CN111650951A - Full-loop composite dynamic inverse tracking control method for complex track of quad-rotor unmanned aerial vehicle - Google Patents
Full-loop composite dynamic inverse tracking control method for complex track of quad-rotor unmanned aerial vehicle Download PDFInfo
- Publication number
- CN111650951A CN111650951A CN202010441724.5A CN202010441724A CN111650951A CN 111650951 A CN111650951 A CN 111650951A CN 202010441724 A CN202010441724 A CN 202010441724A CN 111650951 A CN111650951 A CN 111650951A
- Authority
- CN
- China
- Prior art keywords
- aerial vehicle
- unmanned aerial
- quad
- attitude
- rotor unmanned
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- 239000002131 composite material Substances 0.000 title claims abstract description 37
- 238000000034 method Methods 0.000 title claims abstract description 28
- 238000006073 displacement reaction Methods 0.000 claims description 10
- 238000013461 design Methods 0.000 claims description 9
- 230000008859 change Effects 0.000 claims description 6
- 230000007613 environmental effect Effects 0.000 claims description 4
- 230000001133 acceleration Effects 0.000 claims description 3
- 238000006243 chemical reaction Methods 0.000 claims description 3
- 238000013016 damping Methods 0.000 claims description 3
- 230000005484 gravity Effects 0.000 claims description 3
- 239000011159 matrix material Substances 0.000 claims description 3
- 230000036544 posture Effects 0.000 claims description 3
- 230000006641 stabilisation Effects 0.000 claims description 3
- 238000011105 stabilization Methods 0.000 claims description 3
- 238000005312 nonlinear dynamic Methods 0.000 abstract description 4
- 238000010586 diagram Methods 0.000 description 6
- 230000009471 action Effects 0.000 description 5
- 230000008569 process Effects 0.000 description 4
- 230000004044 response Effects 0.000 description 4
- 238000004088 simulation Methods 0.000 description 4
- 230000000694 effects Effects 0.000 description 3
- 230000001629 suppression Effects 0.000 description 2
- RZVHIXYEVGDQDX-UHFFFAOYSA-N 9,10-anthraquinone Chemical compound C1=CC=C2C(=O)C3=CC=CC=C3C(=O)C2=C1 RZVHIXYEVGDQDX-UHFFFAOYSA-N 0.000 description 1
- 230000002411 adverse Effects 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000015572 biosynthetic process Effects 0.000 description 1
- 238000011217 control strategy Methods 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 230000008030 elimination Effects 0.000 description 1
- 238000003379 elimination reaction Methods 0.000 description 1
- 238000012423 maintenance Methods 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 238000012795 verification Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
- G05D1/08—Control of attitude, i.e. control of roll, pitch, or yaw
- G05D1/0808—Control of attitude, i.e. control of roll, pitch, or yaw specially adapted for aircraft
- G05D1/0816—Control of attitude, i.e. control of roll, pitch, or yaw specially adapted for aircraft to ensure stability
- G05D1/0825—Control of attitude, i.e. control of roll, pitch, or yaw specially adapted for aircraft to ensure stability using mathematical models
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
- G05D1/10—Simultaneous control of position or course in three dimensions
- G05D1/101—Simultaneous control of position or course in three dimensions specially adapted for aircraft
Landscapes
- Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Physics & Mathematics (AREA)
- Automation & Control Theory (AREA)
- Remote Sensing (AREA)
- Radar, Positioning & Navigation (AREA)
- Aviation & Aerospace Engineering (AREA)
- Mathematical Analysis (AREA)
- Pure & Applied Mathematics (AREA)
- Mathematical Physics (AREA)
- Mathematical Optimization (AREA)
- Algebra (AREA)
- Control Of Position, Course, Altitude, Or Attitude Of Moving Bodies (AREA)
Abstract
The invention discloses a full-loop composite dynamic inverse tracking control method for a complicated track of a quad-rotor unmanned aerial vehicle, which comprises the steps of firstly, establishing a full-loop system model of a disturbed quad-rotor unmanned aerial vehicle, wherein the model comprises a position loop and an attitude loop; secondly, designing interference observers aiming at the position subsystem and the attitude subsystem respectively based on an extended state observer technology, and estimating the lumped interference; and finally, constructing a composite dynamic inverse trajectory tracking controller based on a nonlinear dynamic inverse algorithm and in combination with interference estimation information, and realizing high-precision tracking of the complex trajectory. By adopting the extended state observer technology, the asymptotic estimation of lumped interference in position and attitude loops is realized, interference estimation information is compensated in a feedforward mode, and the anti-interference performance of the controller is obviously improved; compared with the traditional dynamic inverse control method, the method has better anti-interference performance, and effectively inhibits the influence of multi-source interference on the control performance of the quad-rotor unmanned aerial vehicle.
