CN109885074B - Finite time convergence attitude control method for quad-rotor unmanned aerial vehicle - Google Patents

Finite time convergence attitude control method for quad-rotor unmanned aerial vehicle Download PDF

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CN109885074B
CN109885074B CN201910153593.8A CN201910153593A CN109885074B CN 109885074 B CN109885074 B CN 109885074B CN 201910153593 A CN201910153593 A CN 201910153593A CN 109885074 B CN109885074 B CN 109885074B
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unmanned aerial
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attitude
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鲜斌
张诗婧
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Tianjin University
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Abstract

The invention relates to the attitude accurate control of a quadrotor unmanned aerial vehicle, and provides a nonlinear attitude controller for the quadrotor unmanned aerial vehicle. 1) Establishing a four-rotor unmanned aerial vehicle dynamic model, and establishing the four-rotor unmanned aerial vehicle dynamic model by adopting a Newton-Euler method; 2) non-linear controller design, including roll angle
Figure DDA0001982180060000011
Designing a nonlinear controller, designing a pitch angle theta nonlinear controller and designing a yaw angle psi nonlinear controller; and finally, realizing the finite time convergence control of the attitude error of the unmanned aerial vehicle. The invention is mainly applied to the situation of accurate attitude control of the quad-rotor unmanned aerial vehicle.

Description

Finite time convergence attitude control method for quad-rotor unmanned aerial vehicle
Technical Field
The invention relates to attitude precision control of a quad-rotor unmanned aerial vehicle. Aiming at the characteristics of high nonlinearity, under-actuation, strong coupling, uncertain disturbance and the like of a quad-rotor unmanned aerial vehicle system, the nonlinear attitude controller based on second-order sliding mode control is provided, and the result of finite time convergence of the attitude control error of the unmanned aerial vehicle is realized. In particular to a finite time convergence attitude control method for a quad-rotor unmanned aerial vehicle.
Background
The multi-rotor unmanned aerial vehicle has the characteristics of simple mechanical structure, capability of vertically taking off and landing, hovering, lower requirement on a field and the like, and occupies more and more important positions in the aspects of scientific research, civil use and military use in recent years. In the numerous many rotor unmanned aerial vehicle types, four rotor unmanned aerial vehicle are comparatively commonly used. The attitude of the airplane is changed by changing the relative rotating speed and the single-shaft thrust between the four rotors, so that the running track of the airplane is changed. Therefore, it is crucial to study attitude control of quad-rotor drones for controlling quad-rotor drones.
Attitude control to four rotor unmanned aerial vehicle, the research of foreign was carried out earlier. The primary main objective of the project of the quad-rotor unmanned aerial vehicle of Stanford university is to improve the cooperative working capacity of the quad-rotor unmanned aerial vehicle by reasonably applying a multi-agent technology, and therefore, the two types of quad-rotor unmanned aerial vehicles are modified successively. The second item improves the speed of the processor and the accuracy of the sensor compared to the first item, thereby resulting in an improved control effect. The quad-rotor unmanned aerial vehicle adopts two single-chip microcomputers of PIC18F6520 company model to coordinate communication, sensing and Control activities on the aircraft (Conference: IEEE RSJ International Conference on Intelligent Robots and Systems; authors: Hoffmann Gabriel M, Waslander Steven L, Vitus Michael P, etc.; published month: 2009; article title: Stanford test of Autonomus Rotorcraft for Multi-Agent Control; page number: 404-. This unmanned aerial vehicle has realized indoor and outdoor autonomic flight at present. The quad-rotor unmanned aerial vehicle at pennsylvania university uses a control algorithm based on a backstepping method to construct a flight control system based on vision. The tasks of landing a ground mobile