Input-limited and coupling-output-limited quadrotor unmanned aerial vehicle motion control method and system based on extended state observer

Abstract

The invention discloses an input-limited and coupled-output-limited quadrotor unmanned aerial vehicle motion control method and system based on an extended state observer, and the method comprises the steps: building a quadrotor unmanned aerial vehicle kinetic model, and carrying out the modeling and decoupling of lumped disturbance. And designing an extended state observer to estimate the position, speed and lumped disturbance of the unmanned aerial vehicle. Coupling output constraint is converted into time-varying non-coupling constraint through the rotation matrix, and tracking errors are defined accordingly. And designing a position controller and an attitude controller based on the error and an estimated value of the observer, and generating expected thrust and expected angular velocity. An input limited function and an auxiliary variable are introduced, and the saturation problem of the controller is solved. The system comprises a dynamic modeling and disturbance decoupling module, a state estimation module, an output constraint processing module, a position control and attitude control module and an input saturation compensation module. According to the invention, the trajectory tracking precision, robustness and constraint processing capability of the unmanned aerial vehicle are significantly improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of control, in particular to an input limited and coupled output limited quadrotor unmanned aerial vehicle motion control method based on an extended state observer. BACKGROUND

[0002] With the rapid development of unmanned aerial vehicle technology, quadrotor unmanned aerial vehicles are widely used in environmental monitoring, logistics transportation, disaster rescue and military reconnaissance due to their simple structure, strong maneuverability, outstanding vertical take-off and landing capability and other advantages. In order to achieve accurate trajectory tracking and attitude control, control system design has become one of the core problems of quadrotor unmanned aerial vehicle research. However, in actual application, the control performance of quadrotor unmanned aerial vehicles is often affected by various non-ideal factors, such as actuator saturation, thrust limitation, attitude angular velocity constraint and external wind disturbance, etc., which makes it difficult for the system to meet the control accuracy requirements while ensuring stability.

[0003] Traditional quadrotor unmanned aerial vehicle control methods, such as proportional, integral and differential control, linear quadratic regulation control and feedback linearization-based control methods, usually assume that the system input and output are not limited. Although such methods are simple to implement and have fast response speed, they are prone to system performance degradation or even instability in the presence of input saturation or output limitation. For example, when the maximum thrust or torque of the motor is physically limited, the controller may not be able to output enough control force to achieve the desired trajectory, resulting in attitude overshoot or tracking error accumulation.

[0004] In addition, when performing complex flight tasks, the position and attitude outputs of quadrotor unmanned aerial vehicles often have a coupling relationship, i.e. attitude changes will directly affect position movement, and position deviations will further affect attitude control. This coupling characteristic makes the control design of the system under output limitation more complex. If the output coupling is ignored, the control law may not accurately compensate for the dynamic coupling effects between attitude and position, thereby reducing the overall tracking performance and stability margin of the system.

[0005] On the other hand, input limitation and output limitation often exist simultaneously and interact with each other. For example, when the position of the unmanned aerial vehicle is limited, the direction of the total thrust generated is also limited; and the saturation of the input thrust in turn affects the reachable range of the output response. Existing researches mostly only design controllers for a single type of constraint, lack of unified control strategies under input and output coupling constraint conditions, and are difficult to balance the dynamic performance and constraint satisfaction of the system.

[0006] In order to solve the above problems, in recent years, some control methods based on barrier Lyapunov function, model predictive control or adaptive control have appeared to ensure that the system state or output runs within the constraint range. However, these methods still have high computational complexity, insufficient robustness or difficulty in online implementation when dealing with nonlinear systems with input constraints and coupled output constraints. Therefore, it is urgent to propose a quadrotor unmanned aerial vehicle motion control method which can maintain system stability and control accuracy under the conditions of input constraints and coupled output constraints. SUMMARY

[0007] The purpose of the present application is to provide an input-constrained and coupled output-constrained quadrotor unmanned aerial vehicle motion control method based on an extended state observer to solve the problems of high computational complexity, insufficient robustness or difficulty in online implementation in the prior art.

