeling is strictly performed through a conversion matrix; the input saturation phenomenon of the quad-rotor drone is considered, that is, the input of the quad-rotor drone system is limited, and this process essentially considers the dynamic constraints of the quad-rotor drone system; according to the above modeling ideas, the accuracy of modeling is improved, and the disadvantage that the model is not in line with reality is overcome;

[0071] The external wind force estimation method of a quad-rotor unmanned aerial vehicle described in the present invention, in the study of external wind force estimation, when designing a new extended state observer, firstly, the extended state observer is changed, and the external wind force is used as an additional state quantity, thereby solving the jitter problem in the external wind force; secondly, a dynamic time trigger mechanism is adopted, and a trigger is performed only when the conditions are met, and a signal is transmitted, otherwise no communication is performed, thereby greatly saving communication resources; overall, the accuracy of external wind force estimation is improved, the demand for communication is reduced, the requirements of engineering applications such as environmental monitoring are met, and the method is more robust and has more practical application value than traditional estimation methods. BRIEF DESCRIPTION OF THE DRAWINGS

[0072] In order to make the content of the present invention more clearly understood, the present invention is further described in detail below according to specific embodiments of the present invention in conjunction with the accompanying drawings, wherein

[0073] Figure 1 This is a flow chart of external wind force estimation for a quad-rotor drone provided by the present invention;

[0074] Figure 2 It is a schematic diagram of a system model of a quad-rotor UAV provided by the present invention. DETAILED DESCRIPTION

[0075] The present invention is further described below in conjunction with the accompanying drawings and specific embodiments so that those skilled in the art can better understand the present invention and implement it, but the embodiments are not intended to limit the present invention.

[0076] Reference Figure 1 As shown, Figure 1 The present invention provides a flow chart of external wind force estimation for a quad-rotor drone, specifically including:

[0077] S1: Construct a kinematic model of a quadrotor drone, which is expressed as:

[0078]

[0079] Among them, m t represents the total mass of the quadrotor drone; P e =[x,y,z] T Indicates the position of the quadrotor drone, x, y, z represent the three-axis position of the quadrotor drone; represents the acceleration in the x, y, and z directions, Respectively represent the acceleration in the x, y, and z directions; G e =[0,0,-m t g] represents the gravity acting on the quadrotor drone, g represents the gravitational acceleration; J e =[I xx ,Iyy ,I zz ] represents the inertia matrix, I xx represents the moment of inertia in the X direction, I yy represents the moment of inertia in the Y direction, I zz represents the moment of inertia in the Z direction; Θ b represents the Euler angle of the quadrotor drone, Θ b =[φ,θ,ψ] T , φ, θ, ψ represent the roll angle, pitch angle, and yaw angle of the quadrotor UAV in the inertial coordinate system, respectively; It represents the angular velocity of the roll angle, pitch angle and yaw angle of the quadrotor drone in the inertial coordinate system. denote the angular velocities of φ, θ, and ψ respectively; Represents the angular acceleration of the roll angle, pitch angle and yaw angle of the quadrotor drone in the inertial coordinate system, Respectively represent the angular acceleration of φ, θ, ψ; τ f Represents the torque generated by the rotation of the propeller of the quadrotor fixed frame; F e The force from the propeller on the quadcopter in the inertial coordinate system is expressed as:

[0080]

[0081]

[0082]

[0083] Among them, F b K represents the force from the propeller on the quadcopter in the body coordinate system; f represents the thrust coefficient; ω1 represents the rotation speed of the first wing; ω2 represents the rotation speed of the second wing; ω3 represents the rotation speed of the third wing; ω4 represents the rotation speed of the fourth wing; represents the rotation matrix;

[0084] S2: The nonlinear relationship between the angular velocity of the quadrotor drone in the inertial coordinate system and the angular velocity in the body coordinate system is:

[0085]

[0086] Among them, φ, θ, and ψ represent the roll angle, pitch angle, and yaw angle of the quadrotor drone in inertial coordinates, respectively; represents the angular velocity of the roll angle, pitch angle, and yaw angle of the quadrotor drone in the inertial coordinate system; p, q, and r represent the angular velocity of the roll angle, pitch angle, and yaw angle of the quadrotor drone in the body coordinate system;