Description
Technical Field
The invention belongs to the technical field of flight control, and particularly relates to a full-loop composite dynamic inverse tracking control method for a four-rotor unmanned aerial vehicle with a complex track.
Background
The quad-rotor unmanned aerial vehicle is an unmanned aerial vehicle capable of hovering at a fixed height and taking off and landing vertically, has the advantages of simple structure, low cost, convenience in maintenance, strong universality of flight environment and the like, is widely applied to the fields of aerial reconnaissance, disaster rescue, formation attack and the like, and has important research significance and application prospect. The high-precision trajectory tracking of the quad-rotor unmanned aerial vehicle is an important basis and precondition for the quad-rotor unmanned aerial vehicle to execute complex tasks or form flying. However, in the tracking process of the track, especially the tracking process of a complex track, the quad-rotor unmanned aerial vehicle is influenced by multi-source interference such as perturbation of internal pneumatic parameters, unmodeled friction dynamic, external gust interference, environmental uncertainty and the like, and the precision of the track tracking is seriously influenced by the multi-source interference. Therefore, interference suppression becomes a critical problem to be solved urgently by the design of a trajectory tracking control system of a quad-rotor unmanned aerial vehicle.
Aiming at the problem of trajectory tracking control of an interfered quad-rotor unmanned aerial vehicle, scholars at home and abroad provide various anti-interference control strategies, including dynamic inverse control for feedback based on nonlinear characteristics of a nominal model and sliding mode control depending on algorithm robustness. However, the interference suppression strategy of these methods is based on passive elimination of the influence of interference by the error signal, and the anti-interference performance of the system is obtained at the expense of the nominal performance. Therefore, a trajectory tracking control method for a quad-rotor unmanned aerial vehicle, which can rapidly and actively suppress multi-source interference influence, is urgently needed.
Disclosure of Invention
The purpose of the invention is as follows: in order to overcome the defects of the prior art, the invention provides a full-loop composite dynamic inverse tracking control method for a complex track of a quad-rotor unmanned aerial vehicle, which can realize gradual estimation of lumped interference of a position loop and an attitude loop, and compensate or offset adverse effects brought by the interference of interference estimation information in a feedforward mode so as to ensure that the quad-rotor unmanned aerial vehicle has quicker and stronger anti-interference performance.
The technical scheme is as follows: the invention provides a full-loop composite dynamic reverse tracking control method for a four-rotor unmanned aerial vehicle with a complex track, which specifically comprises the following steps:
(1) constructing a disturbed four-rotor unmanned aerial vehicle full-loop system model comprising a four-rotor unmanned aerial vehicle position loop subsystem and an attitude loop subsystem;
(2) the problem of trajectory tracking of the quad-rotor unmanned aerial vehicle is converted into the stabilization problem of position ring tracking errors and attitude ring tracking errors;
(3) designing an extended state interference observer of a four-rotor unmanned aerial vehicle position and attitude subsystem;
(4) aiming at a four-rotor unmanned aerial vehicle position subsystem, a composite dynamic inverse controller is designed by introducing virtual control quantity;
(5) converting the virtual control quantity of the position ring into a required lift instruction and an attitude instruction of the attitude ring of the quad-rotor unmanned aerial vehicle through algebraic conversion;
(6) aiming at a four-rotor unmanned aerial vehicle attitude subsystem, a composite dynamic inverse controller is designed, the magnitude of the torque required by three axial directions is obtained, and high-precision tracking of complex tracks is realized.
