CN114489105A - Novel unmanned aerial vehicle attitude system integral sliding mode control method based on disturbance observer - Google Patents

Novel unmanned aerial vehicle attitude system integral sliding mode control method based on disturbance observer Download PDF

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CN114489105A
CN114489105A CN202210089145.8A CN202210089145A CN114489105A CN 114489105 A CN114489105 A CN 114489105A CN 202210089145 A CN202210089145 A CN 202210089145A CN 114489105 A CN114489105 A CN 114489105A
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sliding mode
matrix
integral sliding
aerial vehicle
unmanned aerial
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CN114489105B (en
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蒋国平
刘景宇
周映红
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Nanjing University of Posts and Telecommunications
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Nanjing University of Posts and Telecommunications
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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
    • G05D1/08—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
    • 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
    • G05D1/106—Change initiated in response to external conditions, e.g. avoidance of elevated terrain or of no-fly zones

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Abstract

The application relates to a novel unmanned aerial vehicle attitude system integral sliding mode control method and device based on a disturbance observer, an unmanned aerial vehicle and a storage medium. The method comprises the following steps: acquiring parameter errors and external disturbances observed by an interference observer in real time; inputting the parameter error and the external disturbance into a novel integral sliding mode controller, and enabling the novel integral sliding mode controller to output a control signal to control the posture of the unmanned aerial vehicle according to the parameter error and the external disturbance; the novel integral sliding mode controller is constructed in the following mode: constructing an unmanned aerial vehicle attitude dynamic system model according to the dynamic characteristics of the unmanned aerial vehicle; determining an attitude angle error, and constructing an integral sliding mode surface; constructing an integral sliding mode approach law; according to the unmanned aerial vehicle attitude dynamics system model, the integral sliding mode surface and the integral sliding mode approach law, a novel integral sliding mode controller is constructed, so that the problem that the transient performance is weakened during initial control is solved.

Description

Novel unmanned aerial vehicle attitude system integral sliding mode control method based on disturbance observer
Technical Field
The application relates to the technical field of unmanned aerial vehicle attitude system control, in particular to a novel unmanned aerial vehicle attitude system integral sliding mode control method and device based on an interference observer, a computer storage medium and an unmanned aerial vehicle.
Background
Along with the development in unmanned aerial vehicle technical field, unmanned aerial vehicle can realize the collection of high resolution image, when compensateing satellite remote sensing and often sheltering from because of the cloud cover and can not acquireing from the image shortcoming, has solved traditional satellite remote sensing revisits cycle overlength, emergent untimely scheduling problem, consequently, unmanned aerial vehicle wide application in each field, if: plant protection, military, personal, forest fire suppression, and the like.
At present, aiming at the unmanned aerial vehicle, a controller is also diversified, the traditional integral sliding mode is one of the traditional integral sliding modes, the traditional integral sliding mode control method enables the system state to slide to the target state by applying a nonlinear signal, a curve through which the system state slides is called a sliding mode surface, but the traditional integral sliding mode control method can generate a larger transient performance problem during initial control.
Disclosure of Invention
Based on this, it is necessary to provide a novel unmanned aerial vehicle attitude system integral sliding mode control method, apparatus, computer device and storage medium based on a disturbance observer, which can alleviate the problem of transient performance reduction during initial control.
A novel unmanned aerial vehicle attitude system integral sliding mode control method based on a disturbance observer comprises the following steps:
acquiring parameter errors and external disturbances observed by an interference observer in real time;
inputting the parameter error and the external disturbance into a novel integral sliding mode controller, and enabling the novel integral sliding mode controller to output a control signal to control the posture of the unmanned aerial vehicle according to the parameter error and the external disturbance;
the novel integral sliding mode controller is constructed in the following mode:
constructing an unmanned aerial vehicle attitude dynamic system model according to the dynamic characteristics of the unmanned aerial vehicle;
determining an attitude angle error, and constructing an integral sliding mode surface;
constructing an integral sliding mode approach law;
and constructing a novel integral sliding mode controller according to the unmanned aerial vehicle attitude dynamics system model, the integral sliding mode surface and the integral sliding mode approach law.
In one embodiment, the disturbance observer is constructed in the following manner:
determining a corresponding interference item according to the unmanned aerial vehicle attitude dynamics system model;
and constructing a disturbance observer according to the disturbance term.
In one embodiment, the model of the unmanned aerial vehicle attitude dynamics system is:
Figure BDA0003488447760000021
wherein the content of the first and second substances,
Figure BDA0003488447760000022
is the acceleration of the pitch angle,
Figure BDA0003488447760000023
is the pitch angle rate of the blade,
Figure BDA0003488447760000024
is the angular acceleration of the roll, and,
Figure BDA0003488447760000025
is the angular velocity of the roll-over,
Figure BDA0003488447760000026
is the yaw angular acceleration and is,
Figure BDA0003488447760000027
is the yaw rate; j. the design is a squarexIs the rotary inertia of the x axis of the quad-rotor unmanned plane, JyMoment of inertia, J, for the y-axis of a quad-rotor unmanned aerial vehiclezThe moment of inertia of the z axis of the quad-rotor unmanned aerial vehicle;
Figure BDA0003488447760000028
air damping coefficient of y-axis, KθAir damping coefficient of x-axis, KηAir damping coefficient for the z-axis; the parameter error of the pitch angle and the total disturbance of the external disturbance are
Figure BDA0003488447760000029
The parameter error of the roll angle and the total disturbance of the external disturbance are dθ(t) the parameter error of the yaw angle and the total disturbance of the external disturbances are dη(t), l is the length of the force arm;
Figure BDA00034884477600000210
controller output as pitch angle, uθFor controller output of the roll angle, uηC is the constant force coefficient, which is the controller output for yaw angle.