[0087] Construct a twelve-dimensional state model of a quadrotor drone, and its expression is:

[0088]

[0089]

[0090]

[0091]

[0092]

[0093]

[0094]

[0095]

[0096]

[0097]

[0098]

[0099]

[0100] Among them, x, y, and z represent the three-axis positions of the quadrotor drone. represents the translational speed of the quadrotor drone in the x direction, represents the translational speed of the quadrotor drone in the y direction, Indicates the translational speed of the quadrotor drone in the z direction; u e 、v e 、w e Indicates the translational speed of the quadrotor drone in the x, y, and z directions; Indicates the translational acceleration of the quadrotor drone in the x, y, and z directions; F b Represents the force from the propeller on the quadcopter in the body coordinate system; m t represents the total mass of the quadrotor drone; φ, θ, and ψ represent the roll angle, pitch angle, and yaw angle of the quadrotor drone in inertial coordinates, respectively; represents the angular velocity of the roll angle, pitch angle, and yaw angle of the quadrotor drone in the inertial coordinate system; p, q, and r represent the angular velocity of the roll angle, pitch angle, and yaw angle of the quadrotor drone in the body coordinate system; τ φ represents the moment along the direction indicated by φ; τ θ represents the moment along the direction indicated by θ; τ ψ represents the moment along the direction indicated by ψ; Ixx represents the moment of inertia in the X direction; I yy represents the moment of inertia in the Y direction; I zz represents the moment of inertia in the Z direction;

[0101] S3: Define the input U of the quadrotor drone system, which is expressed as:

[0102]

[0103] Among them, U represents the input of the quadrotor drone system, u i ,i∈[1,4] represents the input of the i-th quadrotor drone system; F b Represents the force from the propeller on the quadcopter in the body coordinate system; τ φ represents the moment along the direction indicated by φ; τ θ represents the moment along the direction indicated by θ; τ ψ represents the moment along the direction indicated by ψ;

[0104] Define the first state space matrix A and the second space state matrix B(ξ(t)), whose expressions are:

[0105]

[0106]

[0107] Among them, I 3×3 represents the moment of inertia; I xx represents the moment of inertia in the X direction, I yy represents the moment of inertia in the Y direction, I zz represents the moment of inertia in the Z direction;

[0108] The nonlinear term f(ζ(t)) in the quadrotor UAV system is expressed as:

[0109]

[0110] Among them, φ, θ, ψ represent the roll angle, pitch angle and yaw angle of the quadrotor drone in the inertial coordinate system respectively; p, q, r represent the angular velocity of the roll angle, pitch angle and yaw angle of the quadrotor drone in the body coordinate system; g represents the acceleration of gravity;

[0111] Considering the input saturation constraint, its expression is:

[0112]

[0113] Among them, u i ,i∈[1,4] represents the input of the i-th quadrotor drone system; u Mirepresents the input saturation of the i-th quadrotor UAV system;

[0114] Omitting the expression of time t, the state space expression of the quadrotor drone is:

[0115]

[0116] in, represents the derivative of the state quantity of the quadrotor drone; ζ represents the state quantity of the quadrotor drone; A represents the first state space matrix; B(ζ) represents the second state space matrix; M(U) represents the input of the quadrotor drone system after considering the input saturation constraint; f(ζ) represents the nonlinear term in the quadrotor drone system; d represents the external wind force;

[0117] Among them, S1-S4 is the modeling process of the quadrotor drone, refer to Figure 2 As shown, Figure 2 A schematic diagram of a system model of a quad-rotor drone provided by the present invention;

[0118] S4: Based on the state space equation expression, the extended state observer under dynamic event triggering is designed, including:

[0119] S41: The extended state observer is expressed as:

[0120]

[0121]

