CN114564047B - Unmanned aerial vehicle constant-speed flight control method considering meteorological conditions - Google Patents

Unmanned aerial vehicle constant-speed flight control method considering meteorological conditions Download PDF

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CN114564047B
CN114564047B CN202210455586.5A CN202210455586A CN114564047B CN 114564047 B CN114564047 B CN 114564047B CN 202210455586 A CN202210455586 A CN 202210455586A CN 114564047 B CN114564047 B CN 114564047B
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unmanned aerial
aerial vehicle
sliding mode
outer ring
speed
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CN114564047A (en
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阚梓
李道春
郑勇峰
姚卓尔
邵浩原
向锦武
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Avic Chengdu Uav System Co ltd
Beihang University
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Avic Chengdu Uav System Co ltd
Beihang University
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    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
    • 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
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
    • Y02T90/00—Enabling technologies or technologies with a potential or indirect contribution to GHG emissions mitigation

Abstract

The invention discloses an unmanned aerial vehicle constant-speed flight control method considering meteorological conditions, which comprises the following steps of establishing a flight dynamics equation of an unmanned aerial vehicle; converting a flight dynamics equation into an unmanned aerial vehicle state space equation, and adding a meteorological condition disturbance item; designing a sliding mode surface by using an unmanned aerial vehicle state space equation, carrying out Yapnov stability judgment on the sliding mode surface to obtain an inner-outer ring controller, designing a self-adaptation law corresponding to the meteorological condition disturbance term, and substituting the self-adaptation law into the inner-outer ring controller to obtain an inner-outer ring sliding mode controller capable of realizing parameter self-adaptation; set up a flying speed, when unmanned aerial vehicle receives meteorological condition disturbance, through parameter self-adaptation's interior outer ring sliding mode controller realizes unmanned aerial vehicle constant speed flight. The method adopts parameter self-adaptation, has obvious inhibition effect on disturbance brought to the unmanned aerial vehicle by different complex meteorology, has relatively high control convergence speed, and does not bring large extra weight to the unmanned aerial vehicle.

Description

Unmanned aerial vehicle constant-speed flight control method considering meteorological conditions
Technical Field
The invention belongs to the field of unmanned aerial vehicle flight control, and particularly relates to an unmanned aerial vehicle constant-speed flight control method considering meteorological conditions.
Background
In recent years, unmanned aerial vehicles have become increasingly a research hotspot in the field of aviation. Unmanned aerial vehicles, as a product of modern science and technology, have an irreplaceable status in the civil field and also play a great role in the military field, so that the research and development investment on unmanned aerial vehicles is increased in each country. Along with the further expansion of unmanned aerial vehicle application range, it inevitably can meet complex meteorological conditions such as rainfall, icing, gust at the flight in-process, these complex meteorology can bring certain influence to unmanned aerial vehicle's flight, for example, raindrop striking unmanned aerial vehicle under the rainfall environment can bring additional power and additional moment, icing can worsen unmanned aerial vehicle flight performance, the gust also can add additional aerodynamic force and moment for unmanned aerial vehicle, under the influence of these complex meteorological factors, unmanned aerial vehicle just hardly continues to keep predetermined speed flight. Therefore, the research on the constant-speed flight control method of the unmanned aerial vehicle under the complex meteorological condition has important significance for the development of the unmanned aerial vehicle.
Disclosure of Invention
The invention aims to solve the problem that the unmanned aerial vehicle cannot keep the flight speed due to interference under the complex meteorological conditions, provides a constant-speed flight control method of the unmanned aerial vehicle considering the meteorological conditions, and provides technical reference for the unmanned aerial vehicle to fly under the complex meteorological conditions. By designing a sliding mode surface and adopting a Lyapunov direct method to design a self-adaptive law and a controller according to a stability criterion, the unmanned aerial vehicle can keep the flying speed under the influence of meteorological factors.