[0008] To achieve the above purpose, the technical solution provided by the present application is to provide an input-constrained and coupled output-constrained quadrotor unmanned aerial vehicle motion control method based on an extended state observer, comprising the following steps: S1: establishing a quadrotor unmanned aerial vehicle dynamics model, modeling and decoupling the lumped disturbance of the quadrotor unmanned aerial vehicle dynamics model; wherein the lumped disturbance includes the uncertainty of the quadrotor unmanned aerial vehicle dynamics model and external disturbance; S2: designing an extended state observer based on the quadrotor unmanned aerial vehicle dynamics model to estimate the position, speed and lumped disturbance of the quadrotor unmanned aerial vehicle during operation; S3: converting the coupled output constraints of the quadrotor unmanned aerial vehicle into time-varying non-coupled constraints through a rotation matrix, and defining the tracking error under the time-varying non-coupled constraints; S4: based on the tracking error under the time-varying non-coupled constraints, combining the position, speed and lumped disturbance estimated by the extended state observer, designing a position controller for the quadrotor unmanned aerial vehicle to generate a desired thrust for controlling the position of the quadrotor unmanned aerial vehicle; according to the desired thrust, designing an attitude controller for the quadrotor unmanned aerial vehicle to generate a desired angular velocity for controlling the attitude of the quadrotor unmanned aerial vehicle; S5: designing an input-constrained function for the quadrotor unmanned aerial vehicle, introducing an auxiliary variable, and based on the position controller of the quadrotor unmanned aerial vehicle and the attitude controller of the quadrotor unmanned aerial vehicle, obtaining a controller for motion control of the quadrotor unmanned aerial vehicle.

[0009] To optimize the above technical solution, the specific measures taken include: In step S1, the quadrotor unmanned aerial vehicle dynamics model expression is: ; wherein, represents the speed of the quadrotor unmanned aerial vehicle in the world coordinate system; represents the velocity vector of the quadrotor in the world coordinate frame; represents the acceleration vector of the quadrotor in the world coordinate frame; represents the mass of the quadrotor in the world coordinate frame; represents the thrust of the quadrotor in the world coordinate frame; represents the gravitational acceleration; represents the components of the third column of the identity matrix; represents the lumped disturbance; is the derivative of the rotation matrix, representing the rate of change of the orientation of the quadrotor; represents the rotation matrix of the quadrotor from the world coordinate frame to the body coordinate frame; represents the angular velocity vector of the quadrotor in the body coordinate frame; represents the skew-symmetric matrix of the angular velocity vector ; Further, in step S1, the lumped disturbance of the quadrotor dynamics model is modeled and decoupled, and the specific formula is: ; wherein, represents the intrinsic mass of the quadrotor; represents the bounded parameter uncertainty for , which is expressed as: ; The acceleration model of the quadrotor is expressed as: ; ; wherein, represents the external disturbance; The quadrotor dynamics model uncertainty and external disturbance are decoupled.

[0010] In step S2, the extended state observer is designed based on the quadrotor dynamics model to estimate the position, velocity, and lumped disturbance of the quadrotor during operation, and the specific process is: The expression of the extended state observer is: ; wherein, represents the position vector of the quadrotor in the world coordinate frame; represents the velocity vector of the quadrotor in the world coordinate frame; represents the lumped disturbance of the quadrotor dynamics model; , , respectively represent , , the estimated value of represents a positive gain parameter; and represent positive definite matrices; the following variables are defined: ; Further, substituting into the expression, the extended state observer final expression is: ; wherein, represents the difference between the actual position of the quadrotor UAV and the observer observed value; represents the difference between the actual velocity of the quadrotor UAV and the observer observed value; represents the difference between the actual lumped disturbance of the quadrotor UAV and the observer observed value; the dot at the top of the character represents the first order derivative with respect to time .

[0011] In step S3, the coupling output restriction of the quadrotor UAV is converted into a time-varying non-coupling restriction by a rotation matrix, and the tracking error under the time-varying non-coupling restriction is defined, and the specific process is as follows: The position vector of the quadrotor UAV in the world coordinate system is converted by a rotation matrix to obtain: ; wherein, , and indicate the components of the position vector of the quadrotor UAV in the world coordinate system on the coordinate axes x, y, and z; Further, the tracking error calculation formula of the converted quadrotor UAV is: ; ; ; wherein, represents the ideal trajectory of the quadrotor UAV; represents the estimated value of the velocity vector of the quadrotor UAV; represents the virtual control variable of the quadrotor UAV; The time-varying non-coupling restriction is: ; ; wherein, and upper and lower bounds of time-varying constraints, 、 and denote three components of the quadrotor UAV in the world coordinate system, on the coordinate axes x, y, z, denote the ideal trajectory of the quadrotor UAV after conversion by the conversion matrix; 、 denote two components of the real-time position of the quadrotor UAV in the world coordinate system.

[0012] In step S4, the position controller of the quadrotor UAV is designed to generate a desired thrust for controlling the position of the quadrotor UAV, and the specific process is as follows: The position controller of the time-varying non-coupled constrained quadrotor UAV is expressed as: ; wherein, denotes the observation value of the converted quadrotor UAV speed error; denotes a positive definite matrix; denotes a positive definite matrix; denotes an auxiliary variable designed to eliminate redundant terms; denotes the acceleration of gravity; denotes the components of the third column of the unit matrix; denotes the inherent mass of the quadrotor UAV; denotes the observation value of the lumped disturbance of the quadrotor UAV dynamics model; Further, the calculation formula of the desired thrust is: ; wherein, and denote the attitude information of the quadrotor UAV during flight; denotes the square of the skew-symmetric matrix of ; denotes the norm of the desired thrust.

