A method for controlling the attitude of a quadrotor drone

Abstract

The present invention belongs to the technical field of unmanned aerial vehicles, and specifically relates to a method for attitude control of a quad-rotor unmanned aerial vehicle, including establishing an attitude dynamics model of a quad-rotor unmanned aerial vehicle, establishing the motion equation and state equation of the unmanned aerial vehicle control system, and designing a linear anti-disturbance controller based on a compensated state observer, and finally establishing a differential tracker to reduce the overshoot of the system. The present invention can reduce the influence of total disturbance on the estimation error in the observer, accurately estimate and compensate for disturbances, enhance the robustness of the system to parameter changes and external disturbances, and design an attitude control method of the unmanned aerial vehicle based on LADRC-CFO. In addition, in order to improve the overall performance of the control system, especially in terms of dynamic performance, steady-state accuracy and anti-disturbance capability, reduce the overshoot of the system, and design a differential tracker to speed up the response speed of the system, so that the system can achieve the desired performance faster.

Description

Technical Field

[0001] The invention belongs to the technical field of unmanned aerial vehicles, and in particular relates to a posture control method for a quad-rotor unmanned aerial vehicle. Background Art

[0002] As an emerging type of aircraft, quadrotor aircraft has attracted extensive attention and applications due to its unique flight characteristics, such as stable flight, strong maneuverability, vertical take-off and landing, free hovering, and the ability to fly in narrow spaces. However, due to the inherent nonlinear, strongly coupled, and multivariable underactuated characteristics of quadrotor aircraft, the design of its flight control algorithm has become a complex and challenging topic;

[0003] At present, the research on flight control algorithms for quadrotors has made significant progress, including linear quadratic regulator (LQR), adaptive control, neural network control, robust control and nonlinear control. However, these methods have certain limitations in practical applications.

[0004] For example, although neural network control and robust control have high control accuracy, the algorithms are complex and time-consuming, and it is difficult to meet the high real-time requirements of quadrotor aircraft; although nonlinear control can achieve more precise control, it often requires full state feedback or high-precision sensors, which are often difficult to achieve in practical applications;

[0005] In recent years, the active disturbance rejection control (ADRC) method has attracted attention due to its strong robustness and anti-interference ability. ADRC achieves high-precision control of the system by observing system disturbances and compensating them in real time.

[0006] However, the ADRC method still faces many challenges when applied to quadrotor control. First, the dynamic model of the quadrotor is complex and has many parameters, which makes the parameter setting of ADRC extremely cumbersome. Second, the traditional ADRC algorithm may be affected by noise when observing system disturbances, resulting in reduced observation accuracy.

[0007] Therefore, an improved method named LADRC for ADRC came into being. However, although it simplifies the parameter setting part, the lack of a differential tracker may cause the LADRC method to produce a large overshoot, affecting the steady-state accuracy.

[0008] Therefore, in view of the deficiencies in the prior art, the present invention proposes an improved active disturbance rejection control method to improve LADRC to solve the above problems. Summary of the invention

[0009] The purpose of the present invention is to provide a method for attitude control of a quad-rotor unmanned aerial vehicle, which can reduce the influence of total disturbance on the estimation error in the observer, accurately estimate and compensate for disturbances, enhance the robustness of the system to parameter changes and external disturbances, and design an attitude control method of the unmanned aerial vehicle based on LADRC-CFO. In addition, in order to improve the overall performance of the control system, especially in terms of dynamic performance, steady-state accuracy and anti-disturbance capability, reduce the system overshoot, and design a differential tracker to speed up the response speed of the system, so that the system can achieve the desired performance faster.

[0010] The technical solution adopted by the present invention is as follows:

[0011] A method for controlling the attitude of a quad-rotor drone comprises the following steps:

[0012] S1: Establish the attitude dynamics model of the quadrotor drone;

[0013] S2: Establish the motion equation and state equation of the UAV control system, and design a linear active disturbance rejection controller based on a compensated state observer;

[0014] S3: Establish a differential tracker to reduce the overshoot of the system.