Further, the step (1) includes the steps of:
(11) constructing a position subsystem model of the disturbed quad-rotor unmanned aerial vehicle:
wherein X, y, z represent the position of the quad-rotor unmanned aerial vehicle, and the positive direction of the X axis is defined as the tangential direction along the local meridian and points to the positive north; the Y-axis positive direction is defined as the tangential direction of the local latitude lines and points to the oriental; the Z-axis forward direction is defined as perpendicular to the local horizontal plane and pointing in the direction of the geocentric according to the right-hand rule, Dx,Dy,DzRepresenting lumped disturbances in three axes, x representing x-axis displacement of the quad-rotor drone,
represents the x axial velocity; y represents quad-rotor unmanned plane y axisThe displacement is carried out towards the direction of the displacement,
represents the y-axis velocity; z represents the z-axial displacement of the quad-rotor drone,
represents the z-axis velocity; phi, theta and psi represent the postures of the quadrotor unmanned aerial vehicle, phi represents the roll angle of the quadrotor unmanned aerial vehicle, theta represents the pitch angle of the quadrotor unmanned aerial vehicle, and psi represents the yaw angle of the quadrotor unmanned aerial vehicle; m represents the mass of the quad-rotor unmanned aerial vehicle, g represents the acceleration of gravity, UPRepresenting the total lift, k, produced by a quad-rotor dronedRepresenting a velocity damping coefficient;
(12) constructing a disturbed quad-rotor unmanned aerial vehicle attitude subsystem model:
wherein, wx，wyAnd wzRepresenting angular velocities of rotation about the x, y and z axes; j. the design is a squarex，JyAnd JzRepresenting moments of inertia about the x, y and z axes; tau isx，τyAnd τzRepresenting moments acting on the x, y and z axes;
DAx,DAy,DAzrepresents lumped interference in three axes; to simplify writing, the following definitions are introduced:
wherein sin x ═ sx,cos x＝cx,tan x＝tx(ii) a The dynamics of the quad-rotor drone attitude subsystem can then be rewritten as follows:
the attitude angle second order dynamics can be obtained according to the attitude dynamic equation:
wherein,
the derivative of W with respect to time is indicated,
and
representing the first and second derivatives of Θ, respectively.
Further, the step (2) is realized as follows:
the position tracking error is defined as: e.g. of the typex＝x-xd,ey＝y-yd,ez＝z-zdWherein x isd,yd,zdFor the track reference signal, considering the environmental interference such as external wind, a position tracking error subsystem can be obtained:
defining an attitude tracking error equation:
wherein, thetad＝[φdθdψd]TFor the desired attitude angle, the attitude system tracking error dynamics can be obtained:
the attitude angle tracking error system dynamics can be obtained:
wherein D isLA∈R3The lumped interference in the attitude tracking error system is expressed as follows:
further, the step (3) specifically includes the following steps:
(31) for a position subsystem design extended state observer of a quad-rotor unmanned aerial vehicle, a virtual control quantity a is introducedxu，ayuAnd azuAn asymptotic estimate of the lumped interference of the three position channels is achieved:
x, Y and the Z-axis extended state observer can be designed to be:
wherein lx1、lx2、ly1、ly2、lz1、lz2The observer parameters are normal numbers,
respectively representing the estimated values of the position triaxial lumped interference;
(32) designing an extended state observer aiming at an attitude tracking error subsystem to realize asymptotic estimation of the attitude angle tracking error change rate and the total disturbance:
wherein L isA1,LA2,LA3Is observer gain, and is a three-dimensional positive diagonal matrix,
and
are respectively as
And DLAAn estimate of (d).
Further, the step (4) is realized as follows:
by introducing virtual control quantity, aiming at a position subsystem, a composite dynamic inverse controller is designed as follows:
wherein, KXP、KXD、KYP、KYD、KZP、KZDAre controller parameters and are all normal numbers.
Further, the step (5) is realized as follows:
further, the step (6) is realized as follows:
wherein,
are controller parameters and are all positive diagonal matrices.
Has the advantages that: compared with the prior art, the invention has the beneficial effects that: 1. the nonlinear characteristic of the system is fully utilized, the nominal nonlinearity is counteracted in a feedback mode in a feedback channel, the adjusting pressure based on error feedback is reduced, and the parameter adjusting difficulty of the controller is obviously reduced; 2. the composite dynamic inverse controller is constructed by combining interference estimation information and a dynamic inverse algorithm, real-time dynamic feedforward compensation is carried out on multi-source interference, and the anti-interference performance and robustness of the system are obviously improved; 3. the method provided by the invention obviously improves the tracking precision of the quad-rotor unmanned aerial vehicle on the complex track, can be popularized and applied to high-precision control of other aircrafts, and has a wide application prospect.
Drawings
FIG. 1 is a block diagram of a full-loop composite dynamic inverse trajectory tracking control method employed in the present invention;
FIG. 2 is a diagram showing the effect of a quad-rotor unmanned aerial vehicle on tracking a spatial three-dimensional cylindrical trajectory under the action of a reference dynamic inverse controller (BNDIC) and the proposed composite dynamic inverse controller (CNDIC);
fig. 3 is a graph of response of three channels of a quadrotor drone under the action of a reference dynamic inverse controller (BNDIC) and the proposed composite dynamic inverse controller (CNDIC);
fig. 4 is a graph of tracking error of three-channel position of a quadrotor drone under the action of a reference dynamic inverse controller (BNDIC) and the proposed composite dynamic inverse controller (CNDIC);
figure 5 is a graph of the response of the control input to a quad-rotor drone under the influence of a baseline dynamic inverse controller (BNDIC) and the proposed composite dynamic inverse controller (CNDIC).