In order to achieve the purpose, the invention adopts the following technical scheme:
an unmanned aerial vehicle constant-speed flight control method considering meteorological conditions comprises the following steps:
s1, establishing a flight dynamics equation of the unmanned aerial vehicle under the axis system of the unmanned aerial vehicle based on the plane earth hypothesis;
s2, converting the flight dynamics equation into an unmanned aerial vehicle state space equation, and adding a meteorological condition disturbance term;
s3, designing a sliding mode surface by using an unmanned aerial vehicle state space equation, judging the Yapunoff stability of luggage on the sliding mode surface to obtain an inner-outer ring controller, designing a self-adaptation law corresponding to the meteorological condition disturbance term, and substituting the self-adaptation law into the inner-outer ring controller to obtain an inner-outer ring sliding mode controller capable of realizing parameter self-adaptation;
and S4, setting a flying speed, and when the unmanned aerial vehicle is disturbed by meteorological conditions, realizing constant-speed flying of the unmanned aerial vehicle through the parameter self-adaptive inner and outer ring sliding mode controller.
Further, in step S2, the unmanned aerial vehicle state space equation after the meteorological condition disturbance term is added specifically is:
Figure 521085DEST_PATH_IMAGE001
wherein
Figure 592946DEST_PATH_IMAGE002
In the form of a matrix of state quantities,
Figure 501996DEST_PATH_IMAGE003
in order to control the matrix of quantities,
Figure 633900DEST_PATH_IMAGE004
in order to be a matrix of the system,
Figure 362822DEST_PATH_IMAGE005
in order to input the matrix, the input matrix is,
Figure 238374DEST_PATH_IMAGE006
representing disturbances caused by meteorological conditions.
Further, in step S3, the control amount of the outer loop controller is set to
Figure 500466DEST_PATH_IMAGE007
The control quantity of the inner ring controller is
Figure 537692DEST_PATH_IMAGE008
The inner and outer ring state space equations are specifically
Figure 19489DEST_PATH_IMAGE009
Wherein
Figure 433153DEST_PATH_IMAGE010
,
Figure 51216DEST_PATH_IMAGE011
，
Figure 524922DEST_PATH_IMAGE012
，
Figure 228436DEST_PATH_IMAGE013
；
Figure 445791DEST_PATH_IMAGE014
Figure 183940DEST_PATH_IMAGE015
Figure 562969DEST_PATH_IMAGE016
Figure 520823DEST_PATH_IMAGE017
Wherein, the first and the second end of the pipe are connected with each other,
Figure 276289DEST_PATH_IMAGE018
Figure 868944DEST_PATH_IMAGE019
,
Figure 418874DEST_PATH_IMAGE020
,
Figure 362560DEST_PATH_IMAGE021
；
Figure 656138DEST_PATH_IMAGE022
respectively representing the speed of the machine body in the X, Y and Z directions;
Figure 368879DEST_PATH_IMAGE023
respectively representing a rolling angular velocity, a pitch angular velocity and a yaw angular velocity;
Figure 355289DEST_PATH_IMAGE024
respectively representing a pitch angle and a roll angle;
Figure 255112DEST_PATH_IMAGE025
respectively representing roll moment, pitch moment and yaw moment;
Figure 352381DEST_PATH_IMAGE026
respectively represents the rotational inertia of the unmanned aerial vehicle to the X axis, the Y axis and the Z axis,
Figure 689603DEST_PATH_IMAGE027
representing the products of inertia of the drone on the X and Z axes;
Figure 581335DEST_PATH_IMAGE028
respectively representing that the unmanned aerial vehicle is subjected to pneumatic resultant force along an X axis, a Y axis and a Z axis;
Figure 234033DEST_PATH_IMAGE029
respectively representing components of the engine thrust on an X axis, a Y axis and a Z axis;
Figure 134993DEST_PATH_IMAGE030
which represents the acceleration of the force of gravity,
Figure 556747DEST_PATH_IMAGE031
representing the drone quality;
Figure 619381DEST_PATH_IMAGE032
represents a dynamic pressure;
Figure 759376DEST_PATH_IMAGE033
showing the stretching length;
Figure 198447DEST_PATH_IMAGE034
representing the wing area;
Figure 740287DEST_PATH_IMAGE035
representing the flight speed of the unmanned aerial vehicle;
Figure 973822DEST_PATH_IMAGE036
respectively representing an aileron deflection angle, a rudder deflection angle and an elevator deflection angle;
Figure 102578DEST_PATH_IMAGE037
respectively representing the moment coefficients along the X, Y and Z axes of the machine body;
