CN112099527A - Control method and system for autonomous landing of mobile platform of vertical take-off and landing unmanned aerial vehicle - Google Patents

Control method and system for autonomous landing of mobile platform of vertical take-off and landing unmanned aerial vehicle Download PDF

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CN112099527A
CN112099527A CN202010978134.6A CN202010978134A CN112099527A CN 112099527 A CN112099527 A CN 112099527A CN 202010978134 A CN202010978134 A CN 202010978134A CN 112099527 A CN112099527 A CN 112099527A
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landing
mobile platform
aerial vehicle
unmanned aerial
vertical take
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CN112099527B (en
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缪志强
林杰
王耀南
张辉
钟杭
刘理
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Hunan University
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    • G05D1/10—Simultaneous control of position or course in three dimensions
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Abstract

The invention discloses a control method and a system for autonomous landing of a vertical take-off and landing unmanned aerial vehicle on a mobile platform. The inversion control method based on error transformation effectively solves the problem of 'combined explosion' in other inversion control methods, ensures that an output error converges to a predefined residual set along an absolute decay time function, and ensures that the maximum overshoot is lower than a preset level. The system comprises a vertical take-off and landing unmanned aerial vehicle, a monocular vision device, an autonomous landing control module, an AprilTag vision reference system and a mobile platform, wherein the load of the vertical take-off and landing unmanned aerial vehicle is low through a minimum of sensors and a low-complexity control method, and the autonomous landing maneuverability is strong.

Description

Control method and system for autonomous landing of mobile platform of vertical take-off and landing unmanned aerial vehicle
Technical Field
The invention relates to the field of autonomous landing of a vertical take-off and landing unmanned aerial vehicle, in particular to a control method and a system for autonomous landing of a vertical take-off and landing unmanned aerial vehicle on a mobile platform.
Background
Vertical take-off and landing drones find wide application in civilian and military settings, including industrial inspection, aerial photography, communication relaying, surveillance, search and rescue, and the like. The autonomous landing of the unmanned aerial vehicle is a process that the airborne automatic flight system completely controls the aircraft to land and fly. In the process, the operation is complex, the ground interference factors are many, and the unmanned aerial vehicle is required to have high-precision autonomous positioning navigation and robust landing trajectory tracking capability.
Currently, more pose estimation methods for static platforms are being studied, but considering the more general application, the difficulty of autonomous landing control systems is further increased when a vertical take-off and landing drone lands on a mobile platform.
When an unmanned aerial vehicle autonomous landing control system is designed, the pose of a landing target relative to a local environment needs to be accurately estimated, and meanwhile, a controller meeting landing task constraints is designed. However, because the effective load characteristic of the vertical take-off and landing unmanned aerial vehicle is low, the airborne sensor and the calculation capability of the vertical take-off and landing unmanned aerial vehicle are limited, and how to design an autonomous landing control system with higher precision under the conditions of low load and low calculation capability becomes a problem which needs to be solved urgently.
Disclosure of Invention
The invention aims to overcome the defects in the prior art and provide a control method and a control system for autonomous landing of a vertical take-off and landing unmanned aerial vehicle on a mobile platform, so that the control precision of the unmanned aerial vehicle is improved, airborne sensing tools are simplified, and the complexity of the control method is reduced.
The invention further aims to solve the technical problem of providing a system comprising the control method on the basis of providing the control method for the autonomous landing.
The technical scheme adopted by the invention for solving the technical problem is as follows: the control method for the autonomous landing of the vertical take-off and landing unmanned aerial vehicle on the mobile platform comprises the following steps:
s1: establishing a dynamic model of the vertical take-off and landing unmanned aerial vehicle, a kinematic model of the mobile platform and a relative kinematic model of the vertical take-off and landing unmanned aerial vehicle and the mobile platform;
s2: designing a predetermined performance specification error transformation method;
s3: designing to obtain a position control law of the vertical take-off and landing unmanned aerial vehicle by adopting an inversion control method based on a predetermined performance standard error transformation method;
s4: designing a desired rotation matrix, and a desired angular velocity;
s5: and calculating the moment required by the vertical take-off and landing unmanned aerial vehicle for automatic landing on the mobile platform, and realizing autonomous landing control.
