CN110488875B - Course error correction method for target tracking initial section of unmanned aerial vehicle based on dynamic inversion - Google Patents

Course error correction method for target tracking initial section of unmanned aerial vehicle based on dynamic inversion Download PDF

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CN110488875B
CN110488875B CN201910824367.8A CN201910824367A CN110488875B CN 110488875 B CN110488875 B CN 110488875B CN 201910824367 A CN201910824367 A CN 201910824367A CN 110488875 B CN110488875 B CN 110488875B
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张毅
杨秀霞
曹唯一
方国伟
严瑄
高恒杰
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Naval Aeronautical University
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C25/00—Manufacturing, calibrating, cleaning, or repairing instruments or devices referred to in the other groups of this subclass
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C25/00—Manufacturing, calibrating, cleaning, or repairing instruments or devices referred to in the other groups of this subclass
    • G01C25/005—Manufacturing, calibrating, cleaning, or repairing instruments or devices referred to in the other groups of this subclass initial alignment, calibration or starting-up of inertial devices
    • G—PHYSICS
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Abstract

The invention discloses a method for correcting course errors of an unmanned aerial vehicle tracking target initial segment based on dynamic inversion, which comprises the following steps: calculating an initial course error; carrying out dynamic reverse course correction; updating and correcting the course error until the course error approaches zero. The method well solves the problem of time separation between the course convergence process and the tracking convergence of the unmanned aerial vehicle to the target circle in the existing method, can realize rapid correction of large course errors existing in the tracking target initial section of the unmanned aerial vehicle, has controllable convergence speed, and continuously reduces the overload in the correction process; the method also has the advantages of global stability, good effectiveness and practicability and the like.

Description

Course error correction method for target tracking initial section of unmanned aerial vehicle based on dynamic inverse
Technical Field
The invention belongs to the field of path planning of unmanned aerial vehicles, mainly relates to a course error correction method for an initial section of a tracked target of an unmanned aerial vehicle, and particularly relates to a course error correction method for an initial section of a tracked target of an unmanned aerial vehicle based on dynamic inversion.
Background
As an aircraft capable of being controlled autonomously or remotely, an unmanned aerial vehicle has attracted more and more attention due to its high endurance and maneuverability, and its path planning during flight has also become a research hotspot.
Tracking and monitoring ground targets are one of the main tasks of Unmanned Aerial Vehicles (UAVs). In order to continuously track the target and acquire target information, when executing such tasks, the unmanned aerial vehicle performs hover tracking around the target by taking the target as a circle center and an expected tracking distance as a radius. However, the heading of the unmanned aerial vehicle in the tracking initial segment is often inconsistent with the expected heading, and a certain heading error exists. For this reason, in order to complete the tracking task of the unmanned aerial vehicle, the initial segment heading error needs to be corrected.
Aiming at the problem of correcting the course error, many scholars research the problem, and various methods can be adopted for tracking and guidance in the initial stage. Some of these researchers have conducted intensive studies based on Lyapunov Guidance Tracking, such as the references "free E W, Lawrence, Dale A, Morris, step. coordinated Stackoff Tracking of Moving Targets Using Lyapunov Guidance Fields [ J ]. Journal of Guidance Control & Dynamics,2008,31(2): 290. 306" introduced a Lyapunov Guidance Vector field method to maintain the desired Standoff Tracking radius. However, there is a time separation problem during the course of the heading and standoff radius convergence certification.
And other scholars measure flight parameters of the unmanned aerial vehicle in real time in a flight state through actual measurement equipment, so that the course of the unmanned aerial vehicle is corrected in real time. The document "Jiang F, Swindlehurst A L. optimization of UAV Heading for the group-to-Air Uplink [ J ]. IEEE Journal on Selected Areas in Communications,2012,30(5): 993-. The method comprises the following steps of identifying an actual course angle of an unmanned aerial vehicle according to a measurement result of an aviation data system and sending an attitude adjustment instruction to the unmanned aerial vehicle to finish course correction, wherein the method can effectively identify the course of the unmanned aerial vehicle and provide required data, but is difficult to realize.
In summary, although the existing method can solve the above problems to a certain extent, the existing method has a problem of time separation between the course convergence process and the unmanned aerial vehicle tracking convergence to the target circle, or has problems of complex system, difficulty in implementation and the like.