platform, grabbing a target, cooperating a plurality of machines and The like can be realized (journal: IEEE Robotics & Automatics Magazine; author: Michael N, Mellinger D, Lindsey Q, Kumar V; published year month: 9 2010; article title: The GRASP Multiple Micro-UAV Test Bed expert Evaluation of Multi aircraft Control Algorithms; page number: 56-65). In terms of applying a high-order Sliding Mode control algorithm, the university of Alabama, Hantzville, university of America, controls a quad-rotor unmanned aerial vehicle by applying a traditional Sliding Mode control and a Super-twilling algorithm (journal: Automatica; author: Shtessel Y, Taleb M, Plesan F; published month: 2012: 5 month; article title: A novel Adaptive-gain Super-twilling Sliding Mode Controller: method and Application; page number: 759-. In addition, there are also students who use high-order sliding mode Control for Unmanned Aerial Vehicle fault-tolerant Control (journal: IEEE Transactions on Control Systems Technology; Renderee: Ryl Markus, Buelthoff Heinrich H, Giordino Paolo Robuffo; published month: 2015 3 months; article title: A Novel acted Quadrotor Unmanned Aerial Vehicle: Modeling, Control, and Experimental Validation; page: 540-. Although the research of the domestic four-rotor unmanned aerial vehicle starts late, a certain result is obtained. Wherein scientific research institutes such as Qinghua university, national defense science and technology university, Tianjin university, Beijing aerospace university and the like make great contribution to the research and development of the domestic four-rotor unmanned aerial vehicle. At present, the control methods used at home and abroad mainly include feedback linearization, a backstepping method, robust control, sliding mode variable structure control, intelligent PID (proportion, integral and differential) control and the like.
With regard to the research on quad-rotor drone control, researchers have achieved some success today, but there are also some limitations: 1) some existing control designs make more assumptions and simplifications on the dynamic model of the unmanned aerial vehicle, for example, some existing achievements assume that the flying speed of the unmanned aerial vehicle is low, and do not consider the disturbance. But in practice the disturbances experienced by the drone are not negligible. 2) Some control methods linearize the model of the controlled object near the equilibrium point and design the controller based on the linearized model, thereby weakening the control effect of the controlled object near the non-equilibrium point.
Disclosure of Invention
In order to overcome the defects of the prior art, the invention aims to provide a nonlinear attitude controller for a quad-rotor unmanned aerial vehicle. Therefore, the invention adopts the technical scheme that the finite time convergence attitude control method of the quad-rotor unmanned aerial vehicle comprises the following steps:
1) establishing a four-rotor unmanned aerial vehicle dynamics model
The invention adopts Newton-Euler method to establish a four-rotor unmanned plane dynamics model, and the expression is as follows:
Figure BDA0001982180040000021
the variables in formula (1) are defined as follows:
Figure BDA0001982180040000022
the mass of the unmanned aerial vehicle is the mass of the unmanned aerial vehicle,
Figure BDA0001982180040000023
is a space position vector of the unmanned aerial vehicle under an inertial coordinate system,
Figure BDA0001982180040000024
and g is 9.8m/s2Which represents the acceleration of the force of gravity,
Figure BDA0001982180040000025
is a translational damping coefficient matrix, Kx,Ky,KzAre all constant parameters, are respectively the air damping coefficients of the unmanned aerial vehicle along the three axes of the body coordinate system,Butrepresenting the resultant force generated by the propeller of the unmanned plane in a body coordinate system,
Figure BDA0001982180040000026
representing the torque of the lift force generated by the propeller acting on the unmanned aerial vehicle body under the body coordinate system,
Figure BDA0001982180040000027
is a rotational inertia matrix of the drone, wherein Jx,Jy,JzRespectively the rotational inertia of the unmanned aerial vehicle around three axes of a coordinate system of the body,
Figure BDA0001982180040000028
is the rotation angular velocity of the unmanned aerial vehicle,