In one embodiment, the integral sliding mode surface is:
Figure BDA00034884477600000211
wherein, KpIs a column entry parameter matrix, KiIs a matrix of integral term parameters, KdIs a matrix of differential term parameters, K1Is a matrix of scaling parameters that is,
Figure BDA0003488447760000031
Figure BDA0003488447760000032
kpθand kpηIn order to compare the column entry parameters,
Figure BDA0003488447760000033
kiθand kiηIn order to be the integral term parameter,
Figure BDA0003488447760000034
kdθand kdηIn order to be a parameter of the differentiation term,
Figure BDA0003488447760000035
k1θand k1ηIn order to scale the parameters of the image,
Figure BDA0003488447760000036
is a matrix of the attitude error,
Figure BDA0003488447760000037
is pitchAngle, theta is the roll angle, eta is the yaw angle,
Figure BDA0003488447760000038
is the target value of the pitch angle, θdIs a target value of the roll angle, ηdIs the target value of the yaw angle,
Figure BDA0003488447760000039
is the error in the angular velocity of the attitude,
Figure BDA00034884477600000310
is the error in the pitch angle rate of the blade,
Figure BDA00034884477600000311
is the error in the roll angular velocity,
Figure BDA00034884477600000312
is the error of the yaw rate, tau is the time variable used for integration, s is the integral sliding mode surface matrix,
Figure BDA00034884477600000313
sliding form surface being pitch angle, sθIs the slip form face of the roll angle, sηIs the slip-form surface of the yaw angle, e (τ) is the attitude error matrix at time τ, and t is time.
In one embodiment, the integral sliding mode approach law is as follows:
Figure BDA00034884477600000314
wherein the content of the first and second substances,
Figure BDA00034884477600000315
is the derivative of the integral sliding mode surface, K2Is an exponential approximation term parameter matrix, K3For the constant-velocity-approach-term parameter matrix,
Figure BDA00034884477600000316
k2θand k2ηIs exponential trendThe parameters of the near term are used as parameters,
Figure BDA00034884477600000317
Figure BDA00034884477600000318
k3θand k3ηFor the parameters of the constant-velocity approach term,
Figure BDA00034884477600000319
s is an integral sliding mode surface matrix.
In one embodiment, the novel integral sliding mode controller is:
Figure BDA0003488447760000041
wherein the content of the first and second substances,
Figure BDA0003488447760000042
in order for the controller to output a matrix,
Figure BDA0003488447760000043
controller output, u, representing pitch angleθController output, u, representing the roll angleηController output, K, representing yaw angle0In the form of a matrix of air damping coefficients,
Figure BDA0003488447760000044
air damping coefficient of y-axis, KθAir damping coefficient of x-axis, KηAir damping coefficient for the z-axis;
Figure BDA0003488447760000045
is a matrix of the attitude angular velocity,
Figure BDA0003488447760000046
is a matrix of the angular acceleration of the attitude,
Figure BDA0003488447760000047
is a matrix of the attitude angles and,
Figure BDA0003488447760000048
is an unmanned aerial vehicle moment of inertia parameter matrix, JxIs the rotary inertia of the x axis of the quad-rotor unmanned plane, JyMoment of inertia, J, for the y-axis of a quad-rotor unmanned aerial vehiclezThe moment of inertia of the z axis of the quad-rotor unmanned aerial vehicle;
Figure BDA0003488447760000049
is a matrix of total interference estimates and,
Figure BDA00034884477600000410
is a total disturbance estimate of the pitch angle,
Figure BDA00034884477600000411
is a total disturbance estimate of the roll angle,
Figure BDA00034884477600000412
is a total disturbance estimate for the yaw angle,
Figure BDA00034884477600000413
is a moment arm length matrix, l is the moment arm length, c is the constant force coefficient; kpIs a column entry parameter matrix, KiIs a matrix of integral term parameters, KdIs a matrix of differential term parameters, K1Is a matrix of scaling parameters that is,
Figure BDA00034884477600000414
is the error of attitude angular velocity, s is the integral sliding mode surface matrix, K2Is an exponential approximation term parameter matrix, K3Is a constant velocity approach term parameter matrix.
In one embodiment, the disturbance observer is:
Figure BDA0003488447760000051
Figure BDA0003488447760000052
Figure BDA0003488447760000053
wherein the content of the first and second substances,
Figure BDA0003488447760000054
is the differential of the estimate of the attitude angular velocity,
Figure BDA0003488447760000055
is an estimate of the attitude angular velocity,
Figure BDA0003488447760000056
is a matrix of attitude angular velocities, Z1Is the total interference estimate, Z2Is an estimate of the derivative of the total interference,
Figure BDA0003488447760000057
is the derivative of the estimate of the total interference,
Figure BDA0003488447760000058
is the derivative of the total interference derivative estimate, L is the moment arm length matrix, u is the controller output matrix, L0、L1、L2、L3Is a matrix of error parameters that is,
Figure BDA0003488447760000059
Figure BDA00034884477600000510
L0θ、L0η、
Figure BDA00034884477600000511
L1θ、L1η、
Figure BDA00034884477600000512
L2θ、L2η、
Figure BDA00034884477600000513
L3θand L3ηIs an error parameter; λ is an auxiliary parameter, λ>0, sat (x) is a saturation function,
Figure BDA00034884477600000514
Figure BDA00034884477600000515
wherein maxVal is a set maximum value of the saturation function, and R is a real number.