Disclosure of Invention
The invention aims to provide a method for correcting course errors of an unmanned aerial vehicle tracking target initial segment based on dynamic inversion, which can realize quick correction of large course errors existing in the unmanned aerial vehicle tracking target initial segment. The invention provides a dynamic inverse-based course error correction method for an unmanned aerial vehicle tracking target initial segment, which comprises the following steps of:
step S1, calculating an initial heading error
Tracking heading error psi of a target according to a two-dimensional spacee＝ψ-ψdCalculating an initial heading error psie0Where ψ is the actual heading of the drone, ψdThe expected heading of the unmanned aerial vehicle;
step S2, dynamic reverse heading correction is performed
The heading error psieMultiplying by feedback gain k, and adding the product into a feedforward term of the rotation rate of the guidance vector field to obtain the course angle change rate
Figure BDA0002188588980000021
Making course correction, wherein
Figure BDA0002188588980000022
K > 0 for a desired course angle rate of change;
step S3, updating course error and correcting
Updating the course error psi of the unmanned plane at the current position (x, y)eWhen there is a heading error ψeRepeating the step S2 to perform dynamic reverse heading correction until the heading error phieAnd finishing correction when approaching zero.
Preferably, the heading error ψeThe method for determining the approach to zero comprises the following steps: when psie/ψe0When the diameter is less than or equal to epsilon, determining the heading error psieApproaching zero, where ε is the feasible error.
Preferably, the feasible error epsilon is less than or equal to 3 percent. When the value of the feasible error epsilon is too small, the course error correction time is too long; when the feasible error epsilon is too large, although the course error correction time is shortened, the residual course error is still larger when the correction is completed.
Preferably, in the two-dimensional space, the unmanned aerial vehicle starts from the initial position, reaches the periphery of the target along the guidance track and then takes the target point O as the center，rdPerforming Stand-Off distance hover tracking on the target for the radius, where rdThe desired tracking radius. Various guidance methods can be adopted to track and guide the target from the initial position, and further a guidance track is generated. The preferred guidance method of the present invention is the Lyapunov guidance method.
Preferably, the desired heading ψdDetermined by the Lyapunov vector field, in particular
Figure BDA0002188588980000023
Wherein r is the distance between the drone and the target.
Preferably, the desired heading angle rate of change
Figure BDA0002188588980000031
Wherein u is0Is an initial flying speed, and u0Is a constant.
Preferably, based on the initial heading error ψe0The time of course correction is determined, and the aim is to select a nearby orbit as a flight route, so that the time length of course correction is shortened. The heading correction direction in step S2 is specifically:
when-pi < psie0When the heading is less than 0, the unmanned aerial vehicle carries out heading correction in the anticlockwise direction;
when 0 < psie0When the distance is less than pi, the unmanned aerial vehicle corrects the course clockwise;
when psie0When being 0, the unmanned aerial vehicle does not need course correction.
Preferably, when | | | ψe0When | ═ pi, that is, when the actual heading of the unmanned aerial vehicle is opposite to the expected heading of the unmanned aerial vehicle, the heading correction direction in step S2 is specifically: the hour direction of course correction is consistent with the hour direction of the initial direction of the guidance vector field. Namely: if the initial direction of the guidance vector field is clockwise, the unmanned aerial vehicle carries out course correction in the clockwise direction; and if the initial direction of the guidance vector field is anticlockwise, the unmanned aerial vehicle carries out course correction towards the anticlockwise direction.
Preferably, when the k value is increased, the time required for correcting the heading error of the unmanned aerial vehicle is shortened. That is, when the time required for heading error correction is to be shortened, the value of k can be increased.
Preferably, when the value k is reduced, the time required for correcting the heading error of the unmanned aerial vehicle is increased. When k value increases, when shortening course error correction time, can cause unmanned aerial vehicle to turn to the camber too big, the problem that the overload that unmanned aerial vehicle bore surpassed unmanned aerial vehicle load probably appears. At this moment, k value needs to be properly reduced to meet the requirement of the maximum overload bearing capacity of the unmanned aerial vehicle, and the time required for correcting the course error of the unmanned aerial vehicle is prolonged to a certain extent.