Further, the step S1 includes the following steps:
s11: establishing a dynamic model of the vertical take-off and landing unmanned aerial vehicle, wherein the model is described as follows:
Figure BDA0002686533250000021
Figure BDA0002686533250000022
Figure BDA0002686533250000023
Figure BDA0002686533250000024
wherein p ═ px,py,pz]ΤIs the three-dimensional position of the vertical take-off and landing unmanned aerial vehicle in a world coordinate system,
Figure BDA0002686533250000025
is the first differential of p, v ═ vx,vy,vz]ΤIs vertically lifted and landed withoutLinear speed of the man-machine under the world coordinate system,
Figure BDA0002686533250000026
is the first differential of v, Ω ═ Ωx,Ωy,Ωz]ΤThe angular velocity of the vertical take-off and landing unmanned aerial vehicle under the body coordinate system is shown as an oblique symmetric matrix of the angular velocity, wherein R omega ^ R multiplied by omega, m and J ═ diag (J)1,J2,J3) Respectively representing the mass and inertia matrix of the VTOL UAV, g is the gravitational acceleration, i3＝[0,0,1]ΤIs a unit vector, f and τ ═ τx,τy,τz]ΤThrust and torsion are respectively provided, R is a rotation matrix, and the rotation matrix is obtained by rotating the vertical take-off and landing unmanned aerial vehicle along Euler angles psi, phi and theta, and psi, phi and theta are respectively expressed as a yaw angle, a roll angle and a pitch angle;
s12: establishing a kinematic model of the mobile platform, wherein the model is described as follows:
Figure BDA0002686533250000027
wherein r isl＝[xl,yl,h]TRepresenting the position of the mobile platform in the world coordinate system, xlIs the abscissa of the mobile platform, ylIs the ordinate of the mobile platform, h is the height of the mobile platform, θlIs the rotation angle, v, of the moving platform body coordinate system relative to the world coordinate systemlAnd ωlRespectively representing the linear velocity and the angular velocity of the mobile platform;
s13: establishing a relative kinematics model of the vertical take-off and landing unmanned aerial vehicle and the mobile platform, wherein the model description is as follows:
rlp＝p-rl (6)
wherein r islp＝[xlp,ylp,zlp]ΤIs the real-time relative three-dimensional position of the vertical take-off and landing unmanned aerial vehicle and the mobile platform.
Further, the predetermined performance error transformation method of step S2 is:
Figure BDA0002686533250000031
therein, ζk＝ek/ρk，ekIn order to define the error, the error is,kfor the transformed error, pkFor the error performance function, k ∈ {1, 2, … 6 }.
Further, the step S3 includes the following steps:
s31: the monocular vision device carried by the vertical take-off and landing unmanned aerial vehicle captures April tag information in an April tag vision system arranged on the mobile platform, and the real-time relative three-dimensional position r between the vertical take-off and landing unmanned aerial vehicle and the mobile platform is obtained by a homography matrix according to the known physical size of the April tag vision systemlp＝[xlp,ylp,zlp]ΤAnd attitude information;
s32: defining a position error ep＝[e1,e2,e3]ΤComprises the following steps:
Figure BDA0002686533250000032
wherein the content of the first and second substances,
Figure BDA0002686533250000033
indicating a desired relative position;
s33: obtaining a transformed position error according to a predetermined performance specification error transformation methodp＝[1,2,3]Τ；
S34: the first order differential expression is obtained from the transformed position error:
Figure BDA0002686533250000034
wherein the content of the first and second substances,
Figure BDA0002686533250000035
is rlAnd Q ═ diag (Q), and1,q2,q3) And η ═ η (η)1,η2,η3)ΤAre defined as:
Figure BDA0002686533250000036
Figure BDA0002686533250000037
Figure BDA0002686533250000038
is rhokFirst order differentiation of;
s35: setting the linear velocity of the virtually-expected VTOL UAV to
Figure BDA0002686533250000039
According to equation (9), the linear velocity control law of the virtual expected vertical unmanned plane is obtained as follows:
Figure BDA00026865332500000310
wherein, K1、K2Are the gains of the intermediate controller;
s36: defining a speed error ev＝[e4,e5,e6]ΤComprises the following steps:
Figure BDA0002686533250000041
s37: obtaining a transformed speed error according to a predetermined performance error transformation methodv＝[4,5,6]ΤThe first order differential expression of the converted speed error can be obtained:
Figure BDA0002686533250000042
wherein Q isv＝diag(q4,q5,q6) And ηv＝(η4,η5,η6)ΤAre defined as:
Figure BDA0002686533250000043
Figure BDA0002686533250000044
s38: according to equations (14) and (2), the position control law is designed as follows:
u＝-(K3Qv Τ+Qv -1K4)v (17)
wherein, K3,K4Is a positive definite matrix.