[0122] in, represents the derivative of the state estimator of the quadrotor drone; represents the state estimation of the quadrotor drone; ζ(k i ) represents the kth i The state measurement value of the quadrotor drone at the moment; Indicates the kth i The state estimate of the quadrotor drone at time; Indicates the kth i The state error value of the quadrotor drone at the moment, A represents the first state space matrix; B(ξ(k i )) represents the second state space matrix; M(U) represents the input of the quadrotor UAV system after considering the input saturation constraint; f(ζ(k i )) represents the nonlinear term in the quadrotor UAV system; represents the derivative of the external wind force estimate, i.e., the rate of change of the external wind force; represents the external wind force estimate; represents the external wind estimation term; represents the error amount of the external wind force estimation, γ1, μ1, μ2 represent diagonal positive definite constant matrices;

[0123] Compared with the traditional extended state observer, the present invention considers adding an external wind force estimator when designing the extended state observer. item; since the original external wind force estimation is only determined by Item, experiments show that only considering The item will cause jitter of the estimated amount when the event is not triggered, thus forming a continuous estimation error. Therefore, the present invention adds According to the following experimental verification process, it can be proved that this structure can greatly eliminate the estimation jitter problem and improve the estimation accuracy;

[0124] S42: The dynamic event triggering mechanism includes:

[0125] k i It is expressed as the i-th triggering moment. At the i-th triggering moment, the dynamic event triggering mechanism is designed as follows:

[0126]

[0127] Among them, G DET Indicates the dynamic event triggering condition. When G(E ζ )<λ1ξ DET When G DET When G(E) is 1, the dynamic event trigger takes effect, the quadcopter mainboard transmits the operation instruction to the controller, and the extended state observer receives the real state value measured by the quadcopter sensor at the current moment and corrects the estimated state value at the current moment. ζ )≥λ1ζ DET When G DET If it is 0, the dynamic event will not be triggered, the communication will be closed, no operation instructions will be transmitted between the quadrotor drone mainboard and the controller, and the extended state observer will not receive the true state value measured by the quadrotor drone sensor at the current moment; E ζ Indicates the kth i The error of the drone state measurement transmitted by the sensor at any time, E ζ =ζ-ζ(k i ), ζ represents the state of the quadrotor drone, ζ(k i ) represents the kth i The state measurement value of the quadrotor drone at the time; λ1 represents the positive definite constant matrix;

[0128] G(E ζ ) represents the threshold function, and its expression is:

[0129]

[0130] Where Λ1=μ1γ1-2I 12 ;γ1,μ1 represent diagonal positive definite constant matrices; I 12 Represents the 12-dimensional identity matrix; α f , α B represents a positive parameter; A represents the first state space matrix; M(U) represents the input of the quadrotor UAV system after considering the input saturation constraint; β1 represents a positive constant less than 1;

[0131] ξ DET Represents the designed dynamic event adaptive variable, the value of which changes automatically according to the value of the following expression:

[0132]

[0133] Among them, λ2 represents a positive definite constant matrix; h represents a positive constant;

[0134] Among them, the dynamic event triggering mechanism can ensure that the wind force estimation effect with the same accuracy as that without reducing the number of communications is achieved while reducing the number of communications (saving resources), that is, under the dynamic event triggering mechanism, the number of communications is reduced, but the wind force estimation effect is almost the same; when the dynamic event triggering takes effect, the true value of the state measured by the quadcopter sensor at the current moment will be transmitted to the state observer; regardless of whether the dynamic event triggering is effective, the state observer is always estimating the state quantity of the quadcopter and transmitting the estimated state to the controller, which will calculate the motor thrust and then drive the motor.

[0135] Based on the above embodiments, the feasibility of the extended state observer under the dynamic event triggering mechanism designed by the present invention is verified, and the verification process is as follows:

[0136] The basic definitions, properties and lemmas used in the verification process include:

[0137] Definition 1: Given a state quantity ζ and its corresponding Lyapunov function V(ζ), if V(ζ) is 0 only when ζ = 0, and there is a time t ζ , so that after this moment ||V(ζ)|| is always less than a normal number, then ζ is eventually uniformly stable.

[0138] Lemma 1: Given a state variable ζ and its corresponding Lyapunov function V(ζ), if ||ζ||≥A ζ hour Among them A ζ is a positive constant, then ||ζ|| in the region [0,A ζ ]Eventually consistent and stable.