The invention relates to a course error correction method of an unmanned aerial vehicle tracking target initial segment based on dynamic inversion, which can realize rapid correction of a large course error existing in the unmanned aerial vehicle tracking target initial segment, wherein the course error is converged to a desired value in an exponential form, and the convergence speed is controllable; the method has the advantages of having overall stability besides convergence; in addition, the method has the advantages of continuously reducing overload, having low requirement on the load-resisting capacity of the unmanned aerial vehicle and the like in the course of quickly correcting the course error. The method well solves the problem of time separation between the course convergence process and the unmanned aerial vehicle tracking convergence to the target circle in the existing method; and the problems of complex system, difficult realization and the like in the existing method are solved, and the method has good effectiveness and practicability.
Drawings
FIG. 1 is a schematic view of an unmanned aerial vehicle tracking a target;
FIG. 2 is a flow chart of a course error correction method;
FIG. 3 is a diagram of a dynamic inverse system architecture;
FIG. 4 is a schematic view of an initial velocity direction and a terminal velocity direction of the UAV;
FIG. 5 is a diagram of a drone being guided to a target simulation along a desired heading;
FIG. 6 shows psi0When the flight path of the unmanned aerial vehicle is pi/3, simulating the flight path of the unmanned aerial vehicle;
FIG. 7 is a graph of course error trend when k is 0.3;
FIG. 8 is a simulation diagram of flight trajectories of the unmanned aerial vehicle at different k values;
FIG. 9 is a graph showing the variation trend of course error under different k values;
FIG. 10 is a comparative simulation of a course error correction method.
Detailed Description
For better understanding and implementing the present invention, specific embodiments are given below in conjunction with the accompanying drawings to describe in detail the method for correcting the heading error of the target initial segment tracked by the unmanned aerial vehicle based on the dynamic inverse method.
As shown in FIG. 1, the object of investigation of the present invention is in two dimensions
Figure BDA0002188588980000042
Starting from an initial position, the unmanned aerial vehicle reaches the periphery of a target along a guidance track and then takes a target point O as a center, rdPerforming Stand-Off distance hover tracking on the target for the radius, where rdThe desired tracking radius.
In the process of guiding to the periphery of the target, the guidance method adopted in the embodiment is a Lyapunov guidance method, and besides, various guidance methods can be adopted to track and guide to the target from the initial position, so that a guidance track is generated.
Under continuous time, the point-quality model of the drone may be represented as
Figure BDA0002188588980000041
Wherein (x, y) is the inertial coordinate of the unmanned aerial vehicle in the two-dimensional space, psi is the actual heading of the unmanned aerial vehicle, u1To command airspeed, u2Is the commanded heading. The model is a simplification of the physical characteristics of the real unmanned aerial vehicle.
As shown in fig. 2, in order to solve the above problem, the present invention provides a method for correcting a heading error of an unmanned aerial vehicle tracking target initial segment based on dynamic inversion, which mainly includes the following steps:
step S1, calculating an initial heading error
Tracking the heading error ψ of a target according to a two-dimensional spacee＝ψ-ψdCalculating an initial heading error psie0Where ψ is the actual heading of the drone, ψdThe expected heading of the unmanned aerial vehicle; the desired course is determined by the Lyapunov vector field, in particular
Figure BDA0002188588980000051
Wherein r is the distance between the drone and the target.
Step S2, performing dynamic reverse heading correction
The heading error psieMultiplying by feedback gain k, and adding the product into a feedforward term of the rotation rate of the guidance vector field to obtain the course angle change rate
Figure BDA0002188588980000052
Making course correction, wherein
Figure BDA0002188588980000053
Is the desired course angular rate of change; the expected heading angular rate of change
Figure BDA0002188588980000054
Wherein u is0To initial flying speed, u0Is a constant. The feedback gain k is more than 0; when the feedback gain k is increased, the time required by correcting the course error of the unmanned aerial vehicle is shortened; and when the feedback gain k value is reduced, the time required by correcting the course error of the unmanned aerial vehicle is increased.
The course correction direction is specifically as follows:
when-pi < psie0When the heading is less than 0, the unmanned aerial vehicle carries out heading correction in the anticlockwise direction.
When 0 < psie0When the angle is less than pi, the unmanned aerial vehicle carries out course correction in the clockwise direction.
When psie0When being 0, the unmanned aerial vehicle does not need course correction.
When | | | ψe0And when | | ═ pi, the hour direction of the course correction is consistent with the hour direction of the initial direction of the guidance vector field.
Step S3, updating and correcting the course error
Updating course error of unmanned aerial vehicle at current position (x, y)ψeWhen there is a heading error psieRepeating the step S2 to make dynamic reverse heading correction until psie/ψe0And completing correction when the epsilon is less than or equal to 3 percent, wherein the feasible error epsilon is less than or equal to.