Figure 79761DEST_PATH_IMAGE038
respectively representing the rate of change of a roll torque coefficient relative to the deflection angle of the aileron, the rate of change of the roll torque coefficient relative to the rudder deflection angle, the rate of change of the roll torque coefficient relative to the roll angular speed and the rate of change of the roll torque coefficient relative to the yaw angular speed;
Figure 476107DEST_PATH_IMAGE039
respectively representing the rate of change of a pitch moment coefficient relative to the deflection angle of the elevator and the rate of change of the pitch moment coefficient relative to the pitch angle speed;
Figure 146123DEST_PATH_IMAGE040
the yaw moment rate of change with respect to the aileron yaw angle, the yaw moment rate of change with respect to the rudder yaw angle, the yaw moment rate of change with respect to the roll angle speed, and the yaw moment rate of change with respect to the yaw angle speed are respectively indicated.
Further, in step S3, for the outer ring controller, the sliding surface is
Figure 995130DEST_PATH_IMAGE041
；
For an inner ring controller, the sliding mode surface is
Figure 41584DEST_PATH_IMAGE042
；
Wherein
Figure 26857DEST_PATH_IMAGE043
Represents the function of the sliding mode surface,
Figure 867774DEST_PATH_IMAGE044
which represents an error in the form of,K i represents a constant coefficient of the output signal of the amplifier,twhich represents the time of day,
Figure 204078DEST_PATH_IMAGE045
representing the expected value.
Further, in step S3, the determination of the stability of the sliding-mode surface luggage japonov to obtain the inner-outer-ring controller is specifically that
Consider the following Lyapunov candidate function:
Figure 788643DEST_PATH_IMAGE046
wherein the content of the first and second substances,W 1 is a first candidate function;
derivation of this can yield:
Figure 658116DEST_PATH_IMAGE047
to make it possible to
Figure 669935DEST_PATH_IMAGE048
For negative, the inner and outer ring controllers are designed as follows:
Figure 493534DEST_PATH_IMAGE049
wherein
Figure 616211DEST_PATH_IMAGE050
In order to determine the constant coefficient to be determined,
Figure 576077DEST_PATH_IMAGE051
for disturbing complex weather
Figure 24376DEST_PATH_IMAGE052
For time invariant disturbances, sgn is a sign function;
setting up
Figure 335271DEST_PATH_IMAGE053
，
Figure 261639DEST_PATH_IMAGE054
Which is indicative of the error in the estimation of the disturbance,i=1,2。
further, in the step S3, the adaptive law corresponding to the meteorological condition disturbance term is designed as
Consider the following Lyapunov candidate function:
Figure 341590DEST_PATH_IMAGE055
wherein the content of the first and second substances,W 2 in order to be a second candidate function,
Figure 196676DEST_PATH_IMAGE056
is a constant coefficient to be determined;
derivation of this can yield:
Figure 729289DEST_PATH_IMAGE057
to make it possible to
Figure 459347DEST_PATH_IMAGE058
For negative, the adaptation law is obtained as:
Figure 393805DEST_PATH_IMAGE059
。
further, in step S3, the inner and outer ring sliding mode controller is specifically an
Outer loop sliding mode controller:
Figure 918327DEST_PATH_IMAGE060
wherein the content of the first and second substances,
Figure 203815DEST_PATH_IMAGE061
；
inner ring sliding mode controller:
Figure 206406DEST_PATH_IMAGE062
wherein the content of the first and second substances,
Figure 260950DEST_PATH_IMAGE063
。
compared with the prior art, the invention has the following beneficial effects:
the invention provides an unmanned aerial vehicle constant-speed flight control method considering meteorological conditions, which is characterized in that a sliding mode surface is designed, and a Lyapunov direct method is adopted to stabilize criteria to design a self-adaptive law and a controller, so that the unmanned aerial vehicle can keep constant-speed flight under the influence of meteorological factors. The method provided by the invention adopts a parameter self-adaptive method, so that the disturbance of the unmanned aerial vehicle caused by different complex meteorology is obviously inhibited, the control convergence speed is relatively high, and meanwhile, the control method provided by the invention cannot bring large extra weight to the unmanned aerial vehicle.