Figure BDA00019821800400000216
as a matrix of rotational damping coefficients,K1,K2,K3For the normal reference, the air damping coefficients of the unmanned aerial vehicle around three axes of the body coordinate system are respectively expressed, and in the formula (1), RtThe expression of (a) is:
Figure BDA00019821800400000210
wherein the content of the first and second substances,
Figure BDA00019821800400000217
theta, psi represents roll angle, pitch angle and yaw angle of the unmanned aerial vehicle, respectively, and forceButIs always perpendicular to the plane where the unmanned aerial vehicle body is located, and the size of the unmanned aerial vehicle generates lift force f for four propellers1,f2,f3,f4The sum of (a):
Figure BDA00019821800400000212
and isBτ is a linear combination of the four propellers producing lift, expressed in the form:
Figure BDA00019821800400000213
wherein
Figure BDA00019821800400000218
The distance from the axis of the propeller to the geometric center of the unmanned aerial vehicle is shown, and is called as the half wheelbase,
Figure BDA00019821800400000215
expressing the lift-torque coefficient of a motor and propeller actuator system of the unmanned aerial vehicle, and bringing the formulas (2) to (4) into formula (1) to obtain:
Figure BDA0001982180040000031
moreover, according to the rotation subsystem of the kinematics model of the drone, we obtain:
Figure BDA0001982180040000032
for attitude stabilization control of the unmanned aerial vehicle, namely, the roll angle, pitch angle and yaw angle of the unmanned aerial vehicle are all 0, so that
Figure BDA0001982180040000033
Theta, psi are small, as small as
Figure BDA0001982180040000034
Approximately equal to the identity matrix, thus, equation (5) is rewritten as:
Figure BDA0001982180040000035
2) non-linear controller design
For design convenience, four virtual control quantities are defined:
Figure BDA0001982180040000036
bringing formula (8) into formulae (5) and (1) gives:
Figure BDA0001982180040000037
wherein A isz,
Figure BDA0001982180040000038
Aθ,AψRespectively representing the external disturbance to which the drone is subjected in that direction;
roll angle
Figure BDA0001982180040000039
The nonlinear controller is designed by the following steps:
cross roll angle channel error
Figure BDA0001982180040000041
Figure BDA0001982180040000042
The desired roll angle is expressed, thereby yielding the following equation:
Figure BDA0001982180040000043
next, defining a slip form surface
Figure BDA0001982180040000044
Figure BDA0001982180040000045
Wherein the content of the first and second substances,
Figure BDA0001982180040000046
constant parameter
Figure BDA0001982180040000047
The pitch angle theta nonlinear controller is designed by the following steps:
pitch angle channel error eθ=θd-θ,θdRepresenting the desired pitch angle, the following equation is derived:
Figure BDA0001982180040000048
next, a slip form surface s is definedθ
Figure BDA0001982180040000049
Wherein the content of the first and second substances,
Figure BDA00019821800400000410
constant value kθ>0;
The design steps of the yaw angle psi nonlinear controller are as follows:
yaw angle channel error eψ=ψd-ψ,ψdThe desired yaw angle is expressed, thereby yielding the following equation:
Figure BDA00019821800400000411
next, a slip form surface s is definedψ
Figure BDA00019821800400000412
Wherein the content of the first and second substances,
Figure BDA00019821800400000413
constant value kψ>0;
The following formula is obtained:
Figure BDA00019821800400000414
thus, three new virtual control quantities are obtained
Figure BDA00019821800400000415
UθAnd UψNow, the control quantity is designed by using the super-twisting algorithm:
Figure BDA0001982180040000051
in the formula betaiAnd alphaiIs a gain and is a constant, andi>0,αi>0, i is preferable
Figure BDA0001982180040000052
Theta or psi.
The invention has the characteristics and beneficial effects that:
the invention establishes a dynamics model containing unknown interference for the quad-rotor unmanned aerial vehicle, designs a nonlinear attitude controller based on a super-twisting control algorithm, realizes the finite time convergence control of the attitude error of the unmanned aerial vehicle, improves the robustness of the quad-rotor unmanned aerial vehicle system, and realizes the accurate control of the attitude of the quad-rotor unmanned aerial vehicle.