For better understanding and implementation of the present invention, the following detailed derivation process and simulation verification of the present invention are described in detail. In an embodiment of the invention, when the drone is tracking a target, the Lyapunov vector field directs the drone to a circular tracking orbit around the target. Assume that the target is stationary, located at the origin (0, 0). Considering the Lyapunov function in a two-dimensional plane:
Figure BDA0002188588980000055
wherein, therein
Figure BDA0002188588980000056
Representing the distance between the drone and the target, then the drone linear velocity may be represented as
Figure BDA0002188588980000057
To achieve circular orbit tracking, the inertial velocity required for selection from the vector field is defined as follows:
Figure BDA0002188588980000061
in order to research the flight path characteristic of the unmanned aerial vehicle in the vector field, the derivation of the formula (2) can be obtained
Figure BDA0002188588980000062
From equation (5), the LaSa's principle of invariance is known: the flight trajectory of the drone converges progressively and stabilizes to the desired tracking circle. When r > rdWhen the radius is larger than the tracking radius value, the r value is reduced to the tracking radius value; when r < rdThe r value increases towards the tracking radius; when r is equal to rdR is constant, and unmanned plane
Figure BDA0002188588980000063
Fly around the desired tracking circle.
ψdRepresenting the desired heading along the Lyapunov vector field, can be determined by equation (4) as follows
Figure BDA0002188588980000064
By differentiating the above equation, the expected course angular rate of change (no course error at this time) along the Lyapunov vector field can be obtained:
Figure BDA0002188588980000065
the above is the case when the initial heading is aligned with the guidance vector field, however, generally the drone initial heading is not aligned with the Lyapunov vector field, but there is an initial heading error.
Assuming that the unmanned aerial vehicle has an initial heading error psie0And heading error psieIs expressed as
ψe＝ψ-ψd (8)
In order to correct errors of course, the invention adopts a course error correction method of an unmanned aerial vehicle tracking target initial segment based on dynamic inversion, and the course error psi is correctedeMultiplying by a feedback gain k and adding it to the feed forward term of the vector field rotation rate, at which time the heading angle rate u changes2Can be obtained by the following formula
Figure BDA0002188588980000066
In the formula (9), k is a feedback gain. The response of the whole closed loop system is a second-order system, and the dynamic inverse system structure is shown in figure 3.
For k > 0, the solution (9) yields an exponential convergence form of the heading error as
ψe(t)＝ψe0e-kt (10)
Wherein psie0＝ψe(0)，
Figure BDA0002188588980000071
In equations (9), (10), the parameter k controls the heading error convergence speed, and in order not to violate the turn rate constraint (drone maximum overload constraint), an appropriate value of k must be chosen so that an appropriate balance is achieved between the feedback term and the feedforward term in equation (9).
In the course error correction process of the unmanned aerial vehicle, the real-time course psi converges to an expected value by exponential property, and a Lyapunov function is taken to prove the stability of the process
Figure BDA0002188588980000072
The derivation of the above formula, parallel connection and vertical type (10) can be obtained
Figure BDA0002188588980000073
On the other hand, the value range
Figure BDA0002188588980000074
In that
Figure BDA0002188588980000075
In the following, the value of Δ is constant positive, so that within the above range, VψConverge to 0 in an exponential nature.
Since drone speed is set to the speed of the target tracking vector field, drone speed will gradually converge to the vector field. Meanwhile, it has been proved in the foregoing that the vector field is globally stable on the tracking circle, so that the whole flight process of the drone is also globally stable.
From equations (1) and (8), the kinetic equation of the drone can be expressed as
Figure BDA0002188588980000076
Note that the heading error ψ is referred to in equation (13)eThe matrix of (t) has a structure of a rotation matrix. In addition, when the heading error ψeAnd (t) when the time (t) is converged to zero, the rotation matrix becomes an identity matrix in an exponential form, and the unmanned aerial vehicle flies along the expected vector field at the moment.
According to equation (13), when a heading error exists, a desired heading angle change rate of
Figure BDA0002188588980000077
Here the expression for the desired heading angle rate is such that the first term is the desired heading angle rate along the guided vector field given in equation (7) and the second term is a reference to sin (ψ)eTerm of/2), and when ψeTowards zero, the value of the term also approaches zero.