[0013] In step S4, the attitude controller of the quadrotor UAV is designed to generate a desired angular velocity for controlling the attitude of the quadrotor UAV, and the specific process is as follows: The attitude error of the quadrotor UAV is expressed as: ; The desired angular velocity is: ; wherein , , is a positive integer; is a stabilizing term, is the third component of the angular velocity in the world coordinate system, is the third column of the identity matrix; represents the square of the skew-symmetric matrix related to the third column of the identity matrix; is the transpose of the rotation matrix; represents the skew-symmetric matrix related to the desired attitude; represents the desired attitude angle; represents the skew-symmetric matrix related to the third component of the identity matrix; represents the velocity error of the quadrotor UAV after transformation by the transformation matrix.

[0014] Further, in step S5, the input limited function of the quadrotor UAV is designed, an auxiliary variable is introduced, and a controller for quadrotor UAV motion control is obtained based on the position controller of the quadrotor UAV and the attitude controller of the quadrotor UAV, in a specific manner as follows: The input limited function of the quadrotor UAV is expressed as: ; ; wherein, represents the designed thrust; represents the upper bound of the input limitation; when the input reaches saturation, and there is a difference, denoted as , which is described as: ; Further, the auxiliary variable is designed as: ; wherein, is a positive definite matrix; is the tracking error of the transformed quadrotor UAV; is a positive definite matrix; is the auxiliary variable related to the input limitation of the quadrotor UAV; is a normal number related to the tracking performance of the quadrotor UAV; The controller for quadrotor UAV motion control is expressed as: ; As another important technical solution, the application further provides an input limited and coupled output limited quadrotor UAV motion control system based on an extended state observer, comprising: The dynamic modeling and disturbance decoupling module is used for establishing a dynamic model of the quad-rotor unmanned aerial vehicle and modeling and decoupling lumped disturbances of the dynamic model of the quad-rotor unmanned aerial vehicle, wherein the lumped disturbances include uncertainties and external disturbances of the dynamic model of the quad-rotor unmanned aerial vehicle. The state estimation module is used for designing an extended state observer based on the dynamic model of the quad-rotor unmanned aerial vehicle to estimate positions, velocities and lumped disturbances of the quad-rotor unmanned aerial vehicle in the running process. The output constraint processing module is used for converting coupled output constraints of the quad-rotor unmanned aerial vehicle into time-varying non-coupled constraints through a rotation matrix and defining tracking errors under the time-varying non-coupled constraints. The position control and attitude control module is used for designing a position controller of the quad-rotor unmanned aerial vehicle based on the tracking errors under the time-varying non-coupled constraints, combining the positions, velocities and lumped disturbances estimated by the extended state observer to generate a desired thrust force for controlling the position of the quad-rotor unmanned aerial vehicle; and designing an attitude controller of the quad-rotor unmanned aerial vehicle according to the desired thrust force to generate a desired angular velocity for controlling the attitude of the quad-rotor unmanned aerial vehicle. The input saturation compensation module is used for designing an input constraint function of the quad-rotor unmanned aerial vehicle, introducing an auxiliary variable and obtaining a controller for motion control of the quad-rotor unmanned aerial vehicle based on the position controller of the quad-rotor unmanned aerial vehicle and the attitude controller of the quad-rotor unmanned aerial vehicle.

[0015] The application further provides an electronic device, which comprises a memory, a processor, and a computer program stored in the memory and capable of running on the processor, and the processor implements the motion control method of the quad-rotor unmanned aerial vehicle with input constraints and coupled output constraints based on an extended state observer when running the computer program.

[0016] The application further provides a computer readable storage medium, which stores a computer program, and the computer program enables a computer to execute the motion control method of the quad-rotor unmanned aerial vehicle with input constraints and coupled output constraints based on an extended state observer.

[0017] Compared with the prior art, the application has the following beneficial effects: The application effectively processes the coupled output constraint relationship between the position and the attitude while considering the input constraints such as the actuator thrust saturation and the attitude angular velocity limitation of the unmanned aerial vehicle, thereby improving the trajectory tracking performance under the premise of ensuring the stability of the system.

[0018] The application improves the feasibility of the control law design and the realizability of the system by constructing a coupled output constraint model and introducing a constraint transformation function to gradually decouple the complex coupled output constraints into independent constraints and giving a spherical region reference.

[0019] The application gives different control schemes for the cases that the dynamic parameters of the unmanned aerial vehicle are known and unknown respectively in the controller design, so that the method has stronger universality and robustness, and is not limited to a specific type of unmanned aerial vehicle platform.