Description of the drawings:
FIG. 1 is a schematic diagram of a quad-rotor drone system for use with the present invention;
FIG. 2 is a flow chart of the four-rotor drone control of the present invention;
FIG. 3 is a hardware-in-the-loop simulation platform for a quad-rotor drone for use with the present invention;
FIG. 4 is a graph of three attitude angles during flight of a quad-rotor drone using a control scheme;
fig. 5 is a graph of roll angle during quad-rotor drone flight when subject to external disturbances after the control scheme is employed.
Detailed Description
In order to overcome the existing defects, the invention designs a nonlinear attitude controller aiming at a four-rotor unmanned aerial vehicle. The non-linear attitude controller is embodied in figure 2 for use in a quad-rotor drone system. The invention adopts the technical scheme that a nonlinear attitude control method of a quad-rotor unmanned aerial vehicle is adopted. The method comprises the following steps:
1) establishing a four-rotor unmanned aerial vehicle dynamics model
The invention adopts Newton-Euler method to establish a four-rotor unmanned plane dynamics model, and the expression is as follows:
Figure BDA0001982180040000053
the variables in formula (1) are defined as follows:
Figure BDA0001982180040000054
the mass of the unmanned aerial vehicle is the mass of the unmanned aerial vehicle,
Figure BDA0001982180040000055
the space position vector of the unmanned aerial vehicle under the inertial coordinate system.
Figure BDA0001982180040000056
And g is 9.8m/s2Representing the gravitational acceleration.
Figure BDA0001982180040000057
Is a translational damping coefficient matrix, Kx,Ky,KzThe air damping coefficients are all constant parameters and are the air damping coefficients of the unmanned aerial vehicle along the three axes of the body coordinate system.ButAnd the resultant force generated by the propeller of the unmanned aerial vehicle under the body coordinate system is represented.
Figure BDA0001982180040000058
And the torque of the lift force generated by the propeller acting on the unmanned aerial vehicle body under the body coordinate system is represented.
Figure BDA0001982180040000059
Is a rotational inertia matrix of the drone, wherein Jx,Jy,JzRespectively is the inertia of the unmanned aerial vehicle around the three axes of the coordinate system of the body.
Figure BDA00019821800400000510
Is the angular velocity of rotation of the drone.
Figure BDA00019821800400000511
As a matrix of rotational damping coefficients, K1,K2,K3And the air damping coefficients of the unmanned aerial vehicle around three axes of the coordinate system of the body are respectively expressed as normal parameters. Further, in the formula (1), RtThe expression of (a) is:
Figure BDA0001982180040000061
force ofButIs always perpendicular to the plane of the unmanned aerial vehicle body and is largeSmall four propellers generating lift force f1,f2,f3,f4The sum of (a):
Figure BDA0001982180040000062
and isBτ is a linear combination of the four propellers producing lift and can be expressed in the form:
Figure BDA0001982180040000063
wherein
Figure BDA0001982180040000064
The distance from the axis of the propeller to the geometric center of the unmanned aerial vehicle is shown, and can be called as a half-wheelbase,
Figure BDA0001982180040000065
representing the lift-torque coefficient of the actuator (motor and propeller) system of the drone. Bringing formulae (2) to (4) into formula (1) can give:
Figure BDA0001982180040000066
moreover, according to the rotation subsystem of the kinematics model of the drone, it is possible to know:
Figure BDA0001982180040000067
considering that the control objective of the present study is attitude stabilization control of the drone, i.e., the roll angle, pitch angle, and yaw angle of the drone are all 0, it is assumed that
Figure BDA0001982180040000068
Theta, psi are small, as small as
Figure BDA0001982180040000069
Approximately equal to the identity matrix, so equation (5) can be rewritten as:
Figure BDA00019821800400000610
2) non-linear controller design
For design convenience, four virtual control quantities are defined:
Figure BDA0001982180040000071
bringing formula (8) into formula (5) and formula (1) can yield:
Figure BDA0001982180040000072
wherein A isz,
Figure BDA0001982180040000073
Aθ,AψRespectively, representing the external disturbances experienced by the drone in that direction.