As shown in fig. 4, the possible initial heading of the drone may be divided into two regions, region a and region B respectively. According to the double-rotation Lyapunov vector field definition, the area A is called a counterclockwise area, and the area B is called a clockwise area.
Typically, the actual initial heading will not be aligned with the guidance vector field, but will point in a direction within one of the regions in FIG. 4. Obviously, under the condition of no special precondition, the unmanned aerial vehicle selects a nearby track as a flight route, and the specific selection mode of the unmanned aerial vehicle is as follows:
assuming that the drone dynamics equation is given by equation (11) and constrained by drone kinematics, the airspeed input is set to a constant u0The heading speed input is given by equations (9) and (10). With the desired heading ψ at the initial point for the droned0The direction is a 0 reference, and when an initial course error exists, the actual course and the area where the actual course is located are divided as follows:
Figure BDA0002188588980000081
according to the literature ' Zhang Yi, Meng Yuan, Yang XiuXia ', an unmanned aerial vehicle obstacle avoidance algorithm [ J ] based on a double-rotation Lyapunov vector field, control and decision, 2018, v.33(8):173-181 ', the double-rotation Lyapunov vector field is defined, and the unmanned aerial vehicle with the actual course in the area A corrects the error in the anticlockwise direction and tracks the target; and the unmanned aerial vehicle with the actual heading in the area B corrects the error in the clockwise direction and tracks the target. Eventually, the drone will progressively converge to a standoff radius and hover around the target at a constant angular velocity.
When the heading area of the unmanned aerial vehicle is divided, psi e00 and ψ | |e0Two special cases of | ═ pi are eliminated. Wherein psie0When the initial course of the unmanned aerial vehicle is aligned with the guidance vector field, no course error correction is needed under the condition; phie0And | pi indicates that the actual course of the unmanned aerial vehicle is opposite to the course of the guidance vector field, and the correction direction of the unmanned aerial vehicle under the condition needs to be determined according to the area where the actual direction of the initial direction of the guidance vector field is located: if the initial direction of the guidance vector field is located in the area A, the unmanned aerial vehicle corrects errors in the clockwise direction; on the contrary, if the initial direction of the guidance vector field is in the area B, the unmanned aerial vehicle performs error correction in the counterclockwise direction.
The method of the present invention can solve the time metric separation problem between heading convergence and standoff radius convergence, as demonstrated in detail below.
In order to simplify the proving process, the situation of the counterclockwise Lyapunov vector field direction is selected during proving, namely the actual initial course of the unmanned aerial vehicle is located in the area A.
In order to prove the convergence of the unmanned aerial vehicle in the initial tracking segment, the value range of r (t) of the unmanned aerial vehicle in the area A is solved under polar coordinates.
For convenience of analysis, before heading error analysis, an angle phi is introduced: since x is rcos θ and y is rsin θ, the angle Φ can be obtained according to the following formula:
Figure BDA0002188588980000082
the angle psi can be obtained from the formula (5)dThe relationship between theta and phi is as follows
ψd＝θ-φ+π (16)
The kinetic equation of the unmanned aerial vehicle can be expressed in a polar coordinate form as
Figure BDA0002188588980000091
The kinetic equation expressing equation (17) as r is as follows:
Figure BDA0002188588980000092
note that according to formula (15), when r → ∞, Φ ∈ [0, π), Φ → 0; when r is rdWhen phi is pi/2; when r → 0, φ → π.
For the unmanned aerial vehicle with the initial course error of phi ≦ psie0≦ 0 (initial heading in region A), an upper bound for parameter r may be obtained (assuming r is in region A)0＞rd)：
r(t)≤r0+u0trmax＝rsup (19)
Wherein, trmaxFor the moment r reaches its maximum value, the expression is
Figure BDA0002188588980000093
According to the formula (18), r (t) ≧ r is given for all t ≧ 0d。
The Lyapunov function is adopted to prove the convergence of the tracking motion of the unmanned aerial vehicle under the condition that the course error exists, and the Lyapunov function is considered for the problem
Figure BDA0002188588980000094
For lambda > 0, the flight path of the unmanned aerial vehicle can be obtained according to the equations (17) and (18)
Figure BDA0002188588980000097
Expression formula
Figure BDA0002188588980000095
Suppose-pi ≦ psie0≤0，
Figure BDA0002188588980000096
Has the following range
Figure BDA0002188588980000101
The parameter λ is selected according to:
Figure BDA0002188588980000102
can obtain
Figure BDA0002188588980000103
Wherein α > 0, and therefore, represented by formula (17)
Figure BDA0002188588980000104
Therefore, the method solves the problem of time measurement separation between course convergence and standoff radius convergence, namely the connection between the course convergence process of the unmanned aerial vehicle and time. The above proof is limited to the initial heading of region a, for which case the convergence can be verified by a similar method due to the different direction of rotation of the vector field.
