CN113138601B - Unmanned aerial vehicle attitude control method applied to anti-low-slow small target - Google Patents

Unmanned aerial vehicle attitude control method applied to anti-low-slow small target Download PDF

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CN113138601B
CN113138601B CN202011554891.7A CN202011554891A CN113138601B CN 113138601 B CN113138601 B CN 113138601B CN 202011554891 A CN202011554891 A CN 202011554891A CN 113138601 B CN113138601 B CN 113138601B
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林德福
郭凯阳
宋韬
何绍溟
张福彪
谷雪晨
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Beijing Institute of Technology BIT
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    • G05D1/0808—Control of attitude, i.e. control of roll, pitch, or yaw specially adapted for aircraft
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    • 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
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Abstract

The invention discloses an unmanned aerial vehicle attitude control method applied to a low-slow small target, which combines disturbance estimation based on an extended state observer and a sliding mode control algorithm based on a nonsingular terminal to realize attitude control of an unmanned aerial vehicle in a point-to-point accurate counter-control low-slow small target process. The unmanned aerial vehicle attitude control method applied to the anti-low-speed small target improves the robustness of a control system and ensures the rapidity of unmanned aerial vehicle attitude control.

Description

Unmanned aerial vehicle attitude control method applied to anti-low-slow small target
Technical Field
The invention relates to an unmanned aerial vehicle control method, in particular to an unmanned aerial vehicle attitude control method applied to a reverse-low-slow small target, and belongs to the field of unmanned aerial vehicle control.
Background
Because the unmanned vehicles have the advantages of small size, low cost, light weight, easiness in operation, strong flexibility and the like, the low-speed small unmanned vehicle clusters are formed into new force for military reconnaissance and batting, and the threat to low-altitude safety is increased along with the development of the low-speed small unmanned vehicle clusters.
When performing the anti-unmanned aerial vehicle task, countries in the world mostly treat the low-altitude invading unmanned aerial vehicle as a special flying target, and utilize the traditional air defense weapons to realize one-to-one accurate butt joint striking, including the air-raid missile, the integrated "unmanned aerial vehicle of scouting and hitting", etc., wherein, because of the cost advantage, adopting the unmanned aerial vehicle to strike the low and slow small targets accurately is the preferred mode.
And the adoption of the point-to-point precise control technology of the unmanned aerial vehicle depends on the performance of the unmanned aerial vehicle control algorithm.
Traditional unmanned aerial vehicle flight control algorithm is when facing low slow little target invasion, especially cluster formation, and the effect is not good: because the low-slow small target detection difficulty and the identification difficulty are higher, and the maneuverability and the flexibility of the small target detection algorithm are generally higher than those of a counter unmanned aerial vehicle with larger size and weight, the system is required to catch the opportunity to quickly complete tasks after the target is detected, and the response time of the fighter and the counter unmanned aerial vehicle is extremely short, so that a control algorithm with better rapidity is needed.
In addition, the existing mainstream anti-low-speed small target anti-robot control algorithm can only play a role in certain specific environments, and after the working environment is changed into complicated regions such as rainforests, urban streets and the like, the anti-robot control system is unstable due to factors such as external air medium interference, large maneuvering of capturing a terminal target, completion of self-model parameter perturbation of target capture and the like, and the robustness and the quality are poor.
The conventional anti-control unmanned aerial vehicle mostly adopts a PID algorithm to realize stable and accurate control of the attitude and the position, the deviation of attitude angular motion information (angle and angular velocity) or flight position motion information (position and velocity) is subjected to proportional-integral-derivative regulation, the steady state and the dynamic characteristics of a control system are improved, and then the control system achieves good control effects, such as quick response, no overshoot, disturbance resistance and the like.
In addition, due to the limitation of the PID algorithm, the single unchanged PID control algorithm does not have strong robustness, so that the overall performance of the system is inevitably reduced in the process of balancing rapidity and robustness, and the requirement of the engineering practice on the counter-control unmanned aerial vehicle applied to the low-speed small target is difficult to meet.