Drawings
FIG. 1 is a flow chart of a method for controlling constant-velocity flight of an unmanned aerial vehicle in consideration of meteorological conditions according to the present invention;
fig. 2 is a logic diagram of the inner and outer ring sliding mode controller of the present invention.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings.
An unmanned aerial vehicle constant-speed flight control method considering meteorological conditions is shown in figure 1 and comprises the following steps:
firstly, establishing a flight dynamics equation of the unmanned aerial vehicle as follows:
Figure 956374DEST_PATH_IMAGE064
Figure 729158DEST_PATH_IMAGE065
wherein
Figure 51553DEST_PATH_IMAGE066
As follows:
Figure 960603DEST_PATH_IMAGE018
Figure 826928DEST_PATH_IMAGE019
,
Figure 87008DEST_PATH_IMAGE020
,
Figure 431401DEST_PATH_IMAGE021
；
wherein, the first and the second end of the pipe are connected with each other,
Figure 460537DEST_PATH_IMAGE067
respectively representing the speed of the machine body in the X, Y and Z directions;
Figure 497764DEST_PATH_IMAGE023
respectively representing a rolling angular velocity, a pitch angular velocity and a yaw angular velocity;
Figure 979560DEST_PATH_IMAGE024
respectively representing a pitch angle and a roll angle;
Figure 393224DEST_PATH_IMAGE068
respectively representing roll moment, pitch moment and yaw moment;
Figure 11287DEST_PATH_IMAGE069
respectively represents the rotational inertia of the unmanned aerial vehicle to the X axis, the Y axis and the Z axis,
Figure 986459DEST_PATH_IMAGE027
representing the products of inertia of the drone on the X and Z axes;
Figure 689973DEST_PATH_IMAGE028
respectively representing that the unmanned aerial vehicle is subjected to pneumatic resultant force along an X axis, a Y axis and a Z axis;
Figure 641748DEST_PATH_IMAGE070
respectively representing components of the thrust of the engine on an X axis, a Y axis and a Z axis;
Figure 379897DEST_PATH_IMAGE030
which represents the acceleration of the force of gravity,
Figure 290084DEST_PATH_IMAGE031
indicating the drone quality.
The specific expressions of force and moment are as follows:
Figure 480894DEST_PATH_IMAGE071
Figure 236361DEST_PATH_IMAGE072
the symbols represent the following meanings:
Figure 829016DEST_PATH_IMAGE073
respectively representing an attack angle and a sideslip angle;
Figure 378946DEST_PATH_IMAGE032
represents a dynamic pressure;
Figure 322631DEST_PATH_IMAGE033
showing the stretching length;
Figure 114744DEST_PATH_IMAGE074
representing a chord length;
Figure 827486DEST_PATH_IMAGE034
representing the wing area;
Figure 548317DEST_PATH_IMAGE035
representing the flight speed of the unmanned aerial vehicle;
Figure 713719DEST_PATH_IMAGE036
respectively representing an aileron deflection angle, a rudder deflection angle and an elevator deflection angle;
Figure 810988DEST_PATH_IMAGE075
respectively representing force coefficients along X, Y and Z axes of the machine body;
Figure 378236DEST_PATH_IMAGE076
respectively representing the change rate of the force coefficient along the X axis of the body relative to the deflection angle of the elevator and the change rate of the force coefficient along the Z axis of the body relative to the deflection angle of the elevator;
Figure 269968DEST_PATH_IMAGE077
representing the rate of change of the force coefficient along the Y axis of the body with respect to the aileron deflection angle;
Figure 188246DEST_PATH_IMAGE078
representing the rate of change of the force coefficient along the Y axis of the body with respect to the rudder deflection angle;
Figure 823626DEST_PATH_IMAGE079
respectively representing the force coefficient along the X axisThe pitch angle rate of change, the rate of change of force coefficient along the Y axis with respect to roll angle rate of change, the rate of change of force coefficient along the Y axis with respect to yaw angle rate of change, and the rate of change of force coefficient along the Z axis with respect to pitch angle rate of change;