In the following, the present specification performs a nonlinear controller design.
Firstly, designing a controller of a roll angle channel. The invention selects closed-loop control, so that the roll angle channel error is set
Figure BDA0001982180040000074
Figure BDA0001982180040000075
The desired roll angle is expressed, thereby yielding the following equation:
Figure BDA0001982180040000076
next, the invention defines a slip form face:
Figure BDA0001982180040000077
wherein the content of the first and second substances,
Figure BDA0001982180040000078
constant parameter
Figure BDA0001982180040000079
And processing other two attitude angle channels according to the method:
setting pitch angle channel error eθ=θd-θ,θdRepresenting the desired pitch angle, the following equation is derived:
Figure BDA00019821800400000710
next, a slip form surface is defined:
Figure BDA00019821800400000711
wherein the content of the first and second substances,
Figure BDA00019821800400000712
constant value kθ>0。
Set yaw angle channel error eψ=ψd-ψ,ψdThe desired yaw angle is expressed, thereby yielding the following equation:
Figure BDA0001982180040000081
next, the invention defines a slip form face:
Figure BDA0001982180040000082
wherein the content of the first and second substances,
Figure BDA0001982180040000083
constant value kψ>0。
Through the above processing of the three attitude angle channels, the following formula is obtained:
Figure BDA0001982180040000084
therefore, the invention obtains three new virtual control quantities
Figure BDA0001982180040000085
UθAnd Uψ. Now, the control quantity is designed by using a super-twisting algorithm:
Figure BDA0001982180040000086
wherein the gains are all constant, and βi>0,αi>0。
The invention aims to solve the technical problem of realizing the accurate control of the posture of the quad-rotor unmanned aerial vehicle under the condition of external interference. Therefore, a dynamic model of the quad-rotor unmanned aerial vehicle containing external disturbance needs to be established, and a super-twisting algorithm-based attitude controller is designed according to the model, so that the attitude of the unmanned aerial vehicle can be accurately controlled.
The technical scheme adopted by the invention is as follows: establishing a four-rotor unmanned aerial vehicle dynamic model containing external unknown disturbance and designing a corresponding nonlinear attitude controller, wherein the method comprises the following steps:
first, a quad-rotor drone dynamics model needs to be built. Fig. 1 is a schematic diagram of a quad-rotor drone system as used herein. The unmanned aerial vehicle is an X-shaped quadrotor unmanned aerial vehicle, and a dynamics model of the quadrotor unmanned aerial vehicle is established by adopting a Newton-Euler method, wherein the expression is as follows:
Figure BDA0001982180040000087
the variables in formula (1) are defined as follows:
Figure BDA0001982180040000088
the mass of the unmanned aerial vehicle is the mass of the unmanned aerial vehicle,
Figure BDA0001982180040000089
the space position vector of the unmanned aerial vehicle under the inertial coordinate system.
Figure BDA00019821800400000810
And g is 9.8m/s2Representing the gravitational acceleration.
Figure BDA00019821800400000811
Is a translational damping coefficient matrix, Kx,Ky,KzThe air damping coefficients are all constant parameters and are the air damping coefficients of the unmanned aerial vehicle along the three axes of the body coordinate system.ButAnd the resultant force generated by the propeller of the unmanned aerial vehicle under the body coordinate system is represented.
Figure BDA00019821800400000812
And the torque of the lift force generated by the propeller acting on the unmanned aerial vehicle body under the body coordinate system is represented.