Due to the reasons, the inventor of the invention carries out keen research on the counter unmanned aerial vehicle for resisting the low and slow small targets, so as to solve the problems of extremely short limiting task time, large pneumatic interference under a complex environment, flexible terminal target maneuvering and obvious attitude control of model parameter perturbation caused by carrying the counter unmanned aerial vehicle after catching when the counter unmanned aerial vehicle catches the low and slow small targets, thereby ensuring that the counter unmanned aerial vehicle gives consideration to rapidity and robustness of an attitude response process and better completing point-to-point accurate rapid striking on the low and slow small targets.
Disclosure of Invention
In order to overcome the problems, the inventor of the invention carries out intensive research and designs an unmanned aerial vehicle attitude control method applied to the anti-low and slow small targets, and the attitude control of the unmanned aerial vehicle in the process of accurately countering the low and slow small targets in a point-to-point mode is realized by combining disturbance estimation based on an extended state observer and a sliding mode control algorithm based on a nonsingular terminal.
Further, the method comprises:
s1, establishing a dynamic model of the unmanned aerial vehicle;
s2, estimating the disturbance based on the extended state observer;
and S3, controlling the attitude of the unmanned aerial vehicle based on the nonsingular terminal sliding mode control algorithm.
In step S1, the quad-rotor drone is used to accurately react to low-slow small targets in a point-to-point manner, and a dynamical model of the quad-rotor drone is modeled.
Further, in step S1, linearizing the hovering mode of the drone to obtain a rotating dynamic model:
Figure BDA0002858335630000031
Figure BDA0002858335630000032
wherein M iscForce effects corresponding to the pulling force and the torque reaction generated by the rotor wing are represented, and D represents the pneumatic damping moment; i ═ diag (I)xx,Iyy,Izz) Is the three-axis moment of inertia of a quad-rotor unmanned plane, Mc＝[L,M,N]TL, M and N are control moments in the three-axis direction of the quad-rotor unmanned aerial vehicle respectively;
attitude angle theta of quad-rotor unmanned aerial vehicle under ground coordinate system is [ phi, theta, psi ═ phi]TThe three-axis attitude change angular speed omega under the machine system is [ p, q, r ═ p]TThe relationship therebetween satisfies the following formula:
Figure BDA0002858335630000033
Figure BDA0002858335630000034
according to the invention, the dynamical model of the drone may be represented as:
Figure BDA0002858335630000035
wherein x is1Representing the attitude angle and attitude angular velocity of the drone, a ═ H1 -1H2，B＝H1 -1ΛT，W＝H1 -1ΛTD, W represents the total disturbance of the system, H1＝ΛTIΛ，
Figure BDA0002858335630000041
In step S2, the extended state observer is designed in the form of:
Figure BDA0002858335630000042
Figure BDA0002858335630000043
wherein z is1And z2Respectively being attitude control variable x1Observed value and expansion state quantity x of2The observed value of (a); e.g. of the type1＝x1-z1And e2＝x2-z2Respectively are the observation error of the attitude angle and the angular velocity and the observation error of the total disturbance;
k1,k2,k3,k4are the gains of the correction terms, and alpha is a positive constant coefficient greater than 2.
In step S3, a nonsingular terminal sliding mode control surface shown in equation eight is designed, and the posture control is divided into two parts, namely an equivalent motion section and an approach motion section:
Figure BDA0002858335630000044
wherein, thetae＝Θ-ΘdRepresenting the deviation, λ, between the actual attitude angle and the desired attitude angle1,λ2,ξ1,ξ2All are constant coefficients larger than 0 and satisfy the mathematical relation 1 < xi1< 2 and xi1＜ξ2。
Wherein the control quantity u of the equivalent motion segment0：
Figure BDA0002858335630000045
Further, the sliding mode control amount u approaching the moving section1Can be represented by the following formula:
Figure BDA0002858335630000046
wherein h is1,h2Are parameters and are positive numbers, 0 < xi3＜1。
Further, the control compensation is carried out on the total disturbance W of the system in the sliding mode control, and the total disturbance compensation control quantity u2：
u2＝-B-1z2Twelve formulas
According to the ninth formula, the tenth formula and the eleventh formula, the nonsingular terminal sliding mode control quantity u applied to the posture control of the counter unmanned aerial vehicle can be obtained:
u＝Mc＝u0+u1+u2the formula thirteen.