[0020] The input saturation compensation mechanism is comprehensively considered in the control law, so that the overdrive phenomenon of the actuator can be effectively avoided, and through strict Lyapunov stability analysis, the system can still maintain bounded stability under uncertain disturbance and parameter variation.

[0021] The application has significant advantages in control accuracy, calculation efficiency and constraint processing capability, and provides theoretical and engineering support for safe and high-performance flight of the quad-rotor unmanned aerial vehicle in complex environments. BRIEF DESCRIPTION OF DRAWINGS

[0022] Figure 1 The model of the quad-rotor unmanned aerial vehicle of the application.

[0023] Figure 2 The tracking error change curve between the actual trajectory and the expected trajectory of the quad-rotor unmanned aerial vehicle in the motion process in the embodiment of the application.

[0024] Figure 3 The three-dimensional graph of the quad-rotor unmanned aerial vehicle moving under the condition of coupling restriction in the embodiment of the application.

[0025] Figure 4 The two-dimensional graph of the quad-rotor unmanned aerial vehicle moving under the condition of coupling restriction in the embodiment of the application.

[0026] Figure 5 The fitting condition of the position observation value and the actual position value of the extended state observer when the quad-rotor unmanned aerial vehicle moves in the embodiment of the application.

[0027] Figure 6 The fitting condition of the disturbance observation value and the actual disturbance value of the extended state observer when the quad-rotor unmanned aerial vehicle moves in the embodiment of the application.

[0028] Figure 7 The input restriction condition of the quad-rotor unmanned aerial vehicle in the embodiment of the application. DETAILED DESCRIPTION

[0029] The above content of the application will be further described in the form of specific embodiments, but this should not be understood as limiting the scope of the above subject matter of the application to the following embodiments, and any technology realized based on the above content of the application belongs to the scope of the application.

[0030] S1: Establish a dynamic model of a quadrotor UAV and model and decouple the lumped disturbance of the quadrotor UAV dynamic model; wherein, the lumped disturbance includes the uncertainty of the quadrotor UAV dynamic model and external disturbances; In this embodiment, the dynamic model expression of the quadcopter UAV is: ; in, This indicates the velocity of the quadcopter drone in the world coordinate system; This represents the velocity vector of a quadcopter UAV in the world coordinate system. This represents the acceleration vector of a quadcopter UAV in the world coordinate system. This represents the mass of a quadcopter drone in the world coordinate system. This represents the thrust of a quadcopter drone in the world coordinate system. Represents gravitational acceleration; This represents the component in the third column of the identity matrix; Indicates lumped disturbance; This indicates the rate of change of direction for a quadcopter drone; This represents the rotation matrix of the UAV from the world coordinate system to the body coordinate system. This represents the angular velocity vector of a quadcopter UAV in the collective coordinate system. Represents the vector of angular velocity The antisymmetric matrix; below is the thrust Provide a detailed description: In the body coordinate system, the thrust generated by each rotor is in the same direction as the z-axis, therefore It can be represented in the following ways: ; in, Indicates the magnitude of the thrust; The representation is as follows: ; To ensure that the quadcopter drone can effectively track the desired trajectory during actual operation, a desired vector thrust is designed and calculated as follows: ; in, Indicates the magnitude of the desired vector thrust; It includes the attitude angle information of the UAV, and the calculation method is as follows: ; The thrust can be derived from the above formula. The expression: ; in, With together constitute the attitude information contained in the flight process of the unmanned aerial vehicle; represent the anti-symmetric matrix of square. This is the mathematical representation of the SO3 model of the quadrotor unmanned aerial vehicle, which regards the outer loop of the controller as the position loop and the inner loop as the attitude loop, and realizes the position and attitude control of the unmanned aerial vehicle through the design of the thrust and angular velocity .

[0031] As preferred, the is modeled, mainly considering that the mass of the unmanned aerial vehicle changes in the actual flight process due to some difficult-to-measure variables, so the mass is decomposed, that is: ; wherein, represents the inherent mass of the unmanned aerial vehicle; represents the bounded parameter uncertainty of , which is expressed as: ; After modeling, the acceleration model of the unmanned aerial vehicle is expressed as: ; wherein, , represents external disturbance, and the model uncertainty and external disturbance are decoupled for separate consideration, thereby providing a theoretical basis for meeting the experimental accuracy requirements.