Figure 245380DEST_PATH_IMAGE080
respectively representing moment coefficients along X, Y and Z axes of the body;
Figure 75058DEST_PATH_IMAGE081
respectively representing the rate of change of a roll torque coefficient relative to the deflection angle of the aileron, the rate of change of the roll torque coefficient relative to the rudder deflection angle, the rate of change of the roll torque coefficient relative to the roll angular speed and the rate of change of the roll torque coefficient relative to the yaw angular speed;
Figure 949473DEST_PATH_IMAGE039
respectively representing the rate of change of a pitch moment coefficient relative to the deflection angle of the elevator and the rate of change of the pitch moment coefficient relative to the pitch angle speed;
Figure 654124DEST_PATH_IMAGE082
the yaw moment rate of change with respect to the aileron yaw angle, the yaw moment rate of change with respect to the rudder yaw angle, the yaw moment rate of change with respect to the roll angle speed, and the yaw moment rate of change with respect to the yaw angle speed are respectively indicated.
Secondly, converting the flight dynamics equation of the unmanned aerial vehicle into an unmanned aerial vehicle state space equation, and adding a meteorological condition disturbance term as follows:
Figure 195964DEST_PATH_IMAGE001
wherein
Figure 429499DEST_PATH_IMAGE002
In the form of a matrix of state quantities,
Figure 56790DEST_PATH_IMAGE003
in order to control the matrix of quantities,
Figure 299552DEST_PATH_IMAGE083
in order to be a matrix of the system,
Figure 430319DEST_PATH_IMAGE005
in order to input the matrix, the input matrix is,
Figure 834756DEST_PATH_IMAGE006
representing the disturbance caused by complex weather, assuming that the disturbance is of a time-invariant nature.
Thirdly, as shown in fig. 2, the unmanned aerial vehicle is divided into an inner ring control and an outer ring control, wherein the outer ring control quantity is
Figure 949342DEST_PATH_IMAGE084
The inner ring control quantity is
Figure 234611DEST_PATH_IMAGE008
. When the unmanned aerial vehicle is disturbed by complex weather, the control quantity of the inner ring of the control surface is firstly passed
Figure 751043DEST_PATH_IMAGE085
Changing angular velocity of unmanned aerial vehicle
Figure 591960DEST_PATH_IMAGE007
And then the outer loop control is performed. Now in the outer loop control, the angular velocity of the drone
Figure 928263DEST_PATH_IMAGE084
For control input, the input will be speed after the drone is disturbed
Figure 247249DEST_PATH_IMAGE086
Remain in the ideal state. Two sets of state space equations are obtained according to the flight dynamics equation of the unmanned aerial vehicle as follows:
Figure 618188DEST_PATH_IMAGE087
wherein the content of the first and second substances,
Figure 630006DEST_PATH_IMAGE010
,
Figure 453606DEST_PATH_IMAGE011
，
Figure 576283DEST_PATH_IMAGE012
，
Figure 303192DEST_PATH_IMAGE013
；
the flight dynamics equation of the unmanned aerial vehicle is combined to obtainf i (x), g i (x) The specific expression of (A) is as follows:
Figure 220333DEST_PATH_IMAGE014
Figure 796808DEST_PATH_IMAGE088
Figure 723175DEST_PATH_IMAGE016
Figure 803127DEST_PATH_IMAGE017
the fourth step, define the sliding mode surface as
Figure 156748DEST_PATH_IMAGE089
Wherein
Figure 954939DEST_PATH_IMAGE090
，
Figure 419419DEST_PATH_IMAGE091
. For outer ring control, the slip form face is
Figure 353877DEST_PATH_IMAGE092
，
Figure 143978DEST_PATH_IMAGE093
，
Figure 928001DEST_PATH_IMAGE094
(ii) a For inner ring control, the slip form surface is
Figure 930592DEST_PATH_IMAGE095
，
Figure 985136DEST_PATH_IMAGE096
，
Figure 946139DEST_PATH_IMAGE097
. Wherein
Figure 187764DEST_PATH_IMAGE098
Represents the function of the sliding mode surface,
Figure 259625DEST_PATH_IMAGE099
which represents an error in the form of,K i represents a constant coefficient of the output signal of the amplifier,twhich represents the time of day,
Figure 168676DEST_PATH_IMAGE100
representing the expected value.