Example 1:
this implementationThe method comprises the following steps of tracking and setting simulation initial conditions aiming at the condition that the initial course of the unmanned aerial vehicle is not aligned with the expected course: the target is located at the origin (0, 0); the initial position of the unmanned aerial vehicle is (6000m ); initial actual heading psi of drone0Pi/3; the expected flight heading at the initial position of the unmanned aerial vehicle is defined by the Lyapunov vector field
Figure BDA0002188588980000105
Then the initial course error of the target tracked by the unmanned aerial vehicle is
Figure BDA0002188588980000106
In order to clearly show the flight track, the unmanned aerial vehicle flight speed u is set in the implementation0500 m/s; the desired tracking radius is 2000 m; the heading error correction feasible error is 3%.
First, a Lyapunov vector field method is applied to guide the drone from an initial position onto a target desired tracking track along a vector field direction, as shown in fig. 5.
Initial actual course psi of unmanned aerial vehicle that sets up in this embodiment0And pi/3, and the feedback gain k is 0.3, by adopting the course error correction method, the course error of the unmanned aerial vehicle is converged in an exponential form, so that the actual course is finally aligned with the expected course, the correction of the course error is completed, and the tracking track is shown in fig. 6. Fig. 7 is a schematic diagram of the change of the heading error of the unmanned aerial vehicle during the flight process along the actual heading when the feedback gain k is 0.3. As can be seen from fig. 7, the initial heading error of the drone during flight is 2.4186, and as the heading error is corrected, the heading error is corrected exponentially to within 0.0725, and the time is 11.8 s. After the unmanned aerial vehicle completes error correction, the speed direction is aligned with the direction of the expected vector field, and then the unmanned aerial vehicle flies along the direction of the expected vector field until an upper target is tracked.
Example 2:
when the feedback gain k takes different values, the convergence speed of the heading error is also different. The present embodiment is a simulation of the convergence speed of the heading error under different feedback gains k.
Simulation conditions of the present embodiment andexample 1 same, but for k1＝0.3、k20.6 and k3The simulation was performed at 2, and the simulation results are shown in fig. 8. The schematic diagram of the heading error change under different feedback gains is shown in fig. 9.
TABLE 1 correction time at different k values
Figure BDA0002188588980000111
From the simulation results of fig. 8 and 9, it can be seen that as the feedback gain k is increased, the time required for the drone to correct the heading error is reduced, i.e., the drone heading can be quickly aligned with the desired direction of the guidance vector field.
It should be noted that the increase of k value may cause the steering curvature of the drone to be too large, and the problem that the overload borne by the drone exceeds the load of the drone may occur. Therefore, when the actual course is corrected, the maximum overload bearing capacity of the unmanned aerial vehicle is considered, and the feedback gain k is reasonably valued.
Example 3:
in the embodiment, the course error of the initial section of the unmanned aerial vehicle is corrected by selecting an arc method, and the correction is compared with the simulation of the method.
The method comprises the steps of enabling the unmanned aerial vehicle to fly along a circular track when the unmanned aerial vehicle starts, and continuously comparing the error between the current course of the unmanned aerial vehicle and the expected course of a real-time position in the flying process. Clearly, there is a point on the arc of a circle at which the actual flight heading of the drone is aligned with the desired heading of the Lyapunov vector field.
In order to compare the performance of the method of the present invention and the performance of the two course error correction methods using the arc method, in this embodiment, k is 1, and the minimum turning radius of the unmanned aerial vehicle calculated under the curvature condition is rmin206.9 m. In order to ensure that the course error can be corrected in the shortest time when the unmanned aerial vehicle adopts the arc method, the minimum turning radius r of the unmanned aerial vehicle calculated in the invention is takenminThe radius is corrected. Then, a simulation test was performed under the conditions, and the results are shown in FIG. 10。
As can be seen from FIG. 10, the two course correction methods fly at the same turning rate when the UAV starts, wherein when the course error is corrected by the method of the present invention, the curvature of the flight path of the UAV is reduced at a faster speed; and when correcting course errors by using an arc method, the unmanned aerial vehicle keeps the maximum curvature to fly until phase angle correction is completed.