Further, the step S4 specifically includes the following steps:
s41: setting the desired rotation angle psi*＝0；
S42: according to the thrust vector F-mgi3-mu and desired rotation angle vector y ═ cos ψ*,sinψ*,0]ΤDesign the desired rotation matrix as Rd＝[r1,r2,r3]Wherein
Figure BDA0002686533250000045
S44: the first order differential of the thrust vector is expressed as
Figure BDA0002686533250000046
Using a first order low pass filter to solve
Figure BDA0002686533250000047
The first order low pass filter is of the form:
Figure BDA0002686533250000048
wherein, KαIs a positive definite symmetric matrix;
s43: the desired angular velocity is expressed as:
Figure BDA0002686533250000051
wherein, (.)∨Denoted as (·) inverse operation,
Figure BDA0002686533250000052
rotating the matrix R as desireddThe first order differential of (a) is,
Figure BDA0002686533250000053
expressed as:
Figure BDA0002686533250000054
I3×3is a 3 rd order identity matrix.
Further, the step S5 specifically includes the following steps:
s51: rewriting formula (2) as:
Figure BDA0002686533250000055
Figure BDA0002686533250000056
according to equation (17), the saturation thrust of the vtol drone is designed as:
Figure BDA0002686533250000057
s52: the error term of the rotation matrix is defined as follows:
Figure BDA0002686533250000058
eΩ＝Ω-RΤRdΩd (26)
wherein R isdFor the desired rotation matrix, R is the actual rotation matrix, eRIs the rotation matrix error; omegadFor desired angular velocity, Ω is the actual angular velocity, eΩIs the angular velocity error;
s53: the moment of getting VTOL unmanned aerial vehicle is with convolution (4), equation (25), equation (26):
τ＝-KReR-KΩeΩ+Ω×JΩ (27)
wherein, KR、KΩThe attitude control gain.
The invention also provides a system for the vertical take-off and landing unmanned aerial vehicle to land on the mobile platform independently, the system comprises the vertical take-off and landing unmanned aerial vehicle, a monocular vision device, an independent landing control module, an Apriltag vision reference system and the mobile platform, wherein:
the monocular vision device is connected with the autonomous landing control module and sends the acquired image information to the autonomous landing control module; the autonomous landing control module is connected with the vertical take-off and landing unmanned aerial vehicle and sends a control instruction to the vertical take-off and landing unmanned aerial vehicle; an Apriltag visual reference system is arranged on the mobile platform; the aprilatag visual reference system is within the range of viewing angles of a monocular visual device.
Further, the vertical lift unmanned aerial vehicle is a quad-rotor unmanned aerial vehicle.
Further, the monocular vision device is a monocular camera.
The invention has the beneficial effects that: the precise three-dimensional position and the posture of the mobile platform relative to the vertical take-off and landing unmanned aerial vehicle are estimated by adopting a monocular camera and an AprilTag vision reference system, so that the number of airborne sensors is simplified, and the airborne load of the vertical take-off and landing unmanned aerial vehicle is low; meanwhile, a preset performance error transformation method is designed, the output error is guaranteed to be converged to a predefined residual set along an absolute decay time function, the maximum overshoot is lower than a preset level, the inversion control method based on the error transformation effectively solves the problem of common term combination explosion in other inversion control methods, the estimation precision is improved, and the maneuverability of the vertical lifting unmanned aerial vehicle in autonomous landing of a mobile platform is effectively improved.