Fifthly, designing the controller under the condition of considering unknown complex meteorological disturbance through a Lyapunov stability criterion to obtain the controller with the unknown disturbance, designing an adaptive law for the complex meteorological disturbance by adopting the Lyapunov stability criterion again, and substituting the adaptive law to obtain the final controller.
Consider the following Lyapunov candidate function:
Figure 35000DEST_PATH_IMAGE046
wherein the content of the first and second substances,W 1 is a first candidate function;
derivation of this can yield:
Figure 295080DEST_PATH_IMAGE047
to make it possible to
Figure 639474DEST_PATH_IMAGE101
For negative, the inner and outer ring controllers are designed as follows:
Figure 170075DEST_PATH_IMAGE102
wherein
Figure 207301DEST_PATH_IMAGE103
In order to determine the constant coefficient to be determined,
Figure 689098DEST_PATH_IMAGE104
for disturbing complex weather
Figure 102762DEST_PATH_IMAGE105
For time invariant perturbations, sgn is a sign function.
Setting up
Figure 986404DEST_PATH_IMAGE106
，
Figure 194532DEST_PATH_IMAGE107
Which is indicative of the error in the estimation of the disturbance,i=1,2；
consider again the following Lyapunov candidate function:
Figure 163625DEST_PATH_IMAGE108
wherein the content of the first and second substances,W 2 in order to be a second candidate function,
Figure 115400DEST_PATH_IMAGE109
is a constant coefficient to be determined;
derivation of this can yield:
Figure 853549DEST_PATH_IMAGE057
thereby to make
Figure 725253DEST_PATH_IMAGE058
Negative, the adaptation law can be found to be:
Figure 181643DEST_PATH_IMAGE110
substituting the adaptive law into the controller
Figure 937109DEST_PATH_IMAGE111
In this way, the final sliding mode controller expression can be obtained as follows:
Figure 529764DEST_PATH_IMAGE112
wherein the content of the first and second substances,
Figure 79694DEST_PATH_IMAGE113
。
the resulting sliding mode controller can thus be obtained as follows:
outer loop sliding mode controller:
Figure 23380DEST_PATH_IMAGE114
wherein the content of the first and second substances,
Figure 316958DEST_PATH_IMAGE115
；
inner ring sliding mode controller:
Figure 29699DEST_PATH_IMAGE116
wherein the content of the first and second substances,
Figure 750530DEST_PATH_IMAGE117
。
sixthly, setting an ideal speed
Figure 181511DEST_PATH_IMAGE118
When the unmanned aerial vehicle is disturbed by complex weather, the unmanned aerial vehicle passes through the self-adaptation law
Figure 514666DEST_PATH_IMAGE119
Real-time updating sliding mode controller
Figure 81914DEST_PATH_IMAGE120
The unmanned aerial vehicle can fly at a constant speed under the disturbance of complex weather.
The above description is only exemplary of the present invention and should not be taken as limiting the scope of the present invention, and any modifications, equivalents, improvements and the like that are within the spirit and principle of the present invention should be included in the scope of the present invention.

Claims (1)

1. An unmanned aerial vehicle constant-speed flight control method considering meteorological conditions is characterized by comprising the following steps:
s1, establishing a flight dynamics equation of the unmanned aerial vehicle under the axis system of the unmanned aerial vehicle based on the plane earth hypothesis;
s2, converting the flight dynamics equation into an unmanned aerial vehicle state space equation, and adding a meteorological condition disturbance term;
s3, designing a sliding mode surface by using an unmanned aerial vehicle state space equation, carrying out japunoff stability judgment on the sliding mode surface to obtain an inner-outer ring controller, designing a self-adaptation law corresponding to the meteorological condition disturbance term, and substituting the self-adaptation law into the inner-outer ring controller to obtain an inner-outer ring sliding mode controller capable of realizing parameter self-adaptation;
s4, setting a flying speed, and when the unmanned aerial vehicle is disturbed by meteorological conditions, realizing constant-speed flying of the unmanned aerial vehicle through the parameter self-adaptive inner and outer ring sliding mode controller;
in step S2, the unmanned aerial vehicle state space equation after the meteorological condition disturbance term is added is specifically:
Figure 273047DEST_PATH_IMAGE001
wherein
Figure 88556DEST_PATH_IMAGE002
In the form of a matrix of state quantities,
Figure 655410DEST_PATH_IMAGE003
in order to control the matrix of quantities,
Figure 214567DEST_PATH_IMAGE004
in order to be a matrix of the system,
Figure 802675DEST_PATH_IMAGE005
in order to input the matrix, the input matrix is,
Figure 789085DEST_PATH_IMAGE006
representing disturbances due to meteorological conditions;
in the step S3, the control amount of the outer loop controller is set to
Figure 344700DEST_PATH_IMAGE007
The control quantity of the inner ring controller is
Figure 441969DEST_PATH_IMAGE008
The inner and outer ring state space equations are specifically
Figure 150162DEST_PATH_IMAGE009
Wherein
Figure 245157DEST_PATH_IMAGE010
,
Figure 163435DEST_PATH_IMAGE011
，
Figure 690493DEST_PATH_IMAGE012
，
Figure 377827DEST_PATH_IMAGE013
；
Figure 581406DEST_PATH_IMAGE014
Figure 721400DEST_PATH_IMAGE015
Figure 629313DEST_PATH_IMAGE016
Figure 295787DEST_PATH_IMAGE017
Wherein the content of the first and second substances,
Figure 794901DEST_PATH_IMAGE018
Figure 563137DEST_PATH_IMAGE019
,
Figure 805900DEST_PATH_IMAGE020
,
Figure 405508DEST_PATH_IMAGE021
；
Figure 698693DEST_PATH_IMAGE022
respectively representing the speed of the machine body in the X, Y and Z directions;
Figure 813280DEST_PATH_IMAGE023
respectively representing a rolling angular velocity, a pitch angular velocity and a yaw angular velocity;
Figure 469520DEST_PATH_IMAGE024
respectively representing a pitch angle and a roll angle;
Figure 251531DEST_PATH_IMAGE025
respectively representing roll moment, pitch moment and yaw moment;
Figure 217082DEST_PATH_IMAGE026
respectively represents the rotational inertia of the unmanned aerial vehicle to the X axis, the Y axis and the Z axis,
Figure 818965DEST_PATH_IMAGE027
representing the products of inertia of the drone on the X and Z axes;
Figure 606792DEST_PATH_IMAGE028
respectively representing that the unmanned aerial vehicle is subjected to pneumatic resultant force along an X axis, a Y axis and a Z axis;
Figure 853097DEST_PATH_IMAGE029
respectively representing components of the engine thrust on an X axis, a Y axis and a Z axis;
Figure 864915DEST_PATH_IMAGE030
which represents the acceleration of the force of gravity,
Figure 314613DEST_PATH_IMAGE031
representing the drone quality;
Figure 968449DEST_PATH_IMAGE032
represents a dynamic pressure;
Figure 69260DEST_PATH_IMAGE033
showing the stretching length;
Figure 251979DEST_PATH_IMAGE034
representing the wing area;
Figure 31717DEST_PATH_IMAGE035
representing the flight speed of the unmanned aerial vehicle;
Figure 82718DEST_PATH_IMAGE036
respectively representing an aileron deflection angle, a rudder deflection angle and an elevator deflection angle;
Figure 162670DEST_PATH_IMAGE037
respectively representing the moment coefficients along the X, Y and Z axes of the machine body;
Figure 922815DEST_PATH_IMAGE038
respectively representing the rate of change of a roll torque coefficient relative to the deflection angle of the aileron, the rate of change of the roll torque coefficient relative to the rudder deflection angle, the rate of change of the roll torque coefficient relative to the roll angular speed and the rate of change of the roll torque coefficient relative to the yaw angular speed;
Figure 721007DEST_PATH_IMAGE039
respectively representing the rate of change of a pitch moment coefficient relative to the deflection angle of the elevator and the rate of change of the pitch moment coefficient relative to the pitch angle speed;
Figure 74234DEST_PATH_IMAGE040
respectively representing the change rate of yaw moment relative to the deflection angle of the aileron, the change rate of yaw moment relative to the deflection angle of the rudder, the change rate of yaw moment relative to the roll angular velocity and the change rate of yaw moment relative to the yaw angular velocity;
Figure 8692DEST_PATH_IMAGE041
representing a chord length;
in step S3, for the outer ring controller, the sliding surface is
Figure 2056DEST_PATH_IMAGE042
；
For an inner ring controller, the sliding mode surface is
Figure 162910DEST_PATH_IMAGE043
；
Wherein
Figure 431081DEST_PATH_IMAGE044
Represents the function of the sliding mode surface,
Figure 875837DEST_PATH_IMAGE045
which represents an error in the form of,K i represents a constant coefficient of the output signal of the amplifier,twhich represents the time of day,
Figure 836840DEST_PATH_IMAGE046
represents the expected value;
the step S3 of determining the japonov stability of the sliding-mode surface includes determining the inner-outer-ring controller
Consider the following Lyapunov candidate function:
Figure 219411DEST_PATH_IMAGE047
wherein, the first and the second end of the pipe are connected with each other,W 1 is a first candidate function;
derivation of this can yield:
Figure 291272DEST_PATH_IMAGE048
to make it possible to
Figure 669164DEST_PATH_IMAGE049
For negative, the inner and outer ring controllers are designed as follows:
Figure 161587DEST_PATH_IMAGE050
wherein
Figure 421667DEST_PATH_IMAGE051
In order to determine the constant coefficient to be determined,
Figure 172586DEST_PATH_IMAGE052
for disturbing complex meteorology
Figure 936142DEST_PATH_IMAGE053
For time invariant disturbances, sgn is a sign function;
setting up
Figure 98002DEST_PATH_IMAGE054
，
Figure 845378DEST_PATH_IMAGE055
Which is indicative of the error in the estimation of the disturbance,i=1,2；
in the step S3, the adaptive law corresponding to the meteorological condition disturbance term is designed to be
Consider the following Lyapunov candidate function:
Figure 931146DEST_PATH_IMAGE056
wherein the content of the first and second substances,W 2 in order to be a second candidate function,
Figure 18051DEST_PATH_IMAGE057
is a constant coefficient to be determined;
derivation of this can yield:
Figure 114926DEST_PATH_IMAGE058
to make it possible to
Figure 84019DEST_PATH_IMAGE059
Negative, the resulting adaptation law is:
Figure 176740DEST_PATH_IMAGE060
；
in the step S3, the inner and outer ring sliding mode controller is specifically
Outer loop sliding mode controller:
Figure 180468DEST_PATH_IMAGE061
wherein the content of the first and second substances,
Figure 684131DEST_PATH_IMAGE062
；
inner ring sliding mode controller:
Figure 140520DEST_PATH_IMAGE063
wherein the content of the first and second substances,
Figure 99249DEST_PATH_IMAGE064
。
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