[0015] The technical effects achieved by the present invention are:

[0016] The present invention designs a compensated state observer (CFO) in derivative form. By introducing a compensation function, the influence of total disturbance on the estimation error in the observer is reduced, the disturbance is accurately estimated and compensated, and the robustness of the system to parameter changes and external disturbances is enhanced. Secondly, the LESO in the LADRC is replaced by the designed CFO, and an attitude control method of the UAV based on LADRC-CFO is designed. In addition, in order to improve the overall performance of the control system, especially in terms of dynamic performance, steady-state accuracy and anti-disturbance capability, and reduce the system overshoot, a differential tracker is designed to speed up the response speed of the system, so that the system can reach the desired performance faster. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 It is a flow chart of the technical solution of the present invention. DETAILED DESCRIPTION

[0018] In order to make the purpose and advantages of the present invention more clearly understood, the present invention is specifically described below in conjunction with embodiments. It should be understood that the following text is only used to describe one or several specific embodiments of the present invention, and does not strictly limit the scope of protection of the specific claims of the present invention.

[0019] like Figure 1 As shown, a method for attitude control of a quad-rotor drone comprises the following steps:

[0020] S1: Establish the attitude dynamics model of the quadrotor drone;

[0021] The attitude of the quad-rotor drone is mainly maintained by the speed of the four motors. The power model of the drone is described as: in, is the lift coefficient, is the drag coefficient, is the total lift brought by the motor driving the propeller and yes Three-axis moment; is the speed of a single motor, ;

[0022] According to the Newton-Euler method, the attitude dynamics model of the quadrotor drone can be described as: in, is the distance from the center of the machine body to the motor rotor, is the total inertia torque of the rotor and the motor, is the air resistance coefficient, They are roll angle, pitch angle, and heading angle, The body is x axis, y axis, z The angular velocity of the axis, The body is x axis, y axis, z The angular acceleration of the axis, The body Directional moment of inertia;

[0023] Due to the strong coupling of the UAV system, the model-based controller design is very difficult. Therefore, the strong coupling relationship is classified as an internal disturbance. ;

[0024] The posture dynamics model is described as: in: Taking external disturbances into account, the attitude dynamics model is modified as follows: in, , Unknown or unmeasurable interference.

[0025] S2: Establish the motion equation and state equation of the UAV control system, and design a linear active disturbance rejection controller based on a compensated state observer;

[0026] According to formula (4), the attitude dynamics equation of the UAV is expressed as: in, y is represented as the output of the system, u is the input of the system, d is represented as the external unknown disturbance of the system, a Expressed as the parameters of the system, b is the control gain of the second-order control system;

[0027] Will Considered as the total disturbance of the system , formula (5) is expressed as: make, , according to formula (6), the system attitude dynamics equation is expressed as: A compensation function observer with derivative form is used to overcome the non-derivative form problem of LESO and improve the accuracy of the observed value;

[0028] Among them, LESO is an observer-based position tracking control strategy, which can be used for MATLAB simulation. During the simulation process, LESO calculates the position error and achieves position tracking by adjusting the controller gain.

[0029] According to formula (7), we can get: in, ; They are The estimated value of is the gain of the observer;

[0030] Subtracting equation (8) from equation (7) yields: According to formula (9), There is a pure differential relationship between them, which solves the problem of error accumulation of stable observer and the estimation error Total interference Related, introduce compensation function , used to reduce the total interference The impact on the estimation error is: Let, equation (7) minus equation (10), and we get the introduced compensation function The observation error is: When the compensation function The closer to the total interference , the estimation error will be significantly reduced;

[0031] Using a low-pass filter to connect the two variables, we get: in, is the cutoff frequency of the low-pass filter;

[0032] Therefore, the expression of the compensation observer (CFO) is: make, , simplifying formula (13) to: in, is the estimated value of disturbance after compensation;

[0033] From equation (14), the characteristic equation of the compensation observer (CFO) is expressed as: Where s is the complex frequency variable after Laplace transformation, equation (14) is the time domain expression, which is transformed into the complex domain after Laplace transformation, and then the transfer function is obtained, and then its characteristic equation (10) is obtained;

[0034] From equation (15), we can see that when all roots of the characteristic equation are in the left half plane, the compensation observer (CFO) is stable. Since the compensation observer is estimable and has the ability to compensate for disturbances, the PD observer can meet the control requirements. Based on the compensation observer (CFO) and the PD controller, the control quantity is Designed for: in, is the expected input, is the PD controller output value, is the link parameter of the PD controller, is the second-order derivative of the desired input ud, It refers to the first-order derivative.