[0032] Step S2, the extended state observer is designed based on the dynamics model of the quadrotor unmanned aerial vehicle, and the position, velocity and lumped disturbance of the quadrotor unmanned aerial vehicle in the running process are estimated, and the specific process is as follows: The expression of the extended state observer is: ; wherein, represents the position vector of the quadrotor unmanned aerial vehicle in the world coordinate system; represents the velocity vector of the quadrotor unmanned aerial vehicle in the world coordinate system; , , respectively represent the estimated values of , , ; represents a positive gain parameter and is regarded as an observation bandwidth; and represent positive definite matrices; the following variables are defined: ; Substituting into the expression, the final expression for the extended state observer is: ; in, This represents the difference between the actual position of the quadcopter drone and the observation value from the observer; This represents the difference between the actual speed of the quadcopter drone and the speed observed by the observer. This represents the difference between the actual lumped interference of the quadcopter drone and the observer's observation; the dot at the top of the character represents the time... The first derivative.

[0033] Preferably, to facilitate the analysis of the stability of the extended state observer, a new variable is defined: ; Its derivative satisfies: ; in, ,

[0034] Design a Lyapunov function: ; Taking its time derivative, we get:

[0035] As a preferred option,

[0036] make Then we have:

[0037] For the newly defined error variable, its interval of convergence is: .

[0038] Step S3, which involves transforming the coupled output constraint of the quadcopter UAV into a time-varying uncoupled constraint using a rotation matrix, and defining the tracking error under the time-varying uncoupled constraint, is as follows: In this embodiment, the spherical coupling output restricted region is considered: ; Preferably, using a rotation matrix can handle more difficult-to-analyze regional scenarios: ; express Position information after rotation (diamond-shaped area) This patent uses a spherical region as an example. The expression is as follows: ; The formula for calculating the tracking error of the converted quadcopter UAV is as follows: ; ; ; in, The ideal trajectory for a quadcopter drone. This represents the ideal trajectory of the UAV after transformation using the transformation matrix.

[0039] The converted end effector is limited to: ; in, ; ; ; In some implementations... The coupled output limitation is transformed into: ; Finally obtained The time-varying uncoupled constraint is:

[0040] in, and These represent the upper and lower bounds of the time-varying constraint, respectively. , and express The three components; In some implementations, this decoupling method is not limited to spherical constraints and can be applied to a wide variety of spatial constraints in real life. For example, a rhomboid region can be considered... Coordinate analysis can simplify the process by rotating a rhombus into a square.

[0041] Consider the following Lyapunov function: ; in,

[0042] As a preferred option, for Differentiating over time yields: ; in,

[0043] get:

[0044] in, .

[0045] definition and virtual control quantity ,get:

[0046] in, , , , .

[0047] Consider the Lyapunov function:

[0048]

[0049] Preferably, the derivative of the above formula with respect to time yields:

[0050] Design an auxiliary variable related to the Lyapunov function, its expression is: ; Redesign the third Lyapunov function to include the auxiliary variables and extended state observers of the previous Lyapunov function: ; Differentiating it, we get:

[0051] Step S4, the design of the quadcopter UAV's position controller generates the desired thrust for controlling the quadcopter UAV's position. The specific process is as follows: The position controller of the time-varying uncoupled restricted quadrotor UAV is expressed as follows: ; in, The observed value represents the converted speed error of the quadcopter UAV; Represents a positive definite matrix; Represents a positive definite matrix; This represents the auxiliary variable designed to eliminate redundant terms; in, , Bring it into :

[0052] By using Young's inequality bounding, that is:

[0053] The final result is:

[0054] in, ; ; , , This represents the maximum value among the eigenvalues ​​of a matrix. The minimum value among the eigenvalues ​​of the matrix can be used to prove that the controller is stable.

[0055] Step S4, the attitude controller for the quadcopter UAV is designed to generate the desired angular velocity for controlling the attitude of the quadcopter UAV. The specific process is as follows: The attitude error of the quadcopter UAV is expressed as: ; Design the final Lyapunov function:

[0056] Taking the time derivative, we get:

[0057] in To ensure stability, the angular velocity was then designed as follows: ; in , , It is a positive integer; As a stable term, This is the third component of the angular velocity in the world coordinate system. These are the components of the third column of the identity matrix; Represents the square of the antisymmetric matrix that relates to the third column component of the identity matrix; This is the transpose of the rotation matrix; This represents the antisymmetric matrix associated with the desired pose; Indicates the desired attitude angle; Represents the antisymmetric matrix with respect to the third component of the identity matrix; This represents the speed error of the quadcopter drone after transformation by the transformation matrix.

[0058] The final result is:

[0059] In step S5, the input constrained function of the quadcopter UAV is designed, auxiliary variables are introduced, and a controller for motion control of the quadcopter UAV is obtained based on the position controller and attitude controller of the quadcopter UAV. The specific method is as follows: The input constraint function of the quadcopter UAV is expressed as: ; ; in, ; Indicates the thrust of the design; This represents an upper bound on the input constraint; when the input reaches saturation, and There exists a difference, denoted as The description is as follows: ; Preferably, the auxiliary variables are designed as follows: ; in, It is a positive definite matrix; The tracking error of the converted quadcopter UAV; It is a positive definite matrix; For auxiliary variables related to input constraints of quadcopter drones; For normal numbers related to the tracking performance of quadcopter drones; Finally, we design the overall Lyapunov function and prove its stability: ; Final proof The derivative with respect to time is rearranged as follows:

[0060] In some implementations, the specific parameters are set as follows: , kg, =0.221kg.