Detailed Description
The present invention is described in further detail below with reference to the attached drawing figures.
Fig. 1 is a block diagram of a composite dynamic inverse full-loop trajectory tracking control structure employed in the present invention. The invention provides a full-loop composite dynamic reverse tracking control method for a four-rotor unmanned aerial vehicle with a complex track, which comprises the following specific steps of:
step 1: and constructing a disturbed four-rotor unmanned aerial vehicle full-loop system model comprising a four-rotor unmanned aerial vehicle position loop subsystem and an attitude loop subsystem.
The position subsystem model of the disturbed quad-rotor drone is described as shown in equation (1):
wherein X, y, z represent the position of the quad-rotor drone, and the positive X-axis direction is defined as the tangential direction along the local meridian, pointing to the positive north; the Y-axis positive direction is defined as the tangential direction of the local latitude lines and points to the oriental; the Z-axis forward direction is defined as being perpendicular to the local horizontal plane and pointing in the direction of the geocentric according to the right-hand rule. Dx,Dy,DzRepresenting lumped disturbances in three axes, x representing x-axis displacement of the quad-rotor drone,
represents the x axial velocity; y represents the quad-rotor drone y axial displacement,
represents the y-axis velocity; z represents the z-axial displacement of the quad-rotor drone,
represents the z-axis velocity; phi, theta and psi represent the postures of the quadrotor unmanned aerial vehicle, phi represents the roll angle of the quadrotor unmanned aerial vehicle, theta represents the pitch angle of the quadrotor unmanned aerial vehicle, and psi represents the yaw angle of the quadrotor unmanned aerial vehicle; m represents the mass of the quad-rotor unmanned aerial vehicle, g represents the acceleration of gravity, UPRepresenting the total lift, k, produced by a quad-rotor dronedRepresenting the velocity damping coefficient.
The disturbed quad-rotor unmanned aerial vehicle attitude subsystem model is described as shown in the formulas (2) and (3):
wherein, wx，wyAnd wzRepresenting angular velocities of rotation about the x, y and z axes; j. the design is a squarex，JyAnd JzRepresenting moments of inertia about the x, y and z axes; tau isx，τyAnd τzRepresenting moments acting on the x, y and z axes;
DAx,DAy,DAzrepresenting lumped interference in three axes. To simplify writing, the following definitions are introduced:
wherein sin x ═ sx,cos x＝cx,tan x＝tx. The dynamics of the quad-rotor drone attitude subsystem can then be rewritten as follows:
the attitude angle second order dynamics can be obtained according to the attitude dynamic equation:
wherein,
the derivative of W with respect to time is indicated,
and
representing the first and second derivatives of Θ, respectively.
Since trajectory tracking of the unmanned rotorcraft position loop is achieved by changing the attitude angle, the control target of the attitude loop is set to track the virtual attitude angle command.
Step 2: the trajectory tracking problem of the quad-rotor unmanned aerial vehicle is converted into the stabilization problem of the tracking error of the position ring and the tracking error of the attitude ring.
The position tracking error is defined as: e.g. of the typex＝x-xd,ey＝y-yd,ez＝z-zdWherein x isd,yd,zdIs a track reference signal. Considering the external wind and other environmental interferences, a position tracking error subsystem can be obtained:
defining an attitude tracking error equation:
wherein, thetad＝[φdθdψd]TFor the desired attitude angle, the attitude system tracking error dynamics can be obtained:
the attitude angle tracking error system dynamics can be obtained:
wherein D isLA∈R3The lumped interference in the attitude tracking error system is expressed as follows:
and step 3: an extended state disturbance observer of a four-rotor unmanned aerial vehicle position and attitude subsystem is designed.
An extended state observer is designed for a position subsystem (1) of a quad-rotor unmanned aerial vehicle to achieve asymptotic estimation of lumped interference of three position channels. The design method comprises the following specific steps:
for the analysis of the position subsystem (1) of the quad-rotor unmanned aerial vehicle, the following virtual control quantities are introduced for the convenience of controller design:
x, Y and the Z-axis extended state observer can be designed to be:
wherein lx1、lx2、ly1、ly2、lz1、lz2The observer parameters are normal numbers;
respectively, representing estimates of the positional three-axis lumped interference.