[0139] Property 1: The nonlinear term f in the state space equation of the quadrotor drone satisfies the Lipsis condition, that is

[0140] ||f(ζ+Δζ-f(ζ)||≤α f ||Δζ||

[0141] Property 2: B in the state space equation of the quadcopter is bounded and satisfies the Lipsis condition, that is,

[0142] ||B(ζ+Δζ)-B(ζ)||≤α B ||Δζ||

[0143]

[0144] Property 3: Young's inequality, that is

[0145]

[0146] Where ε is a positive constant.

[0147] Based on the above basic definitions, properties and lemmas, verify Theorem 1: If If Λ1 is a positive definite matrix, then the state error is estimated by using the extended state observer triggered by dynamic events provided by the present invention. and external wind estimation error is eventually consistent and stable.

[0148] Proof: Choose the Lyapunov function

[0149] Then its derivative is

[0150]

[0151]

[0152]

[0153] Using properties 1 and 2, we can get

[0154]

[0155]

[0156] Among them, || || represents the norm, σ () represents the minimum eigenvalue of the matrix, Represents the largest eigenvalue of the matrix;

[0157] Using property 3, we can get:

[0158]

[0159]

[0160] in,

[0161] In summary, Lemma 1 shows that if time tends to infinity, So The proof is finally concluded to be uniformly stable; and from this, it can be concluded that the designed extended state observer triggered by dynamic events is stable.

[0162] The present invention also provides an external wind force estimation device for a quad-rotor drone, comprising:

[0163] Memory for storing computer programs;

[0164] A processor is used to implement the steps of any of the above-mentioned methods for estimating external wind force of a quad-rotor unmanned aerial vehicle when executing the computer program.

[0165] The present invention also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the external wind force estimation method for a quad-rotor unmanned aerial vehicle as described above are implemented.

[0166] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that include computer-usable program code.

[0167] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0168] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0169] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0170] Obviously, the above embodiments are merely examples for clear explanation and are not intended to limit the implementation methods. For those skilled in the art, other different forms of changes or modifications can be made based on the above description. It is not necessary and impossible to list all the implementation methods here. The obvious changes or modifications derived from these are still within the protection scope of the invention.

Claims

1. A method for estimating external wind force of a quadrotor drone, characterized in that: include: Construct a kinematic model of a quadrotor drone, and construct a twelve-dimensional state quantity model of the quadrotor drone based on the nonlinear relationship between the angular velocity in the inertial coordinate system of the quadrotor drone and the angular velocity in the body coordinate system; define the input, first state space matrix, and second state space matrix of the quadrotor drone system, combine the nonlinear terms of the quadrotor drone, consider the input saturation constraint, and convert the twelve-dimensional state quantity of the quadrotor drone into a state space equation expression; Based on the state space equation expression, an extended state observer under the dynamic event trigger mechanism is constructed. The extended state observer adds an external wind force estimation item to the external wind force change rate, and calculates the external wind force estimation corresponding to the next sampling time according to the system sampling time, combined with the state estimation value, state measurement value and external wind force estimation corresponding to the current sampling time of the quadrotor drone; wherein the dynamic event trigger mechanism is: if the threshold function is greater than or equal to the preset dynamic event trigger adaptive variable, the dynamic event trigger condition is 1, the dynamic event trigger takes effect, the quadrotor drone mainboard transmits the operation instruction to the controller, the extended state observer receives the state true value measured by the quadrotor drone sensor at the current moment, and corrects the state estimation value at the current moment; if the threshold function is less than the preset dynamic event trigger adaptive variable, the dynamic event trigger condition is 0, the communication is closed, the quadrotor drone mainboard does not transmit the operation instruction to the controller, and the extended state observer does not receive the state true value measured by the quadrotor drone sensor at the current moment.