[0061] Preferably, the simulation platform is based on Matlab R2022a under the Windows 11 64-bit operating system, and the simulation object is as follows. Figure 1 As shown. The Cartesian position coordinates of the quadcopter UAV in its initial state are... The initial angle is Numerical simulation results demonstrate the feasibility of the control method proposed in this embodiment. The figure-eight reference trajectory for the quadcopter UAV following is: .

[0062] In this embodiment, the parameters of the selected quadcopter UAV are shown in Table 1: Table 1 Parameters of Quadrotor UAV

[0063] In some implementations, such as Figure 2 As shown in the figure, this curve illustrates the variation of the tracking error between the actual trajectory and the desired trajectory of the quadcopter UAV during its movement. It reflects the performance of the control method of this invention in position tracking and verifies its control accuracy under conditions of limited coupling output.

[0064] like Figure 3 As shown, this figure is a 3D diagram of the motion of a quadcopter UAV under coupled constraints, demonstrating the actual flight trajectory and expected trajectory of the quadcopter UAV under these conditions. It intuitively illustrates how the UAV follows a preset path and satisfies constraints in three-dimensional space.

[0065] like Figure 4 As shown, the Figure Four A two-dimensional diagram of the rotorcraft UAV's motion under limited coupling conditions facilitates the analysis of the UAV's horizontal motion performance. It further illustrates that the system can still maintain good trajectory tracking capability even under limited coupling output.

[0066] like Figure 5 As shown, the position values ​​estimated by the extended state observer are compared with the actual position values, demonstrating the accuracy of the extended state observer in estimating the UAV's position. This demonstrates the effectiveness and robustness of the extended state observer when the system has disturbances and uncertainties.

[0067] like Figure 6 As shown, the estimated values ​​of disturbance in three directions by the extended state observer are compared with the actual values, demonstrating the accuracy of the extended state observer in estimating UAV disturbance. This also shows that the extended state observer has a good fitting effect on the disturbance.

[0068] like Figure 7 As shown in the figure, this diagram illustrates the limitations of input thrust or torque when a quadcopter UAV executes control commands, reflecting the controller's performance under input saturation conditions. This demonstrates that the input constraint function and auxiliary variables designed in this invention effectively prevent actuator saturation and ensure system stability.

[0069] In another embodiment of the present invention, an input-constrained and coupling-output-constrained motion control system for a quadrotor unmanned aerial vehicle based on an extended state observer is proposed, comprising: The dynamics modeling and disturbance decoupling module is used to establish a dynamics model of a quadrotor UAV and to uniformly model and decouple the uncertainties and external disturbances of the quadrotor UAV dynamics model. The state estimation module is used to design an extended state observer based on the dynamic model of the quadrotor UAV to estimate the position, velocity and lumped disturbance of the quadrotor UAV during operation. The output constraint processing module is used to transform the coupled output constraint of the quadcopter UAV into a time-varying uncoupled constraint through a rotation matrix, and to define the tracking error under the time-varying uncoupled constraint. The position control and attitude control module is used to design a position controller for a quadcopter UAV based on the tracking error under time-varying uncoupled constraints, combined with the position, velocity and lumped disturbance estimated by the extended state observer, and to generate the desired thrust for controlling the position of the quadcopter UAV; based on the desired thrust, the attitude controller for the quadcopter UAV is designed to generate the desired angular velocity for controlling the attitude of the quadcopter UAV. The input saturation compensation module is used to design the input constrained function of the quadrotor UAV. By introducing auxiliary variables, a controller for motion control of the quadrotor UAV is obtained based on the position controller and attitude controller of the quadrotor UAV.

[0070] In another embodiment of the present invention, an electronic device is proposed, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the input-constrained and coupled-output-constrained motion control method for a quadrotor unmanned aerial vehicle based on an extended state observer as described above.

[0071] In another embodiment of the present invention, a computer-readable storage medium is provided storing a computer program that causes a computer to execute, as described above, an input-constrained and coupled-output-constrained motion control method for a quadrotor unmanned aerial vehicle based on an extended state observer.

[0072] In the embodiments disclosed in this application, the computer storage medium may be a tangible medium that may contain or store programs for use by or in conjunction with an instruction execution system, apparatus, or device. The computer storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of computer storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing. The above descriptions are merely preferred embodiments of the present invention and are not intended to limit the present invention in any way. Any simple modifications, equivalent substitutions, and improvements made by those skilled in the art to the above embodiments without departing from the scope of the present invention and based on the technical essence of the present invention shall still fall within the protection scope of the present invention.

Claims

1. A motion control method for a quadrotor unmanned aerial vehicle based on an extended state observer with input-constrained and coupled-output-constrained parameters, characterized in that, Includes the following steps: S1: Establish a dynamic model of the quadrotor UAV, and model and decouple the lumped disturbance of the quadrotor UAV dynamic model; wherein, the lumped disturbance includes the uncertainty of the quadrotor UAV dynamic model and external disturbances; S2: Based on the dynamic model of a quadrotor UAV, an extended state observer is designed to estimate the position, velocity, and lumped disturbance of the quadrotor UAV during operation. S3: Transform the coupled output constraint of the quadcopter UAV into a time-varying uncoupled constraint by using a rotation matrix, and define the tracking error under the time-varying uncoupled constraint. S4: Based on the tracking error under time-varying uncoupled constraints, and combined with the position, velocity and lumped disturbance estimated by the extended state observer, design a position controller for the quadcopter UAV to generate the desired thrust for controlling the position of the quadcopter UAV; based on the desired thrust, design an attitude controller for the quadcopter UAV to generate the desired angular velocity for controlling the attitude of the quadcopter UAV. S5: Design the input constrained function for the quadcopter UAV, introduce auxiliary variables, and obtain the controller for motion control of the quadcopter UAV based on the position controller and attitude controller of the quadcopter UAV.

2. The motion control method for a quadrotor UAV based on an extended state observer with input-constrained and coupling-output-constrained characteristics as described in claim 1, characterized in that: In step S1, the dynamic model expression of the quadcopter UAV is: ； in, This indicates the velocity of the quadcopter drone in the world coordinate system; This represents the velocity vector of a quadcopter UAV in the world coordinate system. This represents the acceleration vector of a quadcopter UAV in the world coordinate system. This represents the mass of a quadcopter drone in the world coordinate system. This represents the thrust of a quadcopter drone in the world coordinate system. Represents gravitational acceleration; This represents the component in the third column of the identity matrix; Indicates lumped disturbance; This indicates the rate of change of direction for a quadcopter drone; This represents the rotation matrix of a quadcopter UAV from the world coordinate system to the body coordinate system. This represents the angular velocity vector of a quadcopter UAV in the collective coordinate system. Represents the vector of angular velocity The antisymmetric matrix; In step S1, the lumped disturbance of the quadcopter UAV dynamics model is modeled and decoupled, and the specific formula is as follows: ； in, This indicates the inherent mass of a quadcopter drone; Indicating targeting The bounded parameter uncertainty is expressed as: ； The acceleration model of a quadcopter drone is represented as follows: ； ； in, Indicates external interference; Decouple the uncertainties and external disturbances in the dynamic model of the quadcopter UAV.

3. The motion control method for a quadrotor UAV based on an extended state observer with input-constrained and coupling-output-constrained characteristics, as described in claim 2, is characterized in that: In step S2, the extended state observer designed based on the quadrotor UAV dynamics model is used to estimate the position, velocity, and lumped disturbance of the quadrotor UAV during operation. The specific process is as follows: The extended state observer expression is: ； in, This represents the position vector of a quadcopter UAV in the world coordinate system. , , They represent , , The estimated value; Indicates the positive gain parameter; and Represents a positive definite matrix; define the following variables: ； Substituting into the expression, the final expression for the extended state observer is: ； in, This represents the difference between the actual position of the quadcopter drone and the observation value from the observer; This represents the difference between the actual speed of the quadcopter drone and the speed observed by the observer. This represents the difference between the actual lumped interference of the quadcopter drone and the observer's observation; the dot at the top of the character represents the time... The first derivative.

4. The motion control method for a quadrotor UAV based on an extended state observer with input-constrained and coupling-output-constrained characteristics as described in claim 3, characterized in that: In step S3, the coupling-constrained output of the quadcopter UAV is transformed into a time-varying uncoupled constraint using a rotation matrix, and the tracking error under the time-varying uncoupled constraint is defined. The specific process is as follows: By rotation matrix Position vector of a quadcopter UAV in world coordinate system After conversion, we get: ； in, , and Show the position vector of the quadcopter UAV in the world coordinate system. Components on the coordinate axes x, y, z; The formula for calculating the tracking error of the converted quadcopter UAV is as follows: ； ； ； in, This represents the ideal trajectory of a quadcopter drone; This represents an estimate of the velocity vector of a quadcopter drone. This represents the virtual control variable for a quadcopter drone; The time-varying uncoupling constraint is: ； ； in, and These represent the upper and lower bounds of the time-varying constraint, respectively. , and Represents the world coordinate system The three components on the coordinate axes x, y, z This represents the ideal trajectory of the quadcopter UAV after transformation by the transformation matrix.

5. The motion control method for a quadrotor UAV based on an extended state observer with input-constrained and coupling-output-constrained characteristics as described in claim 1, characterized in that: In step S4, the design of the position controller for the quadcopter drone generates the desired thrust for controlling the position of the quadcopter drone. The specific process is as follows: The position controller of the time-varying uncoupled restricted quadrotor UAV is expressed as follows: ； in, The observed value represents the converted speed error of the quadcopter UAV; Represents a positive definite matrix; This represents a variable matrix; Represents a positive definite matrix; This represents the auxiliary variable designed to eliminate redundant terms; Represents gravitational acceleration; This represents the component in the third column of the identity matrix; This indicates the inherent mass of a quadcopter drone; The observed values ​​represent the lumped perturbations of the quadcopter UAV dynamics model; The formula for calculating the desired thrust is: ； in, and This indicates the attitude information of the quadcopter drone during flight; Indicates and The square of the antisymmetric matrix; This represents the norm of the desired thrust.

6. The motion control method for a quadrotor UAV based on an extended state observer with input-constrained and coupling-output-constrained characteristics, as described in claim 5, is characterized in that: In step S4, the attitude controller for the quadcopter drone is designed to generate the desired angular velocity for controlling the attitude of the quadcopter drone. The specific process is as follows: The attitude error of the quadcopter UAV is expressed as: ； The desired angular velocity is: ； in , , It is a positive integer; As a stable term, This is the third component of the angular velocity in the world coordinate system. These are the components of the third column of the identity matrix; Represents the square of the antisymmetric matrix that relates to the third column component of the identity matrix; This is the transpose of the rotation matrix; This represents the antisymmetric matrix associated with the desired pose; Indicates the desired attitude angle; Represents the antisymmetric matrix with respect to the third component of the identity matrix; This represents the speed error of the quadcopter drone after transformation by the transformation matrix.

7. The motion control method for a quadrotor UAV based on an extended state observer with input-constrained and coupling-output-constrained characteristics as described in claim 1, characterized in that: In step S5, the input constrained function of the quadcopter UAV is designed, auxiliary variables are introduced, and a controller for motion control of the quadcopter UAV is obtained based on the position controller and attitude controller of the quadcopter UAV. The specific method is as follows: The input constraint function of the quadcopter UAV is expressed as: ； ； in, Indicates the thrust of the design; This represents an upper bound on the input constraint; when the input reaches saturation, and There exists a difference, denoted as The description is as follows: ； The auxiliary variables are designed as follows: ； in, It is a positive definite matrix; The tracking error of the converted quadcopter UAV; It is a positive definite matrix; For auxiliary variables related to input constraints of quadcopter drones; For normal numbers related to the tracking performance of quadcopter drones; The controller used for motion control of the quadcopter UAV has the following expression: ； ； in, This represents the actual thrust after the solution is obtained; The norm of the desired thrust; and This indicates the attitude information of the quadcopter drone during flight; Indicates and The square of the antisymmetric matrix.

8. A motion control system for a quadrotor unmanned aerial vehicle based on an extended state observer with input-constrained and coupled-output-constrained characteristics, characterized in that, include: The dynamics modeling and disturbance decoupling module is used to establish a dynamics model of a quadrotor UAV and to model and decouple the lumped disturbances of the quadrotor UAV dynamics model; the lumped disturbances include the uncertainties of the quadrotor UAV dynamics model and external disturbances. The state estimation module is used to design an extended state observer based on the dynamic model of the quadrotor UAV to estimate the position, velocity and lumped disturbance of the quadrotor UAV during operation. The output constraint processing module is used to transform the coupled output constraint of the quadcopter UAV into a time-varying uncoupled constraint through a rotation matrix, and to define the tracking error under the time-varying uncoupled constraint. The position control and attitude control module is used to design a position controller for a quadcopter UAV based on the tracking error under time-varying uncoupled constraints, combined with the position, velocity and lumped disturbance estimated by the extended state observer, and to generate the desired thrust for controlling the position of the quadcopter UAV; based on the desired thrust, the attitude controller for the quadcopter UAV is designed to generate the desired angular velocity for controlling the attitude of the quadcopter UAV. The input saturation compensation module is used to design the input constrained function of the quadrotor UAV. By introducing auxiliary variables, a controller for motion control of the quadrotor UAV is obtained based on the position controller and attitude controller of the quadrotor UAV.

9. An electronic device, characterized in that, include: The system includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the motion control method for an input-constrained and coupled-output-constrained quadrotor unmanned aerial vehicle based on an extended state observer as described in any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: The computer program causes the computer to execute the input-constrained and coupled-output-constrained motion control method for a quadrotor unmanned aerial vehicle based on an extended state observer as described in any one of claims 1 to 7.

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