Since the change rate of the virtual attitude angle command cannot be directly obtained, the change rate of the attitude angle tracking error cannot be directly obtained, and needs to be estimated. The following extended state observer is designed for the attitude tracking error subsystem (7) to achieve asymptotic estimation of attitude angle tracking error change rate and total disturbance:
wherein L isA1,LA2,LA3Is observer gain, and is a three-dimensional positive diagonal matrix,
and
are respectively as
And DLAAn estimate of (d).
And 4, step 4: aiming at a four-rotor unmanned aerial vehicle position subsystem, a composite dynamic inverse controller is designed by introducing virtual control quantity.
By introducing virtual control quantity, aiming at a position subsystem, the following composite dynamic inverse controller is designed:
wherein, KXP、KXD、KYP、KYD、KZP、KZDAre controller parameters and they are all normal numbers.
And 5: through algebraic conversion, turn into the virtual control volume of position ring required lift instruction and the gesture instruction of four rotor unmanned aerial vehicle attitude rings.
Step 6: aiming at the four-rotor unmanned aerial vehicle attitude subsystem, a composite dynamic inverse controller is designed to obtain the magnitude of the three axial required moments.
And (3) constructing a composite dynamic inverse controller by utilizing the attitude ring lumped interference estimation information and the attitude angle tracking error change rate estimation information:
wherein,
are controller parameters and are all positive diagonal matrices.
In order to verify the excellent anti-interference performance of the invention, the simulation comparison verification of the quadrotor unmanned aerial vehicle is carried out on the algorithm and the traditional nonlinear dynamic inverse algorithm based on MATLAB simulation environment under the condition of fully considering the existence of external interference. The initial value of the simulation process is set as:
x(0)＝0,y(0)＝0,z(0)＝0
φ(0)＝0,θ(0)＝0,ψ(0)＝0
wx(0)＝0,wy(0)＝0,wz(0)＝0
the position expectation command and the heading angle expectation value zero are set as follows:
xc(t)＝0.5sin(0.5t)，yc(t)＝0.5cos(0.5t)，
zc(t)＝-2-0.1t，ψc(t)＝cos(0.5t)
the external interference in the simulation process is set as follows:
Dx＝-2,Dy＝2.3,Dz＝1.6,
DAx＝-0.2(1+0.3sin0.2πt),
DAy＝0.13(1+0.4sin0.2πt),
DAz＝-0.12(1+0.2sin0.2πt)
the form and controller parameters of the proposed Composite Nonlinear Dynamic Inverse Controller (CNDIC) have been given in the design examples. The form and control parameters of a Baseline Nonlinear Dynamic Inverse Controller (BNDIC) used for comparison were designed as follows:
the full-loop composite dynamic inverse tracking control method for the complicated track of the quad-rotor unmanned aerial vehicle provided by the invention realizes high-precision tracking control of the cylindrical complicated track of the quad-rotor unmanned aerial vehicle, and adopts full-loop composite dynamic inverse control and classical dynamic inverse control for comparison respectively. Fig. 2 to 4 are an effect diagram of a disturbed quad-rotor unmanned aerial vehicle tracking a spatial three-dimensional cylindrical track, a three-channel position response curve diagram and a three-channel position tracking error curve diagram respectively under the action of a reference dynamic inverse controller (BNDIC) and the proposed composite dynamic inverse controller (CNDIC), and it can be seen that the anti-interference performance of the proposed full-loop composite dynamic inverse control method is obviously superior to that of the conventional dynamic inverse control method. Figure 5 shows a graph of the response of the control input to the quad-rotor drone under the action of the baseline dynamic inverse controller (BNDIC) and the proposed composite dynamic inverse controller (CNDIC), which shows that the control input is within a certain clipping range.
In conclusion, the four-rotor unmanned aerial vehicle tracking system can ensure that the four-rotor unmanned aerial vehicle has higher track tracking precision and stronger anti-interference performance.