2. The method for estimating external wind force of a quad-rotor drone according to claim 1, characterized in that: Construct a kinematic model of a quadrotor drone, and its expression is: Among them, m t represents the total mass of the quadrotor drone; P e =[x,y,z] T Indicates the position of the quadrotor drone, x, y, z represent the three-axis position of the quadrotor drone; represents the acceleration in the x, y, and z directions, Respectively represent the acceleration in the x, y, and z directions; G e =[0,0,-m t g] represents the gravity acting on the quadrotor drone, g represents the gravitational acceleration; J e =[I xx ,I yy ,I zz ] represents the inertia matrix, I xx represents the moment of inertia in the X direction, I yy represents the moment of inertia in the Y direction, I zz represents the moment of inertia in the Z direction; Θ b represents the Euler angle of the quadrotor drone, Θ b =[φ,θ,ψ] T , φ, θ, ψ represent the roll angle, pitch angle, and yaw angle of the quadrotor UAV in the inertial coordinate system, respectively; It represents the angular velocity of the roll angle, pitch angle and yaw angle of the quadrotor drone in the inertial coordinate system. denote the angular velocities of φ, θ, and ψ respectively; Represents the angular acceleration of the roll angle, pitch angle and yaw angle of the quadrotor drone in the inertial coordinate system, Respectively represent the angular acceleration of φ, θ, ψ; τ f Represents the torque generated by the rotation of the propeller of the quadrotor fixed frame; F e The force from the propeller on the quadcopter in the inertial coordinate system is expressed as: Among them, F b K represents the force from the propeller on the quadcopter in the body coordinate system; f represents the thrust coefficient; ω1 represents the rotation speed of the first wing; ω2 represents the rotation speed of the second wing; ω3 represents the rotation speed of the third wing; ω4 represents the rotation speed of the fourth wing; Represents a rotation matrix.

3. The method for estimating external wind force of a quad-rotor drone according to claim 1, characterized in that: The nonlinear relationship between the angular velocity of the quadrotor drone in the inertial coordinate system and the angular velocity in the body coordinate system is: Among them, φ, θ, and ψ represent the roll angle, pitch angle, and yaw angle of the quadrotor drone in inertial coordinates, respectively; It represents the angular velocity of the roll angle, pitch angle and yaw angle of the quadrotor drone in the inertial coordinate system; p, q and r represent the angular velocity of the roll angle, pitch angle and yaw angle of the quadrotor drone in the body coordinate system.

4. The method for estimating external wind force of a quad-rotor drone according to claim 1, characterized in that: Construct a twelve-dimensional state model of a quadrotor drone, and its expression is: Among them, x, y, and z represent the three-axis positions of the quadrotor drone. represents the translational speed of the quadrotor drone in the x direction, represents the translational speed of the quadrotor drone in the y direction, Indicates the translational speed of the quadrotor drone in the z direction; u e 、v e 、w e Indicates the translational speed of the quadrotor drone in the x, y, and z directions; Indicates the translational acceleration of the quadrotor drone in the x, y, and z directions; F b Represents the force from the propeller on the quadcopter in the body coordinate system; m t represents the total mass of the quadrotor drone; φ, θ, and ψ represent the roll angle, pitch angle, and yaw angle of the quadrotor drone in inertial coordinates, respectively; represents the angular velocity of the roll angle, pitch angle, and yaw angle of the quadrotor drone in the inertial coordinate system; p, q, and r represent the angular velocity of the roll angle, pitch angle, and yaw angle of the quadrotor drone in the body coordinate system; τ φ represents the moment along the direction indicated by φ; τ θ represents the moment along the direction indicated by θ; τ ψ represents the moment along the direction indicated by ψ; I xx represents the moment of inertia in the X direction; I yy represents the moment of inertia in the Y direction; I zz represents the moment of inertia in the Z direction.

5. The method for estimating external wind force of a quad-rotor drone according to claim 1, characterized in that: The input, the first state space matrix and the second state space matrix of the quadrotor drone system are defined, the quadrotor drone nonlinear term is combined, the input saturation constraint is considered, and the twelve-dimensional state quantity of the quadrotor drone is converted into a state space equation expression, including: Define the input U of the quadrotor drone system, and its expression is: Among them, U represents the input of the quadrotor drone system, u i ,i∈[1,4] represents the input of the i-th quadrotor drone system; F b Represents the force from the propeller on the quadcopter in the body coordinate system; τ φ represents the moment along the direction indicated by φ; τ θ represents the moment along the direction indicated by θ; τ ψ represents the moment along the direction indicated by ψ; Define the first state space matrix A and the second space state matrix B(ξ(t)), whose expressions are: Among them, I 3×3 represents the moment of inertia; I xx represents the moment of inertia in the X direction, I yy represents the moment of inertia in the Y direction, I zz represents the moment of inertia in the Z direction; The nonlinear term f(ζ(t)) in the quadrotor UAV system is expressed as: Among them, φ, θ, and v represent the roll angle, pitch angle, and yaw angle of the quadrotor drone in the inertial coordinate system, respectively; p, q, and r represent the angular velocities of the roll angle, pitch angle, and yaw angle of the quadrotor drone in the body coordinate system; g represents the acceleration of gravity; Considering the input saturation constraint, its expression is: Among them, u i ,i∈[1,4] represents the input of the i-th quadrotor drone system; u Mi represents the input saturation of the i-th quadrotor UAV system; Omitting the expression of time t, the state space expression of the quadrotor drone is: in, represents the derivative of the state quantity of the quadrotor UAV; ζ represents the state quantity of the quadrotor UAV; A represents the first state space matrix; B(ζ) represents the second state space matrix; M(U) represents the input of the quadrotor UAV system after considering the input saturation constraint; f(ζ) represents the nonlinear term in the quadrotor UAV system; d represents the external wind force.

6. The method for estimating external wind force of a quad-rotor drone according to claim 1, characterized in that: The extended state observer is expressed as: in, represents the derivative of the state estimator of the quadrotor drone; represents the state estimation of the quadrotor drone; ζ(k i ) represents the kth i The state measurement value of the quadrotor drone at the moment; Indicates the kth i The state estimate of the quadrotor drone at time; Indicates the kth i The state error value of the quadrotor drone at the moment, A represents the first state space matrix; B(ζ(k i )) represents the second state space matrix; M(U) represents the input of the quadrotor UAV system after considering the input saturation constraint; f(ζ(k i )) represents the nonlinear term in the quadrotor UAV system; represents the derivative of the external wind force estimate, i.e., the rate of change of the external wind force; represents the external wind force estimate; represents the external wind estimation term; represents the error amount of the external wind force estimation, γ1, μ1, μ2 represent diagonal positive definite constant matrices.

7. The method for estimating external wind force of a quad-rotor drone according to claim 1, characterized in that: The dynamic event triggering mechanism includes: k i It is expressed as the i-th triggering moment. At the i-th triggering moment, the dynamic event triggering mechanism is designed as follows: Among them, G DET Indicates the dynamic event triggering condition. When G(E ζ )<λ1ξ DET When G DET When G(E) is 1, the dynamic event trigger takes effect, the quadcopter mainboard transmits the operation instruction to the controller, and the extended state observer receives the real state value measured by the quadcopter sensor at the current moment and corrects the estimated state value at the current moment. ζ )≥λ1ξ DET When G DET If it is 0, the dynamic event will not be triggered, the communication will be closed, no operation instructions will be transmitted between the quadrotor drone mainboard and the controller, and the extended state observer will not receive the true state value measured by the quadrotor drone sensor at the current moment; E ζ Indicates the kth i The error of the drone state measurement transmitted by the sensor at any time, E ζ =ζ-ζ(k i ), ζ represents the state of the quadrotor drone, ζ(k i ) represents the kth i The state measurement value of the quadrotor drone at the time; λ1 represents the positive definite constant matrix; G(E ζ ) represents the threshold function, and its expression is: Where Λ1=μ1γ1-2I 12 ;γ1,μ1 represent diagonal positive definite constant matrices; I 12 Represents the 12-dimensional identity matrix; α f , α B represents a positive parameter; A represents the first state space matrix; M(U) represents the input of the quadrotor UAV system after considering the input saturation constraint; β1 represents a positive constant less than 1; ξ DET Represents the designed dynamic event adaptive variable, the value of which changes automatically according to the value of the following expression: Where λ2 represents a positive definite constant matrix; h represents a positive constant.

8. An external wind force estimation device for a quad-rotor drone, characterized in that: include: Memory for storing computer programs; A processor, configured to implement the steps of a method for estimating external wind force of a quadrotor drone as described in any one of claims 1 to 7 when executing the computer program.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the external wind force estimation method for a quad-rotor drone as described in any one of claims 1 to 7 are implemented.

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