Drawings
Fig. 1 is a flow chart of a control method for autonomous landing of a vertical take-off and landing unmanned aerial vehicle on a mobile platform according to the present invention;
fig. 2 is a schematic diagram of a system framework of a control method for autonomous landing of a vertical take-off and landing unmanned aerial vehicle on a mobile platform according to the present invention;
fig. 3 is a three-dimensional schematic diagram of an autonomous landing trajectory of a control method for autonomous landing of a vertical take-off and landing unmanned aerial vehicle on a mobile platform according to the present invention;
FIG. 4 shows a relative position error e of a control method for autonomous landing of a VTOL UAV on a mobile platform according to the present invention1A convergence process diagram;
FIG. 5 shows a relative position error e of a control method for autonomous landing of a VTOL UAV on a mobile platform according to the present invention2A convergence process diagram;
FIG. 6 shows a relative position error e of a control method for autonomous landing of a VTOL UAV on a mobile platform according to the present invention3A convergence process diagram;
FIG. 7 shows a velocity error e of a VTOL UAV, which is a control method for the VTOL UAV to autonomously land on a mobile platform according to the present invention4A convergence process diagram;
FIG. 8 shows a velocity error e of a VTOL UAV, which is a control method for the VTOL UAV to autonomously land on a mobile platform according to the present invention5A convergence process diagram;
FIG. 9 shows a VTOL UAV provided by the present invention on a mobile platformControl method for autonomous landing and vertical take-off and landing unmanned aerial vehicle speed error e6A convergence process diagram;
fig. 10 is a schematic diagram of a system for autonomous landing of a vertical take-off and landing drone on a mobile platform according to the present invention.
Detailed Description
In order to make the technical solutions of the present invention better understood, the present invention is further described in detail below with reference to the accompanying drawings.
Referring to fig. 1 and fig. 2, fig. 1 is a block flow diagram of a control method for autonomous landing of a vertical take-off and landing unmanned aerial vehicle on a mobile platform, which is provided by the present invention, and includes the following steps:
s1: establishing a dynamic model of the vertical take-off and landing unmanned aerial vehicle, a kinematic model of the mobile platform and a relative kinematic model of the vertical take-off and landing unmanned aerial vehicle and the mobile platform;
s2: designing a predetermined performance error transformation method;
s3: designing to obtain a position control law of the vertical take-off and landing unmanned aerial vehicle by adopting an inversion control method based on a predetermined performance error transformation method;
s4: designing an expected rotation matrix and an expected angular speed;
s5: and calculating the moment required by the vertical take-off and landing unmanned aerial vehicle for automatic landing on the mobile platform.
Further, the step S1 includes the following steps:
s11: establishing a dynamic model of the vertical take-off and landing unmanned aerial vehicle, wherein the model is described as follows:
Figure BDA0002686533250000071
Figure BDA0002686533250000072
Figure BDA0002686533250000073
Figure BDA0002686533250000074
wherein p ═ px,py,pz]ΤIs the three-dimensional position of the vertical take-off and landing unmanned aerial vehicle in the world coordinate system, v ═ vx,vy,vz]ΤIs the linear velocity of the vertical take-off and landing unmanned aerial vehicle under the world coordinate system, wherein omega is [ omega ]x,Ωy,Ωz]ΤThe angular velocity of the vertical take-off and landing unmanned aerial vehicle under the body coordinate system is shown as an oblique symmetric matrix of the angular velocity, wherein R omega ^ R multiplied by omega, m and J ═ diag (J)1,J2,J3) Respectively representing the mass and inertia matrix of the vertical take-off and landing unmanned aerial vehicle, setting m to be 1.5, J to be diag (0.0095, 0.0095 and 0.019), g to be gravity acceleration, i3＝[0,0,1]ΤIs a unit vector with thrust and torque being f and tau, respectivelyx,τy,τz]Τ. The rotation matrix R is obtained by rotating the vtol drone along the euler angles ψ, Φ, and θ, which are denoted as the yaw angle, the roll angle, and the pitch angle, respectively.
S12: considering incomplete constraint, establishing a kinematic model of the mobile platform, wherein the model is described as follows:
Figure BDA0002686533250000081
wherein r isl＝[xl,yl,h]TRepresenting the position of the mobile platform in the world coordinate system, h is the height of the mobile platform, θlIs the rotation angle, v, of the moving platform body coordinate system relative to the world coordinate systemlAnd ωlRepresenting linear and angular velocities of the moving platform, respectively, set vl＝0.4，ωl＝0.2。
S13: establishing a relative kinematics model of the vertical take-off and landing unmanned aerial vehicle and the mobile platform, wherein the model description is as follows:
rlp＝p-rl (6)
wherein r islp＝[xlp,ylp,zlp]ΤIs the relative three-dimensional position of the vertical take-off and landing unmanned aerial vehicle and the mobile platform.