The invention has the advantages that:
(1) according to the unmanned aerial vehicle attitude control method applied to the anti-low-slow small target, the total disturbance of the control system of the anti-low-slow unmanned aerial vehicle is estimated based on the extended state observer, and the disturbance caused by the disturbance of model parameters and the like caused by large pneumatic disturbance, flexible tail end target maneuvering and carrying of the target after the capture is finished is fed back to the controller for compensation, so that the robustness of the control system is improved.
(2) According to the unmanned aerial vehicle attitude control method applied to the inverse low and slow small targets, the control of the attitude motion of the inverse unmanned aerial vehicle is realized based on a nonsingular terminal sliding mode control algorithm, the controller is decomposed into the superposition of equivalent motion control near the sliding mode surface and motion control in the sliding mode surface approaching process through designing the sliding mode surface and the approaching law, and then disturbance information in feedback quantity is directly compensated, so that the rapidity and the strong robustness of the unmanned aerial vehicle attitude control in the point-to-point accurate inverse capturing process are effectively improved.
Drawings
Fig. 1 shows a flow chart of a method for controlling the attitude of an unmanned aerial vehicle applied to a reverse low-slow small target according to a preferred embodiment of the invention;
fig. 2 shows a block diagram of the structure of the unmanned aerial vehicle attitude control system applied to a low-speed and slow-speed small target according to a preferred embodiment of the invention;
fig. 3 is a schematic diagram illustrating an equivalent motion segment and an approach motion segment in an unmanned aerial vehicle attitude control method applied to a reverse low-slow small target according to a preferred embodiment of the invention;
fig. 4 shows a unit step response curve of attitude control of a quad-rotor drone according to experimental example 1 of the present invention;
FIG. 5 is a view showing a disturbance observation curve in the triaxial direction in the step response simulation according to experimental example 1 of the present invention;
fig. 6 shows sinusoidal signal tracking curves for attitude control of a quad-rotor drone according to experimental example 1 of the present invention;
fig. 7 shows a disturbance observation curve in the triaxial direction in the step response simulation according to experimental example 1 of the present invention.
Detailed Description
The invention is explained in more detail below with reference to the figures and examples. The features and advantages of the present invention will become more apparent from the description.
The word "exemplary" is used exclusively herein to mean "serving as an example, embodiment, or illustration. Any embodiment described herein as "exemplary" is not necessarily to be construed as preferred or advantageous over other embodiments. While the various aspects of the embodiments are presented in drawings, the drawings are not necessarily drawn to scale unless specifically indicated.
According to the unmanned aerial vehicle attitude control method applied to the anti-low-slow small target, the unmanned aerial vehicle attitude control method combines disturbance estimation based on the extended state observer and unmanned aerial vehicle attitude control based on the nonsingular terminal sliding mode control algorithm, realizes the stability and the rapidity of unmanned aerial vehicle control, and improves the robustness of unmanned aerial vehicle attitude control, and comprises the following steps:
s1, establishing a dynamic model of the unmanned aerial vehicle;
s2, estimating the disturbance based on the extended state observer;
and S3, controlling the attitude of the unmanned aerial vehicle based on the nonsingular terminal sliding mode control algorithm.
Specifically, in step S1, the quad-rotor drone is used to accurately react to the low-slow small target "point-to-point" and model the dynamics model of the quad-rotor drone.
According to the invention, the hovering mode of the unmanned aerial vehicle is linearized, and at the moment, the gyro moment of the rotor wing is far smaller than the control moment and can be ignored, so that a rotary dynamic model is obtained:
Figure BDA0002858335630000061
Figure BDA0002858335630000071
wherein M iscThe force effect corresponding to the pulling force and the torque generated by the rotor wing is represented, is related to the dynamic performance of the motor of the unmanned aerial vehicle and the aerodynamic appearance of the blade, and can be obtained through factory calibration or experiments; d represents a pneumatic damping moment, which comprises a pneumatic damping moment caused by the rotation of the blades and a damping moment generated by the unmanned aerial vehicle body; i ═ diag (I)xx,Iyy,Izz) Is the three-axis rotational inertia of the quadrotor unmanned plane,
further, Mc＝[L,M,N]TAnd L, M and N are control moments in the three-axis direction of the quad-rotor unmanned aerial vehicle respectively.
In the present invention, a ground coordinate system (E system, o) is selectedexeyeze) And body coordinate system (B system, o)bxbybzb) As a basis for dynamic modeling of the quad-rotor unmanned aerial vehicle, the attitude angle theta of the quad-rotor unmanned aerial vehicle under the ground coordinate system is [ phi, theta, psi ═ phi]TThe three-axis attitude change angular speed omega under the machine system is [ p, q, r ═ p]TThe relationship therebetween satisfies the following formula:
Figure BDA0002858335630000072
Figure BDA0002858335630000073
wherein the symbol Λ (Θ) is a matrix
Figure BDA0002858335630000074
The shorthand of (1) has no practical meaning.
Substituting equation two into the kinetic model shown in equation one can make the rotational kinetic model:
Figure BDA0002858335630000075
where the superscript T denotes transpose.
Let H1＝ΛTIΛ，
Figure BDA0002858335630000076
The formula three is simplified:
Figure BDA0002858335630000081
further, an attitude control variable is introduced
Figure BDA0002858335630000088
The state space form of the rotation dynamics of the unmanned aerial vehicle can be obtained as follows:
Figure BDA0002858335630000082
wherein A ═ H1 -1H2，B＝H1 -1ΛT，W＝H1 -1ΛTD, W may be used to represent the total disturbance of the system.
In the invention, aerodynamic disturbance in a complex environment, flexible terminal target maneuvering and disturbance of model parameters caused by carrying low and slow small targets after capture are finished all cause disturbance to a reverse unmanned aerial vehicle, the disturbance needs to be assaulted, and then compensation correction is added in a controller so as to improve the robustness of the system and ensure the fast transient convergence quality of a state observer and an attitude control system in a limited time.
In step S2, the total disturbance W of the system directly affects the attitude output of the quad-rotor drone, so that x is the expansion state quantity2When derived, is defined as
Figure BDA0002858335630000083
According to equation five, the dynamical model of the drone can be represented as:
Figure BDA0002858335630000084
Figure BDA0002858335630000085
therefore, the total disturbance of the system can be estimated by designing the extended state observer so as to compensate the total disturbance in the design control algorithm.
Because the total disturbance of the system can not be directly measured by the sensor, in the invention, the observation value is obtained by resolving the expansion state observer, so that the total disturbance of the system is estimated, and further the total disturbance of the system is compensated in the controller, thereby improving the robustness of the system.
Further, the extended state observer is designed in the form of:
Figure BDA0002858335630000086
Figure BDA0002858335630000087
wherein z is1And z2Respectively being attitude control variable x1And the amount of expansion state x2The observed value of (a); e.g. of the type1＝x1-z1As errors in the observation of attitude angle and angular velocity, e2＝x2-z2An observation error that is a total disturbance;
k1,k2,k3,k4the values are gains of correction terms, alpha is a positive constant coefficient larger than 2, the design of the 5 parameters is related to the estimation error and the stability of the extended state observer, and the skilled person can freely select the parameters according to actual needs. In a preferred embodiment, the 5 parameters are designed for a "point-to-point" precise countering task of the drone on low and slow small targets, and are obtained by performing multiple design iterations in combination with time domain response results.
By expanding the state observer pair z1And z2And (4) observing to estimate the total disturbance W of the system.
The inventor finds that under the form of the extended state observer, the system can be ensured to be quickly and stably converged no matter how far the state estimation error deviates from the balance.
Further, among others, the function sigj(xi) Represents a mathematical calculation process: sigj(xi)＝|xi|j·sign(xi)
The extended state observer provided by the invention can realize accurate and stable estimation of disturbance signals within 0.5s in the three-axis direction, provides accurate feedback information for compensation in a controller, has good finite time convergence and accuracy, and ensures strong robustness of a system to a great extent.
In step S3, the posture control of the sliding mode algorithm is divided into two parts, as shown in fig. 3, the first part is a moving stage of the system on the sliding mode surface, which is called an equivalent moving stage, i.e., a → O process; the second part is the movement phase of the system into the slip-form surface s at the initial point, outside the slip-form surface, called the approach movement section, i.e. s → 0 (x shown in fig. 3)0Process → a).
How to realize the sliding mode motion of the two sections has good performance, and the realization of the transition process has good quality, which is the difficulty of the invention.
When model uncertainty and various interferences exist, the traditional terminal sliding mode control algorithm can effectively realize the stability of a control system in a limited time, so that the strong robustness of the control system is ensured, but the singularity in the vibration and calculation process near the sliding mode surface is still the well-known defect.
In the present invention, in order to avoid these disadvantages and maintain good fast tracking performance for instructions, a non-singular terminal sliding mode control surface is designed as shown in the following formula:
Figure BDA0002858335630000101
wherein, thetae＝Θ-ΘdRepresenting the deviation, λ, between the actual attitude angle and the desired attitude angle1,λ2,ξ1,ξ2All are constant coefficients larger than 0 and satisfy the mathematical relation 1 < xi1< 2 and xi1＜ξ2。
The expected attitude angle is a set value, and a person skilled in the art can freely set the expected attitude angle according to actual needs or obtain the expected attitude angle through calculation by an unmanned aerial vehicle navigation guidance system, and the method is not particularly limited in the invention.
Further, when the response of the closed-loop system is close to the sliding mode surface, s is 0, and the controlled variable u of the equivalent motion section is obtained by solving according to the formula eight and the formula one0：
Figure BDA0002858335630000102
In the invention, in order to improve the rapidity of the sliding mode control algorithm and the robustness in an approach motion section, the following form of approach law is designed,
Figure BDA0002858335630000103
wherein h is1,h2Are parameters and are positive numbers, 0 < xi3＜1。
The approach law of the form ensures that the time from the initial state to the sliding mode surface in the sliding mode control is as short as possible, and simultaneously effectively eliminates the vibration problem when the sliding mode surface passes through from top to bottom.
Further, the sliding mode control amount u of the approaching movement section is described1Can be represented by the following formula:
Figure BDA0002858335630000104
furthermore, in sliding mode control, the total disturbance W of the system needs to be compensated for in a control mode, namely according to the expansion state quantity x2Is observed value z2If the total disturbance compensation is carried out, the following total disturbance compensation control quantity u is also provided in the sliding mode control2：
u2＝-B-1z2Twelve formulas
According to the ninth formula, the tenth formula and the eleventh formula, the total control quantity u of nonsingular terminal sliding mode control applied to the posture control of the counter-control unmanned aerial vehicle can be obtained:
u＝Mc＝u0+u1+u2thirteen formula
The nonsingular terminal sliding mode control u provided by the invention conforms to the Lyapunov stability judgment condition, can be quickly converged within a limited time, and meets the requirements on rapidity and robustness.
According to the invention, the obtained nonsingular terminal sliding mode control total control quantity u is distributed to four motors as the total output of the unmanned aerial vehicle attitude control system, and the corresponding change of the rotating speed is controlled, so that the unmanned aerial vehicle attitude change control is realized.
In the invention, the attitude motion of the counter unmanned aerial vehicle is controlled based on a nonsingular terminal sliding mode control algorithm, the controller is decomposed into superposition of equivalent motion control near the sliding mode surface and motion control in the process of approaching the sliding mode surface by designing the sliding mode surface and the approach law, and then disturbance information in a feedback quantity is directly compensated, so that the rapidity and the strong robustness of the attitude control of the unmanned aerial vehicle in the 'point-to-point' precise counter capturing process are effectively improved.
Examples
Example 1
A certain type of 5-kilogram-level quad-rotor unmanned aerial vehicle is used as a counter unmanned aerial vehicle to perform point-to-point accurate counter task on a low-slow small-invasion target, and the attitude control algorithm in the invention is adopted to perform attitude control on the counter unmanned aerial vehicle.
Specifically, step S1 is to establish a dynamical model for the quad-rotor drone:
Figure BDA0002858335630000121
wherein A ═ H1 -1H2，B＝H1 -1ΛT，W＝H1 -1ΛTD；
H1＝ΛTIΛ，
Figure BDA0002858335630000122
Further, the air conditioner is provided with a fan,
Figure BDA0002858335630000123
Figure BDA0002858335630000124
furthermore, the attitude angle Θ of the quad-rotor unmanned aerial vehicle under the ground coordinate system is ═ phi, theta, psi]TThe three-axis attitude change angular speed omega under the machine system is [ p, q, r ═ p]TThe relationship therebetween satisfies the following formula:
Figure BDA0002858335630000125
Figure BDA0002858335630000126
step S2, estimating the total disturbance W based on the extended state observer, wherein the extended state observer is designed in the following form:
Figure BDA0002858335630000127
Figure BDA0002858335630000128
wherein z is1And z2Respectively being attitude control variable x1And the amount of expansion state x2The observed value of (a); e.g. of the type1＝x1-z1As attitude angle, angular velocity, e2＝x2-z2An observation error that is a total disturbance; by design, the parameters are chosen to be: α ═ 3, k1＝8，k2＝50，k3＝10，k4＝3000。
By expanding the state observer pair z1And z2And (4) observing to estimate the total disturbance W of the system.
Step S3, based on non-singular terminalObtaining the attitude control quantity of the unmanned aerial vehicle by a sliding mode control algorithm, wherein the control quantity u of an equivalent motion section0：
Figure BDA0002858335630000131
Sliding mode control amount u approaching to motion section1：
Figure BDA0002858335630000132
Control variable u for the control compensation of the total disturbance W of the system2：
u2＝-B-1z2Twelve formulas
Then apply to the total control volume that controls unmanned aerial vehicle attitude control for the contrary:
u＝Mc＝u0+u1+u2thirteen formula
Further, in the formulas nine to eleven, after design, the following λ is selected as a parameter1＝diag(0.9,1.2,0.9)，λ2＝diag(2.8,2.8,2.8)，ξ1＝2，ξ2＝2，h1＝diag(2,2,2)，h2＝diag(5,5,5)，ξ3＝0.1。
And in flight control, the total control quantity u of the attitude control of the unmanned aerial vehicle is calculated in real time based on an attitude control algorithm, and is further distributed to the four motors to control the rotation speed change of the motors and control the unmanned aerial vehicle to change the flight state.
Experimental example 1
The performance of the state observer and attitude control algorithm in example 1 was verified by simulation experiments.
The method comprises the steps of constructing a simulation model for attitude control of the quad-rotor unmanned aerial vehicle based on an MATLAB/Simulink environment, setting input signals to be step signals and sine signals respectively, observing rising time and steady-state characteristics of a time domain response curve of the simulation model and tracking effects of continuous change instructions to verify response rapidity of a control system, adding a certain disturbance signal at a dynamic model, observing accuracy of estimation of a disturbance state observer and output conditions of the system at the moment, and verifying robustness of the control system.
Specifically, in the simulation where the input is a step signal:
step signals with excitation of 0.26rad (namely 15 degrees) are input into three attitude angle channels of a control system, simulation time is 5s, an initial quadrotor unmanned aerial vehicle is in a hovering state, attitude angles are all 0, and meanwhile sine and cosine disturbance signals [ N & ltn & gt & lt fourteen & gt are respectively added into moments corresponding to the three channelsroll(t),Npitch(t),Nyaw(t)]TAnd representing the total disturbance of the system by the sine and cosine disturbance signals, thereby evaluating the control effect of the system under the simultaneous action of the excitation signal and the disturbance.
Figure BDA0002858335630000141
The simulation results are shown in fig. 4 and 5, wherein fig. 4 is a unit step response curve of attitude control of the quad-rotor unmanned aerial vehicle, and it can be seen from the graph that the responses of three attitude angles are ideal, and are not influenced by too much total disturbance of the system, the transition process is still fast, and the response rapidity index t is63Both at about 0.39s and the rise time at about 0.66s, with yaw response being slightly faster than roll, which is faster than pitch, due to the effect of parameter adjustments. And basically, no steady-state error exists, the steady state of steady-state oscillation in the sliding mode control algorithm is effectively solved, only fluctuation exists in a very small range, the whole sliding mode control algorithm is in a steady state, the transition process is influenced by disturbance and is not as smooth as a first-order link, and the transition process still shows good change quality. On the whole, the system has stronger anti-interference capability and keeps good rapidity and accuracy.
Fig. 5 is a disturbance observation curve of three axes in step response simulation, and it can be seen from the diagram that the extended state observer has a certain fluctuation and error in the initial stage, which is normal, and the accurate and stable estimation of disturbance signals is realized in the three axes directions around 0.5s, so as to provide accurate feedback information for compensation in the controller. Therefore, the extended state observer designed based on the method is effective and reliable in disturbance estimation, the limited time convergence and the accuracy of the extended state observer meet the design requirements, and the strong robustness of the system is guaranteed to a great extent.
In the simulation where the input is a sinusoidal signal:
sine signals shown in the following formula are designed to be respectively input into three attitude angle channels of a control system, the simulation time is 20s, the initial four-rotor unmanned aerial vehicle is in a hovering state, the attitude angles are all 0, and in addition, the sine and cosine disturbance signals [ N ] are still added into moments corresponding to the three channelsroll(t),Npitch(t),Nyaw(t)]TAnd representing the total disturbance of the system, thereby evaluating the control effect of the system under the simultaneous action of the dynamically changed sinusoidal signal and the disturbance.
The simulation results are shown in fig. 6 and 7, wherein fig. 6 is a sinusoidal signal tracking curve for attitude control of a quad-rotor unmanned aerial vehicle, and it can be seen from the graph that the tracking effect of three attitude angles is ideal, and is not influenced by too much total disturbance of the system, and the overall response is very smooth, wherein due to the influence of parameter adjustment, the command tracking of the roll and pitch channels only has a very small time delay, while the yaw channel has a relatively obvious phase lag, and can be reduced by adjusting the parameters. In addition, the dynamic process basically has no overshoot and oscillation, only has certain deviation in the initial section, has higher integral error level and shows good dynamic quality. On the whole, the system has stronger anti-interference capability and keeps good dynamic change instruction tracking performance.
Fig. 7 is a disturbance observation curve of three axes in step response simulation, and it can be seen from the diagram that the extended state observer has small fluctuation and error in a very short initial time range, which is normal, and the three axes are all around 0.2s to achieve accurate and stable estimation of disturbance signals, so as to provide feedback information for compensation in the controller. Therefore, the estimation of the disturbance by the extended state observer based on the design of the invention is effective and reliable, the limited time convergence and the accuracy meet the design requirements, and the strong robustness of the system is ensured to a great extent.
In the description of the present invention, it should be noted that the terms "upper", "lower", "inner", "outer", "front", "rear", and the like indicate orientations or positional relationships based on operational states of the present invention, and are only used for convenience of description and simplification of description, but do not indicate or imply that the referred device or element must have a specific orientation, be constructed in a specific orientation, and be operated, and thus should not be construed as limiting the present invention. Furthermore, the terms "first," "second," "third," and "fourth" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance.
In the description of the present invention, it should be noted that, unless otherwise specifically stated or limited, the terms "mounted," "connected," and "connected" are to be construed broadly, e.g., as meaning either a fixed connection, a removable connection, or an integral connection; can be mechanically or electrically connected; the connection may be direct or indirect via an intermediate medium, and may be a communication between the two elements. The specific meanings of the above terms in the present invention can be understood in specific cases to those skilled in the art.
The present invention has been described above in connection with preferred embodiments, but these embodiments are merely exemplary and merely illustrative. On the basis of the above, the invention can be subjected to various substitutions and modifications, and the substitutions and the modifications are all within the protection scope of the invention.

Claims (3)

1. An unmanned aerial vehicle attitude control method applied to anti-low and slow small targets is characterized in that the attitude control of an unmanned aerial vehicle in a point-to-point accurate anti-low and slow small target process is realized by combining disturbance estimation based on an extended state observer and a sliding mode control algorithm based on a nonsingular terminal;
the method comprises the following steps:
s1, establishing a dynamic model of the unmanned aerial vehicle;
s2, estimating the disturbance based on the extended state observer;
s3, unmanned aerial vehicle attitude control based on a nonsingular terminal sliding mode control algorithm;
in step S1, linearizing the hovering mode of the unmanned aerial vehicle to obtain a rotational dynamics model:
Figure FDA0003556697030000011
wherein, McThe force effect corresponding to the tension and the torque generated by the rotor wing is represented, and D represents the pneumatic damping moment; i ═ diag (I)xx,Iyy,Izz) Is the three-axis moment of inertia of a quad-rotor unmanned plane, Mc＝[L,M,N]TL, M and N are control moments in the three-axis direction of the quad-rotor unmanned aerial vehicle respectively;
attitude angle theta of quad-rotor unmanned aerial vehicle under ground coordinate system is [ phi, theta, psi ═ phi]TThe three-axis attitude change angular speed omega under the machine system is [ p, q, r ═ p]TThe relationship therebetween satisfies the following formula:
Figure FDA0003556697030000012
the dynamic model of the unmanned aerial vehicle is as follows:
Figure FDA0003556697030000013
wherein x is1Representing the attitude angle and the attitude angular velocity of the unmanned aerial vehicle,
Figure FDA0003556697030000014
Figure FDA0003556697030000021
w represents the total disturbance of the system, H1＝ΛTIΛ，
Figure FDA0003556697030000022
In step S2, the extended state observer is designed in the form of:
Figure FDA0003556697030000023
Figure FDA0003556697030000024
wherein z is1And z2Respectively being attitude control variable x1Observed value and expansion state quantity x of2The observed value of (a); e.g. of the type1＝x1-z1As errors in the observation of attitude angle and angular velocity, e2＝x2-z2An observation error that is a total disturbance;
k1,k2,k3,k4all the correction terms are gains, and alpha is a positive constant coefficient greater than 2;
in step S3, a nonsingular terminal sliding mode control surface shown in equation eight is designed, and the posture control is divided into two parts, namely an equivalent motion section and an approach motion section:
Figure FDA0003556697030000025
wherein, thetae＝Θ-ΘdRepresenting the deviation, λ, between the actual attitude angle and the desired attitude angle1,λ2,ξ1,ξ2All are constant coefficients larger than 0 and satisfy the mathematical relation 1 < xi1< 2 and xi1＜ξ2；
Control quantity u of equivalent motion segment0：
Figure FDA0003556697030000026
Sliding mode control quantity u approaching to motion section1Can be represented by the following formula:
Figure FDA0003556697030000027
wherein h is1,h2Are parameters and are positive numbers, 0 < xi3＜1。
2. The unmanned aerial vehicle attitude control method applied to the anti-low-slow small target according to claim 1,
in step S1, the quad-rotor drone is used to accurately react to low-slow small targets in a point-to-point manner, and a dynamical model of the quad-rotor drone is modeled.
3. The unmanned aerial vehicle attitude control method applied to the anti-low-slow small target according to claim 1,
and carrying out control compensation on the total disturbance W of the system in sliding mode control, wherein the total disturbance compensation control quantity u2：
u2＝-B-1z2Twelve formulas
According to the ninth, eleventh and twelfth formulas, the nonsingular terminal sliding mode control quantity u applied to the posture control of the counter unmanned aerial vehicle can be obtained:
u＝Mc＝u0+u1+u2the formula thirteen.
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