A novel unmanned aerial vehicle attitude system integral sliding mode control device based on a disturbance observer, the device comprises:
the information acquisition module is used for acquiring parameter errors and external disturbances observed by the interference observer in real time;
the control module is used for inputting the parameter error and the external disturbance into a novel integral sliding mode controller, so that the novel integral sliding mode controller outputs a control signal to control the posture of the unmanned aerial vehicle according to the parameter error and the external disturbance;
the novel integral sliding mode controller is constructed in the following mode:
constructing an unmanned aerial vehicle attitude dynamic system model according to the dynamic characteristics of the unmanned aerial vehicle;
determining an attitude angle error, and constructing an integral sliding mode surface;
constructing an integral sliding mode approach law;
and constructing a novel integral sliding mode controller according to the unmanned aerial vehicle attitude dynamics system model, the integral sliding mode surface and the integral sliding mode approach law.
A drone comprising a memory storing a computer program and a processor implementing the steps of the method when the processor executes the computer program.
A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the steps of the method.
According to the novel unmanned aerial vehicle attitude system integral sliding mode control method and device based on the disturbance observer, the unmanned aerial vehicle and the storage medium, the parameter error and the external disturbance observed by the disturbance observer are obtained in real time; inputting the parameter error and the external disturbance into a novel integral sliding mode controller, and enabling the novel integral sliding mode controller to output a control signal to control the posture of the unmanned aerial vehicle according to the parameter error and the external disturbance; the novel integral sliding mode controller is constructed in the following mode: constructing an unmanned aerial vehicle attitude dynamic system model according to the dynamic characteristics of the unmanned aerial vehicle; determining an attitude angle error, and constructing an integral sliding mode surface; constructing an integral sliding mode approach law; according to the unmanned aerial vehicle attitude dynamics system model, the integral sliding mode surface and the integral sliding mode approach law, a novel integral sliding mode controller is constructed, the novel integral sliding mode controller has stronger robustness, small errors can be amplified, and large errors are reduced, so that an error curve is more smooth, the problem that the transient performance is weakened during initial control is solved, and the problems that the unmanned aerial vehicle parameters are inaccurate and the control effect is influenced by external interference are further solved.
Drawings
Fig. 1 is a schematic flow chart of a novel unmanned aerial vehicle attitude system integral sliding mode control method based on a disturbance observer in one embodiment;
FIG. 2 is a graph of a target pitch angle and an actual pitch angle in software simulation;
FIG. 3 is a graph of actual disturbance values and observed disturbance values of pitch angles in software simulation;
FIG. 4 is a graph of a target roll angle and an actual roll angle in a software simulation;
FIG. 5 is a graph of an actual disturbance value of a roll angle and an observed disturbance value of the roll angle in software simulation;
FIG. 6 is a graph of target yaw angle and actual yaw angle in a software simulation;
FIG. 7 is a graph of actual yaw angle disturbance values and yaw angle disturbance observations in a software simulation.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application.
In one embodiment, as shown in fig. 1, a novel unmanned aerial vehicle attitude system integral sliding mode control method based on a disturbance observer is provided, which is described by taking the method as an example applied to an unmanned aerial vehicle, and includes the following steps:
step S220, acquiring the parameter error and the external disturbance observed by the disturbance observer in real time.
Wherein, the disturbance observer is used for observing unmanned aerial vehicle's parameter error and external disturbance, lets unmanned aerial vehicle control effect better.
And S240, inputting the parameter error and the external disturbance into a novel integral sliding mode controller, and outputting a control signal to control the posture of the unmanned aerial vehicle by the novel integral sliding mode controller according to the parameter error and the external disturbance.
The novel integral sliding mode controller is constructed in the following mode: constructing an unmanned aerial vehicle attitude dynamic system model according to the dynamic characteristics of the unmanned aerial vehicle; determining an attitude angle error, and constructing an integral sliding mode surface; constructing an integral sliding mode approach law; and constructing a novel integral sliding mode controller according to the unmanned aerial vehicle attitude dynamics system model, the integral sliding mode surface and the integral sliding mode approach law.
According to the novel unmanned aerial vehicle attitude system integral sliding mode control method based on the disturbance observer, the parameter error and the external disturbance observed by the disturbance observer are obtained in real time; inputting the parameter error and the external disturbance into a novel integral sliding mode controller, and enabling the novel integral sliding mode controller to output a control signal to control the posture of the unmanned aerial vehicle according to the parameter error and the external disturbance; the novel integral sliding mode controller is constructed in the following mode: constructing an unmanned aerial vehicle attitude dynamic system model according to the dynamic characteristics of the unmanned aerial vehicle; determining an attitude angle error, and constructing an integral sliding mode surface; constructing an integral sliding mode approach law; according to the unmanned aerial vehicle attitude dynamics system model, the integral sliding mode surface and the integral sliding mode approach law, a novel integral sliding mode controller is constructed, the novel integral sliding mode controller has stronger robustness, small errors can be amplified, and large errors are reduced, so that an error curve is more smooth, the problem that the transient performance is weakened during initial control is solved, and the problems that the unmanned aerial vehicle parameters are inaccurate and the control effect is influenced by external interference are further solved.