The time for completing the error correction of the unmanned aerial vehicle under the two heading error correction methods is shown in table 2:
TABLE 2 course error correction time under different correction methods
Figure BDA0002188588980000112
Figure BDA0002188588980000121
According to the simulation result, the course error correction time and the unmanned aerial vehicle track length are not obviously different under the same available overload condition of the unmanned aerial vehicle by the method and the arc method. However, under the arc method, the unmanned aerial vehicle keeps a large-curvature turn at the initial section to align the course, which undoubtedly puts higher requirements on the initial flight section of the unmanned aerial vehicle; compared with the prior art, the method can gradually reduce the overload borne by the unmanned aerial vehicle in the course error correction process, and does not sacrifice much flight path length of the unmanned aerial vehicle and error correction time.
Finally, it should be noted that the above-mentioned embodiments are only preferred embodiments of the present invention, and not intended to limit the present invention, and although the present invention has been described in detail with reference to the foregoing examples, it will be apparent to those skilled in the art that modifications and equivalents may be made to the technical solutions described in the foregoing examples, or some technical features may be substituted. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims (9)

1. The method for correcting the course error of the target tracking initial section of the unmanned aerial vehicle based on the dynamic inversion is characterized by comprising the following steps of:
step S1, calculating an initial heading error
Tracking heading error psi of a target according to a two-dimensional spacee＝ψ-ψdCalculating an initial heading error psie0Where ψ is the actual heading of the drone, ψdThe expected heading of the unmanned aerial vehicle;
step S2, dynamic reverse heading correction is performed
The heading error psieMultiplying by feedback gain k, and adding the product into a feedforward term of the rotation rate of the guidance vector field to obtain the course angle change rate
Figure FDA0003541823820000011
Making course correction, wherein
Figure FDA0003541823820000012
K > 0 for a desired course angle rate of change;
step S3, updating course error and correcting
Updating the course error psi of the unmanned plane at the current position (x, y)eWhen there is a heading error psieRepeating the step S2 to perform dynamic reverse heading correction until the heading error phieFinishing correction when approaching zero;
the method for tracking the target specifically comprises the following steps: in a two-dimensional space, starting from an initial position, the unmanned aerial vehicle reaches the periphery of a target along a Lyapunov guidance track, and taking a target point O as a center, rdPerforming Stand-Off distance hover tracking on the target for the radius, where rdThe desired tracking radius.
2. Correction method according to claim 1, characterized in that the heading error ψeThe method for determining the approach to zero comprises the following steps: when psie/ψe0When the diameter is less than or equal to epsilon, determining the heading error psieApproaching zero, where ε is the feasible error.
3. The correction method as claimed in claim 2, wherein the feasible error e is less than or equal to 3%.
4. Correction method as claimed in one of claims 1 to 3, characterized in that said desired heading is
Figure FDA0003541823820000013
Wherein r is the distance between the drone and the target.
5. Correction method as claimed in one of claims 1 to 3, characterized in that said desired course angular rate of change
Figure FDA0003541823820000014
Wherein u is0To initial flying speed, u0Is a constant number；
Figure FDA0003541823820000015
r is the distance between the drone and the target.
6. The correction method according to any one of claims 1 to 3, wherein the direction of the heading correction in step S2 is:
when-pi < psie0When the heading is less than 0, the unmanned aerial vehicle carries out heading correction in the anticlockwise direction;
when 0 < psie0When the distance is less than pi, the unmanned aerial vehicle corrects the course clockwise;
when psie0When being 0, the unmanned aerial vehicle does not need course correction.
7. The correction method according to any one of claims 1 to 3, wherein the direction of the heading correction in step S2 is:
when | | | ψe0And when | | -. pi, the direction of the pointer of course correction is consistent with the direction of the pointer of the initial direction of the guidance vector field.
8. The correction method according to any one of claims 1 to 3, wherein when the value of k is increased, the time required for the course error correction of the unmanned aerial vehicle is shortened.
9. The correction method according to any one of claims 1 to 3, wherein a time required for the course error correction of the unmanned aerial vehicle increases when the value of k is decreased.
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