[0035] S3: Establish a differential tracker to reduce the overshoot of the system;

[0036] The formula for establishing the differential tracker is: in, is the expected input, is the sampling time, is the fast factor, is the tracking signal of the initial signal, is the differential of the tracking signal of the initial signal, is the fastest control comprehensive function;

[0037] From equation (17), the control law of the attitude becomes: The above is only a preferred embodiment of the present invention. It should be noted that, for those skilled in the art, several improvements and modifications can be made without departing from the principles of the present invention, and these improvements and modifications should also be considered as the protection scope of the present invention. The structures, devices and operating methods not specifically described and explained in the present invention shall be implemented according to the conventional means in the art unless otherwise specified and limited.

Claims

1. A method for controlling the attitude of a quad-rotor drone, characterized in that: The following steps are involved: S1: Establish the attitude dynamics model of the quadrotor drone; S2: Establish the motion equation and state equation of the UAV control system, and design a linear active disturbance rejection controller based on a compensated state observer; S3: Establish a differential tracker to reduce the overshoot of the system; In S1, the power model of the drone is described as: in, is the lift coefficient, is the drag coefficient, is the total lift brought by the motor driving the propeller and yes Three-axis moment; is the speed of a single motor, ; According to the Newton-Euler method, the attitude dynamics model of the quadrotor drone is described as: in, is the distance from the center of the machine body to the motor rotor, is the total inertia torque of the rotor and the motor, is the air resistance coefficient, are roll angle, pitch angle, and heading angle, respectively. The body is x axis, y axis, z The angular velocity of the axis, are the angular accelerations of the body around the x-axis, y-axis, and z-axis, respectively. The body Directional moment of inertia; Classify strong coupling relationships as internal disturbances ,Should ; The posture dynamics model is described as: in: Taking external disturbances into account, the attitude dynamics model is modified as follows: in, For unknown or unpredictable interference; In S2, according to formula (4), the attitude dynamics equation of the UAV is expressed as: in, y is represented as the output of the system, u is the input of the system, d is represented as the external unknown disturbance of the system, a Expressed as the parameters of the system, b is the control gain of the second-order control system; Will Considered as the total disturbance of the system , formula (5) is expressed as: make, According to formula (6), the system attitude dynamics equation is expressed as: A compensation function observer with a derivative form is used to overcome the non-derivative form problem of LESO. According to formula (7), we can get: in, ; They are The estimated value of is the gain of the observer; Subtracting equation (8) from equation (7) yields: According to formula (9), There is a pure differential relationship between them, and the estimation error Total interference Related, introduce compensation function , used to reduce the total interference The impact on the estimation error is: Let, equation (7) minus equation (10), and we get the introduced compensation function The observation error is: When the compensation function The closer to the total interference , the estimation error will be significantly reduced; Using a low-pass filter to connect the two variables, we get: in, is the cutoff frequency of the low-pass filter; Therefore, the expression of the compensation observer is: make, , simplifying formula (13) to: in, is the estimated value of disturbance after compensation; From equation (14), the characteristic equation of the compensation observer is expressed as: 。 2. The posture control method according to claim 1, characterized in that: From equation (15), we can see that when all roots of the characteristic equation are in the left half plane, the compensation observer is stable. Based on the compensation observer and the PD controller, the control quantity is Designed for: in, is the expected input, is the PD controller output value, It is the link parameter of PD controller.

3. The posture control method according to claim 2, characterized in that: In S3, the establishment formula of the differential tracker is: in, is the expected input, is the sampling time, is the fast factor, is the tracking signal of the initial signal, is the differential of the tracking signal of the initial signal, It is the fastest control comprehensive function.

4. The posture control method according to claim 3, characterized in that: From equation (17), the control law of the attitude becomes: .

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