In one embodiment, the disturbance observer is constructed in a manner that: determining a corresponding interference item according to the unmanned aerial vehicle attitude dynamic system model; and constructing a disturbance observer according to the disturbance term.
In one embodiment, the model of the unmanned aerial vehicle attitude dynamics system is:
Figure BDA0003488447760000081
wherein the content of the first and second substances,
Figure BDA0003488447760000082
is the acceleration of the pitch angle of the vehicle,
Figure BDA0003488447760000083
is the pitch angle rate of the blade,
Figure BDA0003488447760000084
is the angular acceleration of the roll, and,
Figure BDA0003488447760000085
is the angular velocity of the roll-over,
Figure BDA0003488447760000086
is the yaw angular acceleration and is,
Figure BDA0003488447760000087
is the yaw rate; j. the design is a squarexIs the rotary inertia of the x axis of the quad-rotor unmanned plane, JyMoment of inertia, J, for the y-axis of a quad-rotor unmanned aerial vehiclezThe moment of inertia of the z axis of the quad-rotor unmanned aerial vehicle;
Figure BDA0003488447760000088
air damping coefficient of y-axis, KθAir damping coefficient of x-axis, KηAir damping coefficient for the z-axis; the parameter error of the pitch angle and the total disturbance of the external disturbance are
Figure BDA0003488447760000089
The parameter error of the roll angle and the total disturbance of the external disturbance are dθ(t) the parameter error of the yaw angle and the total disturbance of the external disturbances are dη(t), l is the length of the force arm;
Figure BDA00034884477600000810
controller output as pitch angle, uθFor controller output of the roll angle, uηC is the constant force coefficient, which is the controller output for yaw angle.
In one embodiment, the integral slip form surface is:
Figure BDA00034884477600000811
wherein, KpIs a column entry parameter matrix, KiIs a matrix of integral term parameters, KdIs a matrix of differential term parameters, K1Is a matrix of scaling parameters that is,
Figure BDA0003488447760000091
Figure BDA0003488447760000092
kpθand kpηIn order to compare the column entry parameters,
Figure BDA0003488447760000093
kiθand kiηIn order to be the integral term parameter,
Figure BDA0003488447760000094
kdθand kdηIn order to be a parameter of the differentiation term,
Figure BDA0003488447760000095
k1θand k1ηIn order to scale the parameters of the image,
Figure BDA0003488447760000096
is a matrix of the attitude errors,
Figure BDA0003488447760000097
is the pitch angle, theta is the roll angle, eta is the yaw angle,
Figure BDA0003488447760000098
is the target value of the pitch angle, θdIs a target value of the roll angle, ηdIs the target value of the yaw angle,
Figure BDA0003488447760000099
is the error in the angular velocity of the attitude,
Figure BDA00034884477600000910
is the error in the pitch angle rate of the blade,
Figure BDA00034884477600000911
is the error in the roll angular velocity,
Figure BDA00034884477600000912
is the error of the yaw rate, tau is the time variable used for integration, s is the integral sliding mode surface matrix,
Figure BDA00034884477600000913
sliding form surface being pitch angle, sθIs the slip form face of the roll angle, sηIs the slip-form surface of the yaw angle, e (τ) is the attitude error matrix at time τ, and t is time.
The integral term tanh (e (tau)) in the integral sliding mode surface can enlarge small errors and reduce large errors, so that an error curve is smoother.
In one embodiment, the integral sliding mode approach law is:
Figure BDA00034884477600000914
wherein the content of the first and second substances,
Figure BDA00034884477600000915
is the derivative of the integral sliding mode surface, K2Is an exponential approximation term parameter matrix, K3For the constant-velocity-approach-term parameter matrix,
Figure BDA0003488447760000101
k2θand k2ηIn order to be an exponential-approaching term parameter,
Figure BDA0003488447760000102
Figure BDA0003488447760000103
k3θand k3ηFor the parameters of the constant-velocity approach term,
Figure BDA0003488447760000104
s is an integral sliding mode surface matrix.