Claims (7)
1. The full-loop composite dynamic inverse tracking control method for the complex track of the quad-rotor unmanned aerial vehicle is characterized by comprising the following steps of:
(1) constructing a disturbed four-rotor unmanned aerial vehicle full-loop system model comprising a four-rotor unmanned aerial vehicle position loop subsystem and an attitude loop subsystem;
(2) the problem of trajectory tracking of the quad-rotor unmanned aerial vehicle is converted into the stabilization problem of position ring tracking errors and attitude ring tracking errors;
(3) designing an extended state interference observer of a four-rotor unmanned aerial vehicle position and attitude subsystem;
(4) aiming at a four-rotor unmanned aerial vehicle position subsystem, a composite dynamic inverse controller is designed by introducing virtual control quantity;
(5) converting the virtual control quantity of the position ring into a required lift instruction and an attitude instruction of the attitude ring of the quad-rotor unmanned aerial vehicle through algebraic conversion;
(6) aiming at a four-rotor unmanned aerial vehicle attitude subsystem, a composite dynamic inverse controller is designed, the magnitude of the torque required by three axial directions is obtained, and high-precision tracking of complex tracks is realized.
2. The method according to claim 1, wherein the step (1) comprises the following steps:
(11) constructing a position subsystem model of the disturbed quad-rotor unmanned aerial vehicle:
wherein X, y, z represent the position of the quad-rotor unmanned aerial vehicle, and the positive direction of the X axis is defined as the tangential direction along the local meridian and points to the positive north; the Y-axis positive direction is defined as the tangential direction of the local latitude lines and points to the oriental; the Z-axis forward direction is defined as perpendicular to the local horizontal plane and pointing in the direction of the geocentric according to the right-hand rule, Dx,Dy,DzRepresenting lumped disturbances in three axes, x representing x-axis displacement of the quad-rotor drone,
represents the x axial velocity; y represents the quad-rotor drone y axial displacement,
represents the y-axis velocity; z represents the z-axial displacement of the quad-rotor drone,
represents the z-axis velocity; phi, theta and psi represent the postures of the quadrotor unmanned aerial vehicle, phi represents the roll angle of the quadrotor unmanned aerial vehicle, theta represents the pitch angle of the quadrotor unmanned aerial vehicle, and psi represents the yaw angle of the quadrotor unmanned aerial vehicle; m represents the mass of the quad-rotor unmanned aerial vehicle, g represents the acceleration of gravity, UPRepresenting the total lift, k, produced by a quad-rotor dronedRepresenting a velocity damping coefficient;
(12) constructing a disturbed quad-rotor unmanned aerial vehicle attitude subsystem model:
wherein, wx，wyAnd wzRepresenting angular velocities of rotation about the x, y and z axes; j. the design is a squarex，JyAnd JzRepresenting moments of inertia about the x, y and z axes; tau isx，τyAnd τzRepresenting moments acting on the x, y and z axes; dAx,DAy,DAzRepresents lumped interference in three axes; to simplify writing, the following definitions are introduced:
wherein sin x ═ sx,cos x＝cx,tan x＝tx(ii) a The dynamics of the quad-rotor drone attitude subsystem can then be rewritten as follows:
the attitude angle second order dynamics can be obtained according to the attitude dynamic equation:
wherein,
the derivative of W with respect to time is indicated,
and
representing the first and second derivatives of Θ, respectively.
3. The method for controlling the full-loop composite dynamic inverse tracking of the complex track of the quad-rotor unmanned aerial vehicle according to claim 1, wherein the step (2) is realized by the following steps:
the position tracking error is defined as: e.g. of the typex＝x-xd,ey＝y-yd,ez＝z-zdWherein x isd,yd,zdFor the track reference signal, considering the environmental interference such as external wind, a position tracking error subsystem can be obtained:
defining an attitude tracking error equation:
wherein, thetad＝[φdθdψd]TFor the desired attitude angle, the attitude system tracking error dynamics can be obtained:
the attitude angle tracking error system dynamics can be obtained:
wherein D isLA∈R3The lumped interference in the attitude tracking error system is expressed as follows:
4. the full-loop composite dynamic inverse tracking control method for the complex track of the quad-rotor unmanned aerial vehicle as claimed in claim 1, wherein the step (3) specifically comprises the following steps:
(31) for a position subsystem design extended state observer of a quad-rotor unmanned aerial vehicle, a virtual control quantity a is introducedxu，ayuAnd azuAn asymptotic estimate of the lumped interference of the three position channels is achieved:
x, Y and the Z-axis extended state observer can be designed to be:
wherein lx1、lx2、ly1、ly2、lz1、lz2The observer parameters are normal numbers,
respectively representing the estimated values of the position triaxial lumped interference;
(32) designing an extended state observer aiming at an attitude tracking error subsystem to realize asymptotic estimation of the attitude angle tracking error change rate and the total disturbance:
wherein L isA1,LA2,LA3Is observer gain, and is a three-dimensional positive diagonal matrix,
and
are respectively as
And DLAAn estimate of (d).