Further, the predetermined performance error transformation method of step S2 is:
Figure BDA0002686533250000083
therein, ζk＝ek/ρk，ekIn order to define the error, the error is,kfor the transformed error, pkFor the error performance function, k ∈ {1, 2, … 6 };
the design method comprises the following steps: first, define the error as ek(t) using the error performance function ρ to ensure that the error converges to a predefined set of residuals along the time function of the absolute decayk(t) defining a relative error ek(t) boundary:
Figure BDA0002686533250000082
then, the error performance function ρk(t) is defined by the formula:
ρk(t)＝(ρk(0)-ρ∞)e-lt+ρ∞ (9)
where ρ isk(0) Represents the maximum error allowed for the start, and the initial error satisfies 0 < | ek(0)|＜ρk(0) Exponential coefficient l > 0, rho∞Indicating the steady state maximum error. Position maximum allowable steady state error is set to ρ∞0.02, the convergence rate converges exponentially with an exponential coefficient of 1, and the maximum allowable steady state error of the speed is ρ∞The convergence rate converges exponentially with an exponential coefficient of 1 at 0.05.
To design an error transform with a predetermined performance specification, the error is set as follows:
ek(t)＝ρk(t)T(k) (10)
wherein T: (k) Is a smooth continuous monotonically increasing function and satisfies:
Figure BDA0002686533250000091
according to the above requirements, T: (k) Expressed as:
Figure BDA0002686533250000092
definition ζk＝ek/ρkObtaining T (in accordance with formula (12))k) Is expressed as:
Figure BDA0002686533250000093
further, the estimation of the accurate three-dimensional position and the attitude of the mobile platform relative to the VTOL UAV is to carry a monocular camera through the VTOL UAV, set a visual Apriltag (visual reference system) mark on the mobile platform, and obtain the relative position r between the mobile platform and the VTOL UAV through a homography matrix according to the physical size of the known marklp＝[xlp,ylp,zlp]ΤWith attitude, obtained rlp＝[2,2,1.7]Τ。
Further, the inversion control method of step S3 through the predetermined performance error transformation function includes the following steps:
s31: the monocular vision device carried by the vertical take-off and landing unmanned aerial vehicle captures April tag information in an April tag vision system arranged on the mobile platform, and the real-time relative position r between the mobile platform and the vertical take-off and landing unmanned aerial vehicle is obtained by a homography matrix according to the known physical size of the April taglp＝[xlp,ylp,zlp]ΤAnd attitude information, r acquired by the embodimentlp＝[2,2,1.7]Τ；
S32: defining a position error ep＝[e1,e2,e3]ΤComprises the following steps:
Figure BDA0002686533250000101
wherein the content of the first and second substances,
Figure BDA0002686533250000102
indicating a desired relative position, the desired relative position having an initial value of
Figure BDA0002686533250000103
S33: obtaining a transformed position error according to a predetermined performance error transformation methodp＝[1,2,3]Τ；
S34: the transformation error is subjected to a first order differential expression to obtain:
Figure BDA0002686533250000104
wherein the content of the first and second substances,
Figure BDA0002686533250000105
is rlAnd Q ═ diag (Q), and1,q2,q3) And η ═ η (η)1,η2,η3)ΤAre defined as:
Figure BDA0002686533250000106
Figure BDA0002686533250000107
Figure BDA0002686533250000108
is rhokFirst order differentiation of;
s35: assume that a virtual speed control variable is defined as
Figure BDA0002686533250000109
According to equation (15), the linear velocity control law of the virtual expected vertical unmanned plane is obtained as follows:
Figure BDA00026865332500001010
wherein, K1,K2Is a positive definite matrix, is the gain of the intermediate controller, and is set to K1Biag (0.01, 0.01, 0.01) and K2＝diag(2，2，2)，Q＝diag(q1,q2,q3)，pIs the transformed position error;
s36: defining a speed error ev＝[e4,e5,e6]ΤComprises the following steps:
Figure BDA00026865332500001011
s37: obtaining a transformed speed error according to a predetermined performance error transformation methodv＝[4,5,6]ΤThe first order differential expression of the converted speed error can be obtained:
Figure BDA00026865332500001012
wherein Q isv＝diag(q4,q5,q6) And ηv＝(η4,η5,η6)ΤAre defined as:
Figure BDA00026865332500001013
Figure BDA0002686533250000111
s38: according to equations (20) and (2), the position control law is designed as follows:
u＝-(K3Qv Τ+Qv -1K4)v (23)
wherein, K3,K4Is a positive definite matrix, is the gain of the position controller, and is set to K3Biag (0.01, 0.01, 0.01) and K4＝diag(10，10，10)。
Further, the step S4 specifically includes the following steps:
s41: considering that the physical structure of the quad-rotor unmanned aerial vehicle is symmetrical, when the quad-rotor unmanned aerial vehicle lands on a mobile platform, the rotation angle does not influence the performance requirement of autonomous landing, and an expected rotation angle psi is set*＝0。
S42: according to the thrust vector F-mgi3-mu and desired rotation angle vector y ═ cos ψ*,sinψ*,0]ΤDesign the desired rotation matrix as Rd＝[r1,r2,r3]Wherein
Figure BDA0002686533250000112
S43: the desired angular velocity is expressed as:
Figure BDA0002686533250000113
wherein, (.)∨Inverse operation, denoted (·) such that
Figure BDA0002686533250000114
First order differential of the desired rotation matrix
Figure BDA0002686533250000115
Is represented as follows:
Figure BDA0002686533250000116
s44: the first order differential of the thrust vector is expressed as
Figure BDA0002686533250000117
We use a first order low pass filter to solve
Figure BDA0002686533250000118
The first order low pass filter is of the form:
Figure BDA0002686533250000119
wherein, KαIs a positive definite symmetric matrix, and sets K for the gain of the low-pass filterα＝0.01，I3×3Is a 3 rd order identity matrix.
Further, the step S5 specifically includes the following steps:
s51: rewriting formula (2) as:
Figure BDA0002686533250000121
Figure BDA0002686533250000122
according to equation (23), the saturation thrust of the vtol drone is designed as:
Figure BDA0002686533250000123
s45: the error term of the rotation matrix is defined as follows:
Figure BDA0002686533250000124
eΩ＝Ω-RΤRdΩd (32)
wherein R isdFor the desired rotation matrix, R is the actual rotation matrix, eRIs the rotation matrix error; omegadFor desired angular velocity, Ω is the actual angular velocity, eΩIs the angular velocity error;
s52: convolution (4), formula (31), formula (32), the torsion design that obtains VTOL unmanned aerial vehicle is:
τ＝-KReR-KΩeΩ+Ω×JΩ (33)
gain setting of attitude controller is KRBiag (150, 150, 150) and KΩ＝diag(1.5，1.5，1.5)。
Referring to fig. 3, a complete three-dimensional trajectory of autonomous landing of a vertical lift drone controlled by the above method is shown, wherein Q issAnd PsRespectively representing the initial positions of the vertically-elevating drone and the mobile platform. Referring to fig. 4, 5, and 6, the relative position error converges rapidly along the absolute decay time function, and referring to fig. 7, 8, and 9, the velocity error converges rapidly along the absolute decay time function. The results show that the algorithm for the vertical take-off and landing unmanned aerial vehicle to move independently has good transient and steady-state performances.
Referring to fig. 10, there is provided a system for autonomous landing of a vertical take-off and landing drone on a mobile platform, the system including a vertical take-off and landing drone 1, a monocular vision device 2, an autonomous landing control module 3, an aprilatag vision reference system 4, a mobile platform 5, wherein: the monocular vision device 2 is connected with the autonomous landing control module 3, and the monocular vision device 2 sends acquired image information to the autonomous landing control module 3; the autonomous landing control module 3 is connected with the vertical take-off and landing unmanned aerial vehicle 1 and sends a control instruction to the vertical take-off and landing unmanned aerial vehicle 1; an Apriltag visual reference system 4 is arranged on the mobile platform 5;
further, the vertical lift unmanned aerial vehicle is a quad-rotor unmanned aerial vehicle.
Further, the monocular vision device is a monocular camera.
The method and system for autonomous landing of a vertical take-off and landing unmanned aerial vehicle on a mobile platform provided by the invention are described in detail above, and the specific principles and embodiments of the invention are explained by way of examples, and these descriptions are only used to help understand the core idea of the invention. It should be noted that, for those skilled in the art, without departing from the principle of the present invention, several improvements and modifications can be made to the present invention, and these improvements and modifications also fall into the protection scope of the claims of the present invention.

Claims (9)

1. A control method for autonomous landing of a vertical take-off and landing unmanned aerial vehicle on a mobile platform is characterized by comprising the following steps:
s1: establishing a dynamic model of the vertical take-off and landing unmanned aerial vehicle, a kinematic model of the mobile platform and a relative kinematic model of the vertical take-off and landing unmanned aerial vehicle and the mobile platform;
s2: designing a predetermined performance specification error transformation method;
s3: designing to obtain a position control law of the vertical take-off and landing unmanned aerial vehicle by adopting an inversion control method based on a predetermined performance standard error transformation method;
s4: designing a desired rotation matrix, and a desired angular velocity;
s5: and calculating the moment required by the vertical take-off and landing unmanned aerial vehicle for automatic landing on the mobile platform, and realizing autonomous landing control.
2. The method for controlling the autonomous landing of a VTOL UAV on a mobile platform according to claim 1, wherein the step S1 comprises the steps of:
s11: establishing a dynamic model of the vertical take-off and landing unmanned aerial vehicle, wherein the model is described as follows:
Figure FDA0002686533240000011
Figure FDA0002686533240000012
Figure FDA0002686533240000013
Figure FDA0002686533240000014
wherein p ═ px,py,pz]ΤIs the three-dimensional position of the vertical take-off and landing unmanned aerial vehicle in a world coordinate system,
Figure FDA0002686533240000015
is the first differential of p, v ═ vx,vy,vz]ΤIs the linear velocity of the vertical take-off and landing unmanned aerial vehicle under a world coordinate system,
Figure FDA0002686533240000016
is the first differential of v, Ω ═ Ωx,Ωy,Ωz]ΤIs the angular velocity, omega, of the vertical take-off and landing unmanned aerial vehicle under the body coordinate system∧A diagonally symmetric matrix representing angular velocity such that R Ω∧R × Ω, m and J ═ diag (J)1,J2,J3) Respectively representing the mass and inertia matrix of the VTOL UAV, g is the gravitational acceleration, i3＝[0,0,1]ΤIs a unit vector, f and τ ═ τx,τy,τz]ΤThrust and torsion are respectively provided, R is a rotation matrix, and the rotation matrix is obtained by rotating the vertical take-off and landing unmanned aerial vehicle along Euler angles psi, phi and theta, and psi, phi and theta are respectively expressed as a yaw angle, a roll angle and a pitch angle;
s12: establishing a kinematic model of the mobile platform, wherein the model is described as follows:
Figure FDA0002686533240000017
wherein r isl＝[xl,yl,h]TRepresenting the position of the mobile platform in the world coordinate system, xlIs the abscissa of the mobile platform, ylIs the ordinate of the mobile platform, h is the height of the mobile platform, θlIs the rotation angle, v, of the moving platform body coordinate system relative to the world coordinate systemlAnd ωlRespectively representing the linear velocity and the angular velocity of the mobile platform;
s13: establishing a relative kinematics model of the vertical take-off and landing unmanned aerial vehicle and the mobile platform, wherein the model description is as follows:
rlp＝p-rl (6)
wherein r islp＝[xlp,ylp,zlp]ΤIs the real-time relative three-dimensional position of the vertical take-off and landing unmanned aerial vehicle and the mobile platform.
3. The method for controlling the autonomous landing of a VTOL UAV on a mobile platform according to claim 1, wherein the predetermined performance specification error transformation method of step S2 is as follows:
Figure FDA0002686533240000021
therein, ζk＝ek/ρk，ekIn order to define the error, the error is,kfor the transformed error, pkFor the error performance function, k ∈ {1, 2, … 6 }.
4. The method for controlling the autonomous landing of a VTOL UAV on a mobile platform according to claim 3, wherein the step S3 comprises the steps of:
s31: the monocular vision device carried by the vertical take-off and landing unmanned aerial vehicle captures April tag information in an April tag vision system arranged on a mobile platform, and obtains the vertical take-off and landing through a homography matrix according to the known physical size of the April tagReal-time relative three-dimensional position r between unmanned aerial vehicle and mobile platformlp＝[xlp,ylp,zlp]ΤAnd attitude information;
s32: defining a position error ep＝[e1,e2,e3]ΤComprises the following steps:
Figure FDA0002686533240000022
wherein the content of the first and second substances,
Figure FDA0002686533240000023
indicating a desired relative position;
s33: obtaining a transformed position error according to a predetermined performance specification error transformation methodp＝[1,2,3]Τ；
S34: the first order differential expression of the transformed position error can be obtained:
Figure FDA0002686533240000024
wherein the content of the first and second substances,
Figure FDA0002686533240000025
is rlAnd Q ═ diag (Q), and1,q2,q3) And η ═ η (η)1,η2,η3)ΤAre defined as:
Figure FDA0002686533240000026
Figure FDA0002686533240000031
Figure FDA0002686533240000032
is rhokFirst order differentiation of;
s35: setting the linear velocity of the virtually-expected VTOL UAV to
Figure FDA0002686533240000033
According to equation (9), the linear velocity control law of the virtual expected vertical unmanned plane is obtained as follows:
Figure FDA0002686533240000034
wherein, K1、K2Are the gains of the intermediate controller;
s36: defining a speed error ev＝[e4,e5,e6]ΤComprises the following steps:
Figure FDA0002686533240000035
s37: normalizing the error transformation method according to the predetermined performance to obtain the transformed speed errorv＝[4,5,6]ΤThe first order differential expression of the converted speed error can be obtained:
Figure FDA0002686533240000036
wherein Q isv＝diag(q4,q5,q6) And ηv＝(η4,η5,η6)ΤAre defined as:
Figure FDA0002686533240000037
Figure FDA0002686533240000038
s38: according to equations (14) and (2), the position control law is designed as follows:
u＝-(K3Qv Τ+Qv -1K4)v (17)
wherein, K3,K4Is a positive definite matrix.
5. The method for controlling the autonomous landing of a VTOL UAV on a mobile platform according to claim 4, wherein the step S4 specifically comprises the following steps:
s41: setting the desired rotation angle psi*＝0；
S42: according to the thrust vector F-mgi3-mu and desired rotation angle vector y ═ cos ψ*,sinψ*,0]ΤDesign the desired rotation matrix as Rd＝[r1,r2,r3]Wherein
Figure FDA0002686533240000041
S44: the first order differential of the thrust vector is expressed as
Figure FDA0002686533240000042
Using a first order low pass filter to solve
Figure FDA0002686533240000043
The first order low pass filter is of the form:
Figure FDA0002686533240000044
wherein, KαIs a positive definite symmetric matrix;
s43: the desired angular velocity is expressed as:
Figure FDA0002686533240000045
wherein, (.)∨Is shown as (.)∧The reverse operation of (a) is performed,
Figure FDA0002686533240000046
rotating the matrix R as desireddThe first order differential of (a) is,
Figure FDA0002686533240000047
expressed as:
Figure FDA0002686533240000048
I3×3is a 3 rd order identity matrix.
6. The method for controlling the autonomous landing of a VTOL UAV on a mobile platform according to claim 5, wherein the step S5 specifically comprises the following steps:
s51: rewriting formula (2) as:
Figure FDA0002686533240000049
Figure FDA00026865332400000410
according to equation (17), the saturation thrust of the vtol drone is designed as:
Figure FDA00026865332400000411
s52: the error term of the rotation matrix is defined as follows:
Figure FDA00026865332400000412
eΩ＝Ω-RΤRdΩd (26)
wherein R isdFor the desired rotation matrix, R is the actual rotation matrix, eRIs the rotation matrix error; omegadFor desired angular velocity, Ω is the actual angular velocity, eΩIs the angular velocity error;
s53: the moment of getting VTOL unmanned aerial vehicle is with convolution (4), equation (25), equation (26):
τ＝-KReR-KΩeΩ+Ω×JΩ (26)
wherein, KR、KΩThe attitude control gain.
7. The utility model provides a system that VTOL unmanned aerial vehicle independently landed on mobile platform, its characterized in that, the system contains VTOL unmanned aerial vehicle, monocular vision device, autonomic landing control module, aprilTag vision benchmark system, mobile platform, wherein:
the monocular vision device is connected with the autonomous landing control module and sends the acquired image information to the autonomous landing control module;
the autonomous landing control module is connected with the vertical take-off and landing unmanned aerial vehicle and sends a control instruction to the vertical take-off and landing unmanned aerial vehicle;
an Apriltag visual reference system is arranged on the mobile platform;
the aprilatag visual reference system is within the range of viewing angles of a monocular visual device.
8. The system of claim 7, wherein the VTOL drone is a quad-rotor drone.
9. The system of claim 8, wherein the monocular vision device is a monocular camera.
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