Figure BDA00019821800400000813
Is a rotational inertia matrix of the drone, wherein Jx,Jy,JzRespectively is the inertia of the unmanned aerial vehicle around the three axes of the coordinate system of the body.
Figure BDA00019821800400000814
Is the angular velocity of rotation of the drone.
Figure BDA00019821800400000815
As a matrix of rotational damping coefficients, K1,K2,K3And the air damping coefficients of the unmanned aerial vehicle around three axes of the coordinate system of the body are respectively expressed as normal parameters. Further, in the formula (1), RtThe expression of (a) is:
Figure BDA0001982180040000091
force ofButIs always perpendicular to the plane where the unmanned aerial vehicle body is located, and the size of the unmanned aerial vehicle generates lift force f for four propellers1,f2,f3,f4The sum of (a):
Figure BDA0001982180040000092
and isBτ is a linear combination of the four propellers producing lift and can be expressed in the form:
Figure BDA0001982180040000093
wherein
Figure BDA0001982180040000094
The distance from the axis of the propeller to the geometric center of the unmanned aerial vehicle is shown, and can be called as a half-wheelbase,
Figure BDA0001982180040000095
representing the lift-torque coefficient of the actuator (motor and propeller) system of the drone.
Bringing formulae (2) to (4) into formula (1) can give:
Figure BDA0001982180040000096
moreover, according to the rotation subsystem of the kinematics model of the drone, it is possible to know:
Figure BDA0001982180040000097
the control objective in view of this study is attitude stabilization control of the drone, i.e. roll, pitch and yaw of the droneAngles are all 0, so suppose
Figure BDA0001982180040000098
Theta, psi are small, as small as
Figure BDA0001982180040000099
Approximately equal to the identity matrix, so equation (5) can be rewritten as:
Figure BDA00019821800400000910
then, the design of the nonlinear controller based on the super-twisting control algorithm is carried out according to the dynamic model.
For design convenience, four virtual control quantities are defined:
Figure BDA0001982180040000101
bringing formula (8) into formula (5) and formula (1) can yield:
Figure BDA0001982180040000102
wherein A isz,
Figure BDA0001982180040000103
Aθ,AψRespectively, representing the external disturbances experienced by the drone in that direction.
The following is a non-linear controller design.
The invention selects closed-loop control, so the roll angle channel error is set
Figure BDA0001982180040000104
Figure BDA00019821800400001013
Representing the desired roll angle, the following equation is obtained:
Figure BDA0001982180040000106
next, the invention defines a slip form face:
Figure BDA0001982180040000107
wherein the content of the first and second substances,
Figure BDA0001982180040000108
constant parameter
Figure BDA0001982180040000109
And processing other two attitude angle channels according to the method, wherein the detailed process is as follows:
setting pitch angle channel error eθ=θd-θ,θdRepresenting the desired pitch angle, the following equation is derived:
Figure BDA00019821800400001010
next, the invention defines a slip form face:
Figure BDA00019821800400001011
wherein the content of the first and second substances,
Figure BDA00019821800400001012
constant value kθ>0。
Set yaw angle channel error eψ=ψd-ψ,ψdThe desired yaw angle is expressed, thereby yielding the following equation:
Figure BDA0001982180040000111
next, the invention defines a slip form face:
Figure BDA0001982180040000112
wherein the content of the first and second substances,
Figure BDA0001982180040000113
constant value kψ>0。
To give the following formula:
Figure BDA0001982180040000114
order to
Figure BDA0001982180040000115
And suppose | ρ | |<δ, δ being a constant
Therefore, the invention obtains three new virtual control quantities
Figure BDA0001982180040000116
UθAnd Uψ
Now, the control quantity is designed by using a super-twisting algorithm:
Figure BDA0001982180040000117
wherein the gains are all constant, and βi>0,αi>0. It can be demonstrated that when the gains α, β satisfy α>δ,β2>4 α, the control system may converge in a limited time. Wherein the transfer function G(s) ═ C (sI-A)-1B satisfies
Figure BDA0001982180040000118
And:
Figure BDA0001982180040000119
specific examples of implementation are given below:
first, introduction of experiment platform
The invention utilizes the experimental platform shown in fig. 3 to verify the effect of the designed nonlinear controller. This experiment platform is four rotor unmanned aerial vehicle hardware in the ring simulation platform. This platform adopts real four rotor unmanned aerial vehicle as the controlled object to loaded real attitude sensor on unmanned aerial vehicle, can obtain real and audio-visual unmanned aerial vehicle attitude control effect from this, also made the result more press close to the actual flight condition. Meanwhile, the platform establishes communication among the upper computer, the target computer and the monitoring computer by utilizing a network, and is convenient for data interaction and control.
Second, flight experiment results
In order to verify the effectiveness and the feasibility of the nonlinear attitude controller provided by the invention, the four-rotor unmanned aerial vehicle attitude stabilization experiment is carried out on the experimental platform. The control target is that three attitude angles of the unmanned aerial vehicle approach to zero in limited time, namely:
Figure BDA00019821800400001110
and can still be recovered to a stable state when being interfered by the outside.
The experimental platform relates to the parameter values of inertia moment J ═ diag [1.34,1.31,2.54 ]]T×10-2kg·m2The half-axle distance l is 0.225m, the lift-torque coefficient c is 0.25, and the mass m is 1.5 kg.
As can be seen from FIG. 4, the error can be controlled to be within-1 to 1.5 using the super-twisting attitude controller. It can be seen from fig. 5 that the steady state can still be reached when the external disturbance reaches 40 °. Therefore, the nonlinear attitude controller of the quad-rotor unmanned aerial vehicle has good robustness and can accurately control the attitude angle.

Claims (1)

1. A finite time convergence attitude control method for a quad-rotor unmanned aerial vehicle is characterized by comprising the following steps:
1) establishing a four-rotor unmanned aerial vehicle dynamics model
A Newton-Euler method is adopted to establish a four-rotor unmanned plane dynamic model, and the expression formula is as follows:
Figure FDA0003366254470000011
the variables in formula (1) are defined as follows:
Figure FDA0003366254470000012
the mass of the unmanned aerial vehicle is the mass of the unmanned aerial vehicle,
Figure FDA0003366254470000013
is a space position vector of the unmanned aerial vehicle under an inertial coordinate system,
Figure FDA0003366254470000014
and g is 9.8m/s2Which represents the acceleration of the force of gravity,
Figure FDA0003366254470000015
is a translational damping coefficient matrix, Kx,Ky,KzAre all constant parameters, are respectively the air damping coefficients of the unmanned aerial vehicle along the three axes of the body coordinate system,Butrepresenting the resultant force generated by the propeller of the unmanned plane in a body coordinate system,
Figure FDA0003366254470000016
representing the torque of the lift force generated by the propeller acting on the unmanned aerial vehicle body under the body coordinate system,
Figure FDA0003366254470000017
is a rotational inertia matrix of the drone, wherein Jx,Jy,JzRespectively the rotational inertia of the unmanned aerial vehicle around three axes of a coordinate system of the body,
Figure FDA0003366254470000018
is the rotation angular velocity of the unmanned aerial vehicle,
Figure FDA0003366254470000019
as a matrix of rotational damping coefficients, K1,K2,K3The air damping coefficients of the unmanned aerial vehicle around three axes of the body coordinate system are respectively expressed as constant parameters, and in the formula (1), RtThe expression of (a) is:
Figure FDA00033662544700000110
wherein the content of the first and second substances,
Figure FDA00033662544700000111
respectively representing the roll angle, pitch angle and yaw angle of the unmanned aerial vehicle, and forceButIs always perpendicular to the plane where the unmanned aerial vehicle body is located, and the size of the unmanned aerial vehicle generates lift force f for four propellers1,f2,f3,f4The sum of (a):
Figure FDA00033662544700000112
and isBτ is a linear combination of the four propellers producing lift, expressed in the form:
Figure FDA00033662544700000113
wherein
Figure FDA00033662544700000114
The distance from the axis of the propeller to the geometric center of the unmanned aerial vehicle is shown, and is called as the half wheelbase,
Figure FDA00033662544700000115
motor for indicating unmanned aerial vehicleAnd the lift-torque coefficient of the propeller actuator system, and the expressions (2) to (4) are taken into the formula (1) to obtain:
Figure FDA00033662544700000116
Figure FDA00033662544700000117
Figure FDA00033662544700000118
moreover, according to the rotation subsystem of the kinematics model of the drone, we obtain:
Figure FDA0003366254470000021
for attitude stabilization control of the unmanned aerial vehicle, namely, the roll angle, pitch angle and yaw angle of the unmanned aerial vehicle are all 0, so that
Figure FDA0003366254470000022
Very small, as small as
Figure FDA0003366254470000023
Approximately equal to the identity matrix, thus, equation (5) is rewritten as:
Figure FDA0003366254470000024
Figure FDA0003366254470000025
Figure FDA0003366254470000026
2) non-linear controller design
For design convenience, four virtual control quantities are defined:
u1=f1+f2+f3+f4
u2=f1+f2-f3-f4
u3=-f1+f2+f3-f4
u4=-f1+f2-f3+f4 (8)
bringing formula (8) into formulae (5) and (1) gives:
Figure FDA0003366254470000027
Figure FDA0003366254470000028
Figure FDA0003366254470000029
Figure FDA00033662544700000210
wherein
Figure FDA00033662544700000211
Respectively representing the external disturbance to which the drone is subjected in that direction;
roll angle
Figure FDA00033662544700000212
The nonlinear controller is designed by the following steps:
cross roll angle channel error
Figure FDA00033662544700000213
Figure FDA00033662544700000214
The desired roll angle is expressed, thereby yielding the following equation:
Figure FDA00033662544700000215
Figure FDA00033662544700000216
next, defining a slip form surface
Figure FDA00033662544700000217
Figure FDA0003366254470000031
Figure FDA0003366254470000032
Wherein the content of the first and second substances,
Figure FDA0003366254470000033
Figure FDA0003366254470000034
constant parameter
Figure FDA00033662544700000321
The pitch angle theta nonlinear controller is designed by the following steps:
pitch angle channelError eθ=θd-θ,θdRepresenting the desired pitch angle, the following equation is derived:
Figure FDA0003366254470000035
Figure FDA0003366254470000036
next, a slip form surface s is definedθ
Figure FDA0003366254470000037
Figure FDA0003366254470000038
Wherein the content of the first and second substances,
Figure FDA0003366254470000039
Figure FDA00033662544700000310
constant value kθ>0;
The design steps of the yaw angle psi nonlinear controller are as follows:
yaw angle channel error eψ=ψd-ψ,ψdThe desired yaw angle is expressed, thereby yielding the following equation:
Figure FDA00033662544700000311
Figure FDA00033662544700000312
next, a slip form surface s is definedψ
Figure FDA00033662544700000313
Figure FDA00033662544700000314
Wherein the content of the first and second substances,
Figure FDA00033662544700000315
Figure FDA00033662544700000316
constant value kψ>0;
The following formula is obtained:
Figure FDA00033662544700000317
thus, three new virtual control quantities are obtained
Figure FDA00033662544700000318
UθAnd UψNow, the control quantity is designed by using the super-twisting algorithm:
Figure FDA00033662544700000319
Figure FDA00033662544700000322
in the formula betaiAnd alphaiIs a gain and is a constant, andi>0,αi>0, i is preferable
Figure FDA00033662544700000320
Theta or psi.
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