5. The full-loop composite dynamic inverse tracking control method for the complex track of the quad-rotor unmanned aerial vehicle as claimed in claim 1, wherein the step (4) is realized by the following steps:
by introducing virtual control quantity, aiming at a position subsystem, a composite dynamic inverse controller is designed as follows:
wherein, KXP、KXD、KYP、KYD、KZP、KZDAre controller parameters and are all normal numbers.
6. The full-loop composite dynamic inverse tracking control method for the complex track of the quad-rotor unmanned aerial vehicle according to claim 5, wherein the step (5) is realized by the following steps:
7. the full-loop composite dynamic inverse tracking control method for the complex track of the quad-rotor unmanned aerial vehicle according to claim 1, wherein the step (6) is realized by the following steps:
wherein,
are controller parameters and are all positive diagonal matrices.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010441724.5A CN111650951B (en) | 2020-05-22 | 2020-05-22 | Full-loop composite dynamic inverse tracking control method for complex track of quad-rotor unmanned aerial vehicle |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010441724.5A CN111650951B (en) | 2020-05-22 | 2020-05-22 | Full-loop composite dynamic inverse tracking control method for complex track of quad-rotor unmanned aerial vehicle |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN111650951A true CN111650951A (en) | 2020-09-11 |
| CN111650951B CN111650951B (en) | 2021-09-17 |
Family
ID=72352712
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010441724.5A Active CN111650951B (en) | 2020-05-22 | 2020-05-22 | Full-loop composite dynamic inverse tracking control method for complex track of quad-rotor unmanned aerial vehicle |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN111650951B (en) |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112462798A (en) * | 2020-12-04 | 2021-03-09 | 三生万物(北京)人工智能技术有限公司 | Unmanned aerial vehicle and method for improving flight performance of unmanned aerial vehicle |
| CN112462796A (en) * | 2020-11-28 | 2021-03-09 | 中国人民解放军海军航空大学青岛校区 | Adaptive inversion control system and method for attitude angle stabilization of rigid aircraft |
| CN113110554A (en) * | 2021-04-30 | 2021-07-13 | 南京航空航天大学 | Four-rotor unmanned aerial vehicle composite continuous rapid terminal sliding mode attitude control method |
| CN114578837A (en) * | 2022-02-18 | 2022-06-03 | 南京航空航天大学 | Active fault-tolerant anti-interference trajectory tracking control method of unmanned helicopter considering actuator faults |
Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103092213A (en) * | 2013-01-21 | 2013-05-08 | 南京航空航天大学 | Trajectory tracking controlling method of six-rotor-wing air vehicle |
| CN105739513A (en) * | 2016-02-05 | 2016-07-06 | 北京航空航天大学 | Quadrotor flying robot non-linear trajectory tracking controller and tracking control method thereof |
| CN109597426A (en) * | 2018-11-13 | 2019-04-09 | 上海无线电设备研究所 | Based on L1The four-rotor helicopter Trajectory Tracking Control method of self adaptive control |
| CN110825122A (en) * | 2019-10-08 | 2020-02-21 | 南京航空航天大学 | Active anti-interference tracking control method for circular track of quad-rotor unmanned aerial vehicle |
| CN110850887A (en) * | 2019-10-10 | 2020-02-28 | 南京航空航天大学 | Composite dynamic inverse anti-interference attitude control method for quad-rotor unmanned aerial vehicle |
| CN111007877A (en) * | 2019-11-20 | 2020-04-14 | 江苏信息职业技术学院 | Global robust self-adaptive trajectory tracking control method of four-rotor aircraft |
| CN111026160A (en) * | 2019-12-26 | 2020-04-17 | 华中科技大学 | Trajectory tracking control method for quad-rotor unmanned aerial vehicle |
| CN111123967A (en) * | 2020-01-02 | 2020-05-08 | 南京航空航天大学 | Fixed-wing unmanned aerial vehicle carrier landing control method based on adaptive dynamic inversion |
-
2020
- 2020-05-22 CN CN202010441724.5A patent/CN111650951B/en active Active
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103092213A (en) * | 2013-01-21 | 2013-05-08 | 南京航空航天大学 | Trajectory tracking controlling method of six-rotor-wing air vehicle |
| CN105739513A (en) * | 2016-02-05 | 2016-07-06 | 北京航空航天大学 | Quadrotor flying robot non-linear trajectory tracking controller and tracking control method thereof |
| CN109597426A (en) * | 2018-11-13 | 2019-04-09 | 上海无线电设备研究所 | Based on L1The four-rotor helicopter Trajectory Tracking Control method of self adaptive control |