In one embodiment, the novel integral sliding mode controller is:
Figure BDA0003488447760000105
wherein the content of the first and second substances,
Figure BDA0003488447760000106
in order for the controller to output a matrix,
Figure BDA0003488447760000107
controller output, u, representing pitch angleθController output, u, representing the roll angleηController output, K, representing yaw angle0Is the damping coefficient of airThe matrix is a matrix of a plurality of matrices,
Figure BDA0003488447760000108
air damping coefficient of y-axis, KθAir damping coefficient of x-axis, KηAir damping coefficient for the z-axis;
Figure BDA0003488447760000109
is a matrix of the attitude angular velocity,
Figure BDA00034884477600001010
is a matrix of the angular acceleration of the attitude,
Figure BDA00034884477600001011
is a matrix of the attitude angles and,
Figure BDA00034884477600001012
is an unmanned aerial vehicle moment of inertia parameter matrix, JxIs the rotary inertia of the x axis of the quad-rotor unmanned plane, JyMoment of inertia, J, for the y-axis of a quad-rotor unmanned aerial vehiclezThe moment of inertia of the z axis of the quad-rotor unmanned aerial vehicle;
Figure BDA00034884477600001013
is a matrix of total interference estimates and,
Figure BDA00034884477600001014
is a total disturbance estimate of the pitch angle,
Figure BDA00034884477600001015
is a total disturbance estimate of the roll angle,
Figure BDA00034884477600001016
is a total disturbance estimate for the yaw angle,
Figure BDA00034884477600001017
is a moment arm length matrix, l is the moment arm length, c is the constant force coefficient; kpIs a column entry parameter matrix, KiIs a matrix of integral term parameters, KdIs differentialItem parameter matrix, K1Is a matrix of scaling parameters that is,
Figure BDA0003488447760000111
is the error of attitude angular velocity, s is the integral sliding mode surface matrix, K2Is an exponential approximation term parameter matrix, K3Is a constant velocity approach term parameter matrix.
In one embodiment, the disturbance observer is:
Figure BDA0003488447760000112
Figure BDA0003488447760000113
Figure BDA0003488447760000114
wherein the content of the first and second substances,
Figure BDA0003488447760000115
is the differential of the estimate of the attitude angular velocity,
Figure BDA0003488447760000116
is an estimate of the attitude angular velocity,
Figure BDA0003488447760000117
is a matrix of attitude angular velocities, Z1Is the total interference estimate, Z2Is an estimate of the derivative of the total interference,
Figure BDA0003488447760000118
is the derivative of the estimate of the total interference,
Figure BDA0003488447760000119
is the derivative of the total interference derivative estimate, L is the moment arm length matrix, u is the controller output matrix, L0、L1、L2、L3Is a matrix of error parameters that is,
Figure BDA00034884477600001110
Figure BDA00034884477600001111
L0θ、L0η、
Figure BDA00034884477600001112
L1θ、L1η、
Figure BDA00034884477600001113
L2θ、L2η、
Figure BDA00034884477600001114
L3θand L3ηIs an error parameter; λ is an auxiliary parameter, λ>0, sat (x) is a saturation function,
Figure BDA00034884477600001115
Figure BDA00034884477600001116
wherein maxVal is a set maximum value of the saturation function, and R is a real number.
The novel integral sliding mode controller in the novel unmanned aerial vehicle attitude system integral sliding mode control method based on the disturbance observer has stronger robustness, small errors can be amplified in the controller, and large errors can be reduced, so that an error curve is smoother; according to the novel unmanned aerial vehicle attitude system integral sliding mode control method based on the disturbance observer, the disturbance observer can observe the parameter error of the unmanned aerial vehicle and the specific value of external disturbance, and the parameter error and the specific value are integrated into a control algorithm to enable the control effect to be better. Therefore, the unmanned aerial vehicle attitude control system controls the attitude of the unmanned aerial vehicle by combining the novel integral sliding mode controller and the interference observer, so that the error between the actual attitude and the target attitude can quickly approach to zero, the unmanned aerial vehicle attitude system can quickly reach the target angle, the robustness is good, and the attitude angle of the unmanned aerial vehicle can reach the target attitude set arbitrarily.
In order to verify that the novel unmanned aerial vehicle attitude system integral sliding mode control method based on the disturbance observer has convergence, the following proving process is carried out:
for a disturbance observer:
assume that 1: in the model of the unmanned aerial vehicle attitude dynamics system,
Figure BDA0003488447760000121
the i-th derivative of D (t) is D(i)(t) and is bounded.
Assume 2: has a constant alphai(i ═ 1, 2, 3, 4), β, a positive continuously differentiable function V, and a positive continuously differentiable function W, where R of the positive continuously differentiable function V and the positive continuously differentiable function Wn+1Approaching to real number R, Rn+1Is n +1 dimensional euclidean space, n is 0, 1, 2, 3 … ….
So that the following equation holds:
(1)α1||k||2≤V(k)≤α2||k||2，α3||k||2≤W(f)≤α4||k||2，
(2)
Figure BDA0003488447760000122
(3)
Figure BDA0003488447760000123
where k is a vector, k ═ k (k)1，k2，k3……kn+1)，k1Is a first function, k2Is a second function, k3Is a third function, fiIs the ith function, fn+1Is the (n + 1) th function, | | | | |, represents Rn+1Euclidean norm of.
The disturbance observer is converted into the following formula:
Figure BDA0003488447760000131
Figure BDA0003488447760000132
Figure BDA0003488447760000133
where λ is small, nearly zero, and for f1，f2And f3The method comprises the following steps of (1) preparing,
Figure BDA0003488447760000134
Figure BDA0003488447760000135
Figure BDA0003488447760000136
setting up
Figure BDA0003488447760000137
Then the system of error equations is:
Figure BDA0003488447760000138
Figure BDA0003488447760000139
Figure BDA00034884477600001310
wherein e isiIs error of stateDifference, xi(t) is the value of the true state,
Figure BDA00034884477600001311
is an estimated state value, yiIs the (i) th error equation,
Figure BDA00034884477600001312
is the derivative of the 1 st error equation,
Figure BDA00034884477600001313
is the derivative of the total interference matrix.
According to hypothesis 1, when t>At the time of 0, the number of the first,
Figure BDA00034884477600001314
and M is>0, M is a normal number.
Then, based on hypothesis 2, one V (y (t)),
Figure BDA00034884477600001315
Figure BDA0003488447760000141
then there is a list of the number of,
Figure BDA0003488447760000142
according to the definition of the error, the error is obtained,
Figure BDA0003488447760000143
thus, the disturbance observer will converge steadily when assumptions 1 and 2 are both satisfied and the parameters are properly selected.
For a sliding mode surface s, a Lyapunov function V is set1Comprises the following steps:
Figure BDA0003488447760000144
the derivation is carried out on the formula (13), and the derivative of the integral sliding mode surface and a novel integral sliding mode controller are brought in, so that the following steps are carried out:
Figure BDA0003488447760000145
because the disturbance observer can be stable, there are:
Figure BDA0003488447760000146
then the formula (14) has the following formula,
Figure BDA0003488447760000147
thus, according to Lyapunov's second theorem, the integral sliding-mode surface may converge to zero.
According to the Barbalt theorem, when t → 0,
Figure BDA0003488447760000148
according to the integral sliding mode surface, there is,
Figure BDA0003488447760000149
obtained according to the formula (17),
Figure BDA0003488447760000151
wherein, the first and the second end of the pipe are connected with each other,
Figure BDA0003488447760000152
is the attitude angular acceleration error.
For the error e, a corresponding Lyapunov function V is set2Comprises the following steps:
Figure BDA0003488447760000153
the derivation for equation (19) is:
Figure BDA0003488447760000154
when the formula (18) is brought into the formula (20),
Figure BDA0003488447760000155
thus, e can converge to zero under the control of the controller.
In summary, the novel unmanned aerial vehicle attitude system integral sliding mode control method based on the disturbance observer can stabilize the unmanned aerial vehicle attitude system.
In order to further verify the effectiveness and feasibility of the novel unmanned aerial vehicle attitude system integral sliding mode control method based on the disturbance observer, Matlab program simulation is carried out, and simulation data are as follows:
program simulation in Matlab, Jx＝0.00531，Jy＝0.00577，Jz＝0.00808，c＝1，l＝0.165，
Figure BDA0003488447760000156
Figure BDA0003488447760000157
Figure BDA0003488447760000161
λ＝0.1，
Figure BDA0003488447760000162
Theoretical analysis was verified by Matlab program simulation, and the simulation results are shown in fig. 2-7.
As can be observed from fig. 2, 4 and 6, the target value of the pitch angle is-1, the target value of the roll angle is 0, and the target value of the yaw angle is 1, under the action of the novel unmanned aerial vehicle attitude system integral sliding mode control method based on the disturbance observer, the target angle is converged from the initial angle quickly, and the error between the target angle and the actual angle is small.
As can be observed from fig. 3, 5 and 7, the errors between the estimated disturbance values of the pitch angle, the roll angle and the yaw angle obtained by the disturbance observer and the actual disturbance values are small, and the actual disturbance values can be tracked quickly at a high frequency.
In conclusion, the effectiveness and feasibility of the novel unmanned aerial vehicle attitude system integral sliding mode control method based on the disturbance observer are verified through simulation experiments.
It should be understood that, although the steps in the flowchart of fig. 1 are shown in order as indicated by the arrows, the steps are not necessarily performed in order as indicated by the arrows. The steps are not performed in the exact order shown and described, and may be performed in other orders, unless explicitly stated otherwise. Moreover, at least a portion of the steps in fig. 1 may include multiple sub-steps or multiple stages that are not necessarily performed at the same time, but may be performed at different times, and the order of performance of the sub-steps or stages is not necessarily sequential, but may be performed in turn or alternately with other steps or at least a portion of the sub-steps or stages of other steps.
In one embodiment, a novel unmanned aerial vehicle attitude system integral sliding mode control device based on a disturbance observer is provided, and includes:
the information acquisition module is used for acquiring parameter errors and external disturbances observed by the interference observer in real time;
the control module is used for inputting the parameter error and the external disturbance into a novel integral sliding mode controller, so that the novel integral sliding mode controller outputs a control signal to control the posture of the unmanned aerial vehicle according to the parameter error and the external disturbance;
the novel integral sliding mode controller is constructed in the following mode:
constructing an unmanned aerial vehicle attitude dynamic system model according to the dynamic characteristics of the unmanned aerial vehicle;
determining an attitude angle error, and constructing an integral sliding mode surface;
constructing an integral sliding mode approach law;
and constructing a novel integral sliding mode controller according to the unmanned aerial vehicle attitude dynamic system model, the integral sliding mode surface and the integral sliding mode approach law.
For specific limitation of the novel unmanned aerial vehicle attitude system integral sliding mode control device based on the disturbance observer, reference may be made to the above limitation on the novel unmanned aerial vehicle attitude system integral sliding mode control method based on the disturbance observer, and details are not repeated here. All modules in the novel unmanned aerial vehicle attitude system integral sliding mode control device based on the disturbance observer can be completely or partially realized through software, hardware and a combination of the software and the hardware. The modules can be embedded in a hardware form or independent of a processor in the computer device, and can also be stored in a memory in the computer device in a software form, so that the processor can call and execute operations corresponding to the modules.
In one embodiment, an unmanned aerial vehicle is provided, and includes a memory and a processor, where the memory stores a computer program, and the processor implements the steps of the above-described novel unmanned aerial vehicle attitude system integral sliding mode control method based on the disturbance observer when executing the computer program.
In one embodiment, a computer readable storage medium is provided, on which a computer program is stored, and the computer program, when executed by a processor, implements the steps of the above-mentioned novel unmanned aerial vehicle attitude system integral sliding mode control method based on the disturbance observer.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by hardware related to instructions of a computer program, which can be stored in a non-volatile computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in the embodiments provided herein may include non-volatile and/or volatile memory, among others. Non-volatile memory can include read-only memory (ROM), Programmable ROM (PROM), Electrically Programmable ROM (EPROM), Electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), Dynamic RAM (DRAM), Synchronous DRAM (SDRAM), Double Data Rate SDRAM (DDRSDRAM), Enhanced SDRAM (ESDRAM), Synchronous Link DRAM (SLDRAM), Rambus Direct RAM (RDRAM), direct bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).
The technical features of the above embodiments can be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the above embodiments are not described, but should be considered as the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
The above-mentioned embodiments only express several embodiments of the present application, and the description thereof is more specific and detailed, but not construed as limiting the scope of the invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, which falls within the scope of protection of the present application. Therefore, the protection scope of the present patent shall be subject to the appended claims.

Claims (10)

1. A novel unmanned aerial vehicle attitude system integral sliding mode control method based on a disturbance observer is characterized by comprising the following steps:
acquiring parameter errors and external disturbances observed by an interference observer in real time;
inputting the parameter error and the external disturbance into a novel integral sliding mode controller, and enabling the novel integral sliding mode controller to output a control signal to control the posture of the unmanned aerial vehicle according to the parameter error and the external disturbance;
the novel integral sliding mode controller is constructed in the following mode:
constructing an unmanned aerial vehicle attitude dynamic system model according to the dynamic characteristics of the unmanned aerial vehicle;
determining an attitude angle error, and constructing an integral sliding mode surface;
constructing an integral sliding mode approach law;
and constructing a novel integral sliding mode controller according to the unmanned aerial vehicle attitude dynamics system model, the integral sliding mode surface and the integral sliding mode approach law.
2. The method of claim 1, wherein the disturbance observer is constructed by:
determining a corresponding interference item according to the unmanned aerial vehicle attitude dynamics system model;
and constructing a disturbance observer according to the disturbance term.
3. The method of claim 1, wherein the drone attitude dynamics system model is:
Figure FDA0003488447750000011
wherein the content of the first and second substances,
Figure FDA0003488447750000012
is the acceleration of the pitch angle,
Figure FDA0003488447750000013
is the pitch angle rate of the blade,
Figure FDA0003488447750000014
is the angular acceleration of the roll, and,
Figure FDA0003488447750000015
is the angular velocity of the roll-over,
Figure FDA0003488447750000016
is the yaw angular acceleration and is,
Figure FDA0003488447750000017
is the yaw rate; j. the design is a squarexIs the rotary inertia of the x axis of the quad-rotor unmanned plane, JyMoment of inertia, J, for the y-axis of a quad-rotor unmanned aerial vehiclezThe moment of inertia of the z axis of the quad-rotor unmanned aerial vehicle;
Figure FDA0003488447750000018
air damping coefficient of y-axis, KθAir damping coefficient, K, for the x-axisηAir damping coefficient for the z-axis; the parameter error of the pitch angle and the total disturbance of the external disturbance are
Figure FDA00034884477500000218
The parameter error of the roll angle and the total disturbance of the external disturbance are dθ(t) the parameter error of the yaw angle and the total disturbance of the external disturbances are dη(t), l is the length of the force arm;
Figure FDA00034884477500000219
controller output as pitch angle, uθFor controller output of the roll angle, uηC is the constant force coefficient, which is the controller output for yaw angle.
4. The method of claim 1, wherein the integrating slip-form surfaces are:
Figure FDA0003488447750000021
wherein, KpIs a column entry parameter matrix, KiIs a matrix of integral term parameters, KdIs a matrix of differential term parameters, K1Is a matrix of scaling parameters that is,
Figure FDA0003488447750000022
Figure FDA0003488447750000023
Figure FDA0003488447750000024
kpθand kpηIn order to compare the column entry parameters,
Figure FDA0003488447750000025
kiθand kiηIn order to be the integral term parameter,
Figure FDA0003488447750000026
kdθand kdηIn order to be a parameter of the differentiation term,
Figure FDA0003488447750000027
k1θand k1ηIn order to scale the parameters of the image,
Figure FDA0003488447750000028
is a matrix of the attitude error,
Figure FDA0003488447750000029
is the pitch angle, theta is the roll angle, eta is the yaw angle,
Figure FDA00034884477500000210
is the target value of the pitch angle, θdIs a target value of the roll angle, ηdIs the target value of the yaw angle,
Figure FDA00034884477500000211
is the error in the angular velocity of the attitude,
Figure FDA00034884477500000212
is the error in the pitch angle rate of the blade,
Figure FDA00034884477500000213
is the error in the roll angular velocity,
Figure FDA00034884477500000214
is the error of the yaw rate, tau is the time variable used for integration, s is the integral sliding mode surface matrix,
Figure FDA00034884477500000215
Figure FDA00034884477500000216
sliding form surface being pitch angle, sθIs the slip form face of the roll angle, sηIs the slip-form surface of the yaw angle, e (τ) is the attitude error matrix at time τ, and t is time.
5. The method of claim 1, wherein the integral sliding-mode approach law is:
Figure FDA00034884477500000217
wherein the content of the first and second substances,
Figure FDA0003488447750000031
is the derivative of the integral sliding mode surface, K2Is an exponential approximation term parameter matrix, K3For the constant-velocity-approach-term parameter matrix,
Figure FDA0003488447750000032
Figure FDA0003488447750000033
k2θand k2ηIn order to be an exponential-approaching term parameter,
Figure FDA0003488447750000034
Figure FDA0003488447750000035
k3θand k3ηFor the parameters of the constant-velocity approach term,
Figure FDA0003488447750000036
s is an integral sliding mode surface matrix.
6. The method of claim 1, wherein the novel integral sliding-mode controller is:
Figure FDA0003488447750000037
wherein the content of the first and second substances,
Figure FDA0003488447750000038
in order for the controller to output a matrix,
Figure FDA0003488447750000039
controller output, u, representing pitch angleθController output, u, representing the roll angleηController output, K, representing yaw angle0In the form of a matrix of air damping coefficients,
Figure FDA00034884477500000310
Figure FDA00034884477500000311
air damping coefficient of y-axis, KθAir damping coefficient of x-axis, KηAir damping coefficient for the z-axis;
Figure FDA00034884477500000312
is a matrix of the attitude angular velocity,
Figure FDA00034884477500000313
is a matrix of the angular acceleration of the attitude,
Figure FDA00034884477500000314
is a matrix of the attitude angles and,
Figure FDA00034884477500000315
is an unmanned aerial vehicle moment of inertia parameter matrix, JxIs the rotary inertia of the x axis of the quad-rotor unmanned plane, JyMoment of inertia, J, for the y-axis of a quad-rotor unmanned aerial vehiclezThe moment of inertia of the z axis of the quad-rotor unmanned aerial vehicle;
Figure FDA00034884477500000316
is a matrix of total interference estimates and,
Figure FDA00034884477500000317
is a total disturbance estimate of the pitch angle,
Figure FDA00034884477500000318
is a total disturbance estimate of the roll angle,
Figure FDA0003488447750000041
is a total disturbance estimate for the yaw angle,
Figure FDA0003488447750000042
is a moment arm length matrix, l is the moment arm length, c is the constant force coefficient; kpIs a column entry parameter matrix, KiIs a matrix of integral term parameters, KdIs a matrix of differential term parameters, K1Is a matrix of scaling parameters that is,
Figure FDA0003488447750000043
is the error of attitude angular velocity, s is the integral sliding mode surface matrix, K2Is an exponential approximation term parameter matrix, K3Is a constant velocity approach term parameter matrix.
7. The method of claim 1, wherein the disturbance observer is:
Figure FDA0003488447750000044
Figure FDA0003488447750000045
Figure FDA0003488447750000046
wherein the content of the first and second substances,
Figure FDA0003488447750000047
is the differential of the estimate of the attitude angular velocity,
Figure FDA0003488447750000048
is an estimate of the attitude angular velocity,
Figure FDA0003488447750000049
is a matrix of attitude angular velocities, Z1Is the total interference estimate, Z2Is an estimate of the derivative of the total interference,
Figure FDA00034884477500000410
is the derivative of the estimate of the total interference,
Figure FDA00034884477500000411
is the derivative of the total interference derivative estimate, L is the moment arm length matrix, u is the controller output matrix, L0、L1、L2、L3Is a matrix of error parameters that is,
Figure FDA00034884477500000412
Figure FDA00034884477500000413
L0θ、L0η、
Figure FDA00034884477500000414
L1θ、L1η、
Figure FDA00034884477500000415
L2θ、L2η、
Figure FDA00034884477500000416
L3θand L3ηIs an error parameter; λ is an auxiliary parameter, λ>0, sat (x) is a saturation function,
Figure FDA00034884477500000417
Figure FDA00034884477500000418
wherein maxVal is a set maximum value of the saturation function, and R is a real number.
8. The utility model provides a novel unmanned aerial vehicle attitude system integral sliding mode controlling means based on disturbance observer which characterized in that, the device includes:
the information acquisition module is used for acquiring parameter errors and external disturbances observed by the interference observer in real time;
the control module is used for inputting the parameter error and the external disturbance into a novel integral sliding mode controller, so that the novel integral sliding mode controller outputs a control signal to control the posture of the unmanned aerial vehicle according to the parameter error and the external disturbance;
the novel integral sliding mode controller is constructed in the following mode:
constructing an unmanned aerial vehicle attitude dynamic system model according to the dynamic characteristics of the unmanned aerial vehicle;
determining an attitude angle error, and constructing an integral sliding mode surface;
constructing an integral sliding mode approach law;
and constructing a novel integral sliding mode controller according to the unmanned aerial vehicle attitude dynamics system model, the integral sliding mode surface and the integral sliding mode approach law.
9. A drone comprising a memory and a processor, the memory storing a computer program, characterized in that the processor, when executing the computer program, implements the steps of the method of any one of claims 1 to 7.
10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method of any one of claims 1 to 7.
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