| CN110825122A (en) * | 2019-10-08 | 2020-02-21 | 南京航空航天大学 | Active anti-interference tracking control method for circular track of quad-rotor unmanned aerial vehicle |
| CN110850887A (en) * | 2019-10-10 | 2020-02-28 | 南京航空航天大学 | Composite dynamic inverse anti-interference attitude control method for quad-rotor unmanned aerial vehicle |
| CN111007877A (en) * | 2019-11-20 | 2020-04-14 | 江苏信息职业技术学院 | Global robust self-adaptive trajectory tracking control method of four-rotor aircraft |
| CN111026160A (en) * | 2019-12-26 | 2020-04-17 | 华中科技大学 | Trajectory tracking control method for quad-rotor unmanned aerial vehicle |
| CN111123967A (en) * | 2020-01-02 | 2020-05-08 | 南京航空航天大学 | Fixed-wing unmanned aerial vehicle carrier landing control method based on adaptive dynamic inversion |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112462796A (en) * | 2020-11-28 | 2021-03-09 | 中国人民解放军海军航空大学青岛校区 | Adaptive inversion control system and method for attitude angle stabilization of rigid aircraft |
| CN112462798A (en) * | 2020-12-04 | 2021-03-09 | 三生万物(北京)人工智能技术有限公司 | Unmanned aerial vehicle and method for improving flight performance of unmanned aerial vehicle |
| CN113110554A (en) * | 2021-04-30 | 2021-07-13 | 南京航空航天大学 | Four-rotor unmanned aerial vehicle composite continuous rapid terminal sliding mode attitude control method |
| CN114578837A (en) * | 2022-02-18 | 2022-06-03 | 南京航空航天大学 | Active fault-tolerant anti-interference trajectory tracking control method of unmanned helicopter considering actuator faults |
Also Published As
| Publication number | Publication date |
|---|---|
| CN111650951B (en) | 2021-09-17 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN111766899B (en) | Interference observer-based quad-rotor unmanned aerial vehicle cluster anti-interference formation control method | |
| CN111650951B (en) | Full-loop composite dynamic inverse tracking control method for complex track of quad-rotor unmanned aerial vehicle | |
| CN109991991B (en) | Robust fault-tolerant tracking method for unmanned helicopter | |
| CN110850887B (en) | Composite dynamic inverse anti-interference attitude control method for quad-rotor unmanned aerial vehicle | |
| CN109765918B (en) | Robust adaptive compensation control method for unmanned helicopter | |
| CN106325291B (en) | Sliding mode control law and ESO (electronic stability program) based four-rotor aircraft attitude control method and system | |
| CN112346470A (en) | Four-rotor attitude control method based on improved active disturbance rejection control | |
| CN110825122B (en) | Active anti-interference tracking control method for circular track of quad-rotor unmanned aerial vehicle | |
| CN110320925B (en) | Four-rotor aircraft safety control method based on high-order disturbance observer | |
| CN109062042B (en) | Limited time track tracking control method of rotor craft | |
| CN112015192B (en) | Self-healing quad-rotor unmanned aerial vehicle anti-interference control method and system | |
| CN109885074B (en) | Finite time convergence attitude control method for quad-rotor unmanned aerial vehicle | |
| CN112666960B (en) | L1 augmentation self-adaption-based control method for rotary wing aircraft | |
| CN110377044B (en) | Finite time height and attitude tracking control method of unmanned helicopter | |
| CN117289598B (en) | Method and system for controlling backstepping sliding mode of aircraft | |
| CN110275542B (en) | Four-rotor aircraft control method based on self-adaptive finite time control | |
| CN113156995A (en) | Unmanned helicopter attitude control method under actuator fault | |
| CN115202213A (en) | Four-rotor aircraft control method based on active disturbance rejection control | |
| CN109976364B (en) | Attitude decoupling control method for six-rotor aircraft | |
| Du et al. | Advanced quadrotor takeoff control based on incremental nonlinear dynamic inversion and integral extended state observer | |
| CN111857171B (en) | Unmanned aerial vehicle control method based on quality self-adaptive multilayer neural network | |
| Song et al. | Research on attitude control of quadrotor uav based on active disturbance rejection control | |
| CN116719226A (en) | Four-rotor unmanned aerial vehicle disturbance suppression fault-tolerant control method under unknown external disturbance | |
| CN116203840A (en) | Adaptive gain scheduling control method for reusable carrier | |
| Peng et al. | Nonlinear flight control design for maneuvering flight of quadrotors in high speed and large acceleration |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |