Self-adaptive control method for multi-source uncertainty glide mode of quad-rotor unmanned aerial vehicle

Abstract

The embodiment of the invention discloses a quadrotor unmanned aerial vehicle multi-source uncertainty glide mode self-adaptive control method, and the method comprises the steps: combining the resistance of a quadrotor unmanned aerial vehicle, the external unknown disturbance and an unknown function in a system model, and carrying out the calculation to obtain the total disturbance of the quadrotor unmanned aerial vehicle, constructing a motion model of the quad-rotor unmanned aerial vehicle according to the actuator fault influence and the total disturbance; obtaining a moving target expected value of the four-rotor unmanned aerial vehicle; converting the expected value of the moving target into a smooth process, and calculating to obtain the expected value of the system; establishing a state space expression of the four-rotor unmanned aerial vehicle system; designing a super-distortion expansion state observer which is used for observing unknown disturbance existing in the system; and obtaining an estimated value of a fault in the system model by utilizing the design of an adaptive rate, and calculating to obtain a control parameter of the system based on the estimated value. An expansion state observer and a sliding mode self-adaptive controller are designed according to the characteristics of each disturbance, and the problem of insufficient anti-disturbance is solved.

Description

Technical Field

[0001] The present invention relates to the technical field of unmanned aerial vehicle control, and particularly to a multi-source uncertainty sliding mode adaptive control method for a quadrotor unmanned aerial vehicle. Background Art

[0002] In recent years, unmanned aerial vehicles (UAVs) have gradually replaced manned aircraft in various scenarios due to their unique advantages. They can perform various tasks in environments with unknown risks and those difficult for humans to access. Compared with fixed-wing UAVs, rotor UAVs have the advantages of vertical takeoff and landing, flexible flight maneuverability, easy maintenance, small size, convenient portability and use, etc., and have broad development prospects. Currently, they are widely used in fields such as payload transportation, urban monitoring, environmental monitoring, and precision agriculture.

[0003] A quadrotor UAV is a typical highly nonlinear, strongly coupled, multi-variable underactuated system, and is extremely vulnerable to various uncertain factors, such as time-varying wind disturbances, model uncertainties, actuator failures, input saturation, low state detection accuracy, input time delay, etc. These factors will increase the control difficulty of the UAV in stable flight.

[0004] In the prior art, traditional linear control methods and more complex nonlinear control strategies are usually adopted to solve the stability and trajectory tracking problems of quadrotor aircraft. The most common linear control method is PID, which is flexible and easy to implement, and has a low dependence on the controlled object model, so it is widely used in industrial control systems. In nonlinear control methods, feedback linearization is a common technique used for the control of quadrotor aircraft. This method designs a feedforward control to transform the nonlinear model of the quadrotor aircraft into an equivalent linear model, and then uses the design method of a linear system controller to realize the design of the controller. Finally, combining the nonlinear feedforward control and the linear controller forms a complete nonlinear controller. Many nonlinear control methods have been applied to quadrotor aircraft, such as sliding mode control, backstepping control, and predictive control. However, nonlinear control methods cannot effectively suppress unknown disturbances in the presence of multi-source uncertain factors, and cannot specifically solve the problem of actuator failures in quadrotor UAVs. Summary of the Invention

[0005] The embodiments of the present invention provide a multi-source uncertainty sliding mode adaptive control method for a quadrotor UAV to solve the technical problems in the prior art that quadrotor UAVs cannot effectively suppress unknown disturbances and cannot specifically solve the problem of actuator failures in quadrotor UAVs.

[0006] The embodiments of the present invention provide a multi-source uncertainty sliding mode adaptive control method for a quadrotor UAV, including: Combine the self-resistance of the quadrotor UAV, the external unknown disturbances, and the unknown functions existing in the system model to calculate the total disturbance suffered by the quadrotor UAV; Construct the motion model of the quadrotor UAV according to the actuator fault influence and the total disturbance; Obtain the expected value of the motion target of the quadrotor UAV; Convert the expected value of the motion target into a smoothing process and calculate the expected value of the system; Establish the state-space expression of the quadrotor UAV system; Design a super-twisting extended state observer for observing the unknown disturbances existing in the system; Use the design of the adaptive rate to obtain the estimated value of the fault in the system model, and calculate the control parameters of the system based on the estimated value; The combination of the self-resistance of the quadrotor UAV, the external unknown disturbances, and the unknown functions existing in the system model to calculate the total disturbance suffered by the quadrotor UAV includes: Establish the dynamic model of the quadrotor UAV; Based on the dynamic model of the quadrotor UAV, establish the dynamic model of the quadrotor UAV in the form of Lagrangian with multi-source uncertainties; The combination of the self-resistance of the quadrotor UAV, the external unknown disturbances, and the unknown functions existing in the system model to calculate the total disturbance suffered by the quadrotor UAV includes: Establish the dynamic model of the quadrotor UAV; Based on the dynamic model of the quadrotor UAV, establish the dynamic model of the quadrotor UAV in the form of Lagrangian with multi-source uncertainties; The construction of the motion model of the quadrotor UAV according to the actuator fault influence and the total disturbance includes: Establish a multiplicative or additive uncertainty model in the actuator output according to the influence of common actuator faults; Construct the motion model of the quadrotor UAV according to the multiplicative or additive uncertainty model and the total disturbance; The dynamic model of the quadrotor UAV includes: , , , where, is the position quantity of the quadrotor UAV, are the roll angle, pitch angle, and yaw angle of the quadrotor UAV, are the velocity quantities of the quadrotor UAV on the x-axis, y-axis, and z-axis respectively, are the roll angular velocity, pitch angular velocity, and yaw angular velocity of the quadrotor UAV, is the total weight of the quadrotor UAV, is the acceleration due to gravity, is the control quantity of the quadrotor UAV, where is the control quantity of the position loop of the quadrotor UAV, is the control quantity of the attitude loop of the quadrotor UAV, is the inertial moment of the propeller, is the rotational speed of the th propeller, is the resultant force vector relative to the earth-fixed frame, is the velocity vector relative to the earth-fixed frame, is the acceleration vector relative to the earth-fixed frame, is the resultant torque vector, is the angular velocity vector relative to the UAV-fixed coordinate system, is the angular acceleration vector relative to the UAV-fixed coordinate system, is the diagonal inertia matrix; When the axes of the body-fixed frame coincide with the inertial principal axes of the quadrotor UAV, is a static transformation matrix from the quadrotor UAV frame to the earth-fixed frame: , Establish a dynamic transformation matrix through the relationship between Euler angle rate and angular velocity: where: , where, is the transformation matrix, setting the changes in roll angle and pitch angle to be less than the set change threshold so that is close to the identity matrix, using the Euler angle rate instead of the angular velocity, we get: , where, , is the acceleration quantity in the axis direction of the quadrotor UAV, axis direction of the acceleration quantity and axis direction of the acceleration quantity, is the roll angular acceleration, pitch angular acceleration and yaw angular acceleration of the quadrotor UAV; The above-mentioned quadrotor UAV dynamics model based on the multi-source uncertainty Lagrangian form established from the quadrotor UAV dynamics model includes: Express the unknown external disturbance received by the quadrotor UAV system as: , where D1, D2... D6 respectively correspond to the external disturbances of the six system states of the quadrotor UAV; Combining the self-resistance of the quadrotor UAV, the external unknown disturbance D, and the unknown function existing in the system model, the total disturbance received by the quadrotor UAV is expressed as: , where: , Assume that for the total disturbance of the quadrotor, is continuously differentiable, and is bounded, that is , where is a positive constant; Correspondingly, the multiplicative or additive uncertainty model in the actuator output established according to the influence of common actuator faults includes: Establish the following model: , where is the position loop control quantity of the quadrotor UAV excluding the influence of external uncertainties, is the attitude loop control quantity of the quadrotor UAV excluding the influence of external uncertainties, where is the roll angle direction control quantity, is the pitch angle direction control quantity, is the yaw angle direction control quantity, represents the multiplicative loss of the position loop thrust caused by the fault, represents the multiplicative loss of the roll angle direction torque caused by the fault, represents the multiplicative loss of the pitch angle direction torque caused by the fault, represents the multiplicative loss of the yaw angle direction torque caused by the fault, represents the additive parameter of the position loop deviation caused by the fault, is the additive parameter used to represent the pitch angle direction deviation caused by the fault, is the additive parameter used to represent the pitch angle direction deviation caused by the fault, is the additive parameter used to represent the yaw angle direction deviation caused by the fault, and the real-time values of the fault parameters and are unknown, and τ is the attitude loop control quantity; Correspondingly, the motion model of the constructed quadrotor UAV is as follows:

[0007] Furthermore, the process of converting the motion target expectation value into a smooth process and calculating the expectation value of the system includes: According to the expected yaw angle , determine the new x-axis, y-axis and z-axis control inputs; Determine the state space of the quadrotor UAV according to the new x-axis, y-axis and z-axis control inputs, and determine the desired trajectory; Define the desired vector using the desired roll angle, desired pitch angle and desired trajectory; Input the desired vector into the nonlinear tracking differentiator to obtain the smoothed system expected value.

[0008] Furthermore, design a super-twisting extended state observer for observing the unknown disturbances existing in the system, including: Expand the state space expression of the quadrotor UAV system; Use the designed super-twisting extended state observer to adjust the adjustable gain of the extended state observer, obtain the estimated error system of the extended state observer, and calculate the unknown disturbances existing in the observed system.

[0009] Furthermore, use the design of the adaptive rate to obtain the estimated value of the fault in the system model, and calculate the control parameters of the system based on the estimated value, including: Obtain the unknown faults and corresponding parameters in the system from the adaptive law, and according to the position faults and corresponding parameters in the system; use the designed global fast terminal sliding mode surface to design the control quantity to express the control quantity of the position loop of the quadrotor UAV and the control quantity of the attitude loop of the quadrotor UAV.

[0010] Furthermore, according to the desired yaw angle , determine the new x-axis, y-axis and z-axis control inputs, including: According to the received expected value of the yaw angle and the desired target point, respectively define in the quadrotor UAV model axis, axis and axis control quantity as: , According to the characteristics of the control quantity with unknown parameters of the actuator error, respectively define the new axis, axis and axis control input as and , and satisfy the following conditions: , The state space expression of the quadrotor UAV determined according to the new x-axis, y-axis and z-axis control inputs is: , where, , , , , , ; , , , , , The intermediate quantity calculated from the above formula is the system state vector composed of the six-dimensional state of the UAV system is the derivative of the system state vector composed of the six-dimensional state of the UAV system is the derivative of the UAV system state vector is the second derivative of the system state vector composed of the six-dimensional state of the UAV system, expressed as the velocity and angular velocity of the system is the vector converted from the UAV gravity is the vector converted from the actuator fault multiplicative coefficient is the matrix converted from the actuator fault additive coefficient and are the control quantities of the attitude loop of the quadrotor UAV, where is the control quantity in the roll angle direction of the quadrotor UAV is the control quantity in the pitch angle direction is the control quantity in the yaw angle direction; Said determining the state space of the quadrotor UAV and the desired trajectory according to the new x-axis, y-axis and z-axis control inputs includes: Determining the desired roll angle according to the new x-axis, y-axis and z-axis control inputs and the pitch angle , and determining the desired trajectory according to the said desired roll angle and the pitch angle : , Said defining the desired vector by using the desired roll angle, the desired pitch angle and the desired trajectory includes: Generating the desired vector by using the desired trajectory and the desired attitude angle: , Said nonlinear tracking differentiator includes: , wherein, the nonlinear function is defined as follows: , wherein, is the required deflection angle of the tracking signal, is the differential signal of and are respectively the speed factor and the filtering factor of the tracking differentiator, , is a non - linear function of the intermediate parameter, used to calculate the non - linear function.

[0011] Furthermore, the state - space expression of the expanded quadrotor UAV system is: , wherein, , , the super - twisting extended state observer is: ,

[0012] wherein, is the output state of the extended state observer, is the speed observation value of the extended state observer, is the disturbance observation value of the extended state observer, is the adjustable gain of the extended state observer, assuming the estimated error state is and ; The detailed form of the super - twisting algorithm is: , , , , , , Using the designed super - twisting extended state observer, adjusting the adjustable gain of the extended state observer, obtaining the estimated error system of the extended state observer, and calculating the unknown disturbance existing in the observation system, which is realized by the following method: , Correspondingly, the unknown faults and corresponding parameters in the system are obtained from the adaptive law. According to the position faults and corresponding parameters in the system, including: Set , , and are the unknown parameters of the faults in the system , , and Online estimation is designed by the following adaptive law: , where, is a positive constant, is the transpose of the position-loop sliding-mode surface vector, is the transpose of the attitude-loop sliding-mode surface vector; The control quantities of the position loop of the quadrotor UAV and the control quantities of the attitude loop of the quadrotor UAV are designed by using the designed global fast terminal sliding-mode surface, including: The UAV designs the following control quantities: , where, is the control quantity of the position loop of the quadrotor UAV, where is the control quantity in the axis direction of the quadrotor UAV, is for axis direction and is for axis direction; is the control quantity of the attitude loop of the quadrotor UAV, where is the control quantity in the roll angle direction of the quadrotor UAV, is the control quantity in the pitch angle direction and is the control quantity in the yaw angle direction, and are the designed global fast terminal sliding-mode surfaces, where is the sliding-mode surface in the axis direction of the quadrotor UAV, is for axis direction, is for axis direction of the sliding mode surface, is the sliding-mode surface in the roll angle direction of the quadrotor UAV, is the sliding-mode surface in the pitch angle direction and is the sliding-mode surface in the yaw angle direction, and are the position and velocity tracking errors. and are the tracking errors of angular velocity and angular acceleration. Where and are both greater than 0, and are , is a strictly positive constant of the control gain of the controller, , , , , , Among them: , , , , , , , .

[0013] The multi-source uncertainty sliding mode adaptive control method for a quadrotor UAV provided by an embodiment of the present invention combines the self-resistance of the quadrotor UAV, external unknown disturbances, and unknown functions existing in the system model to calculate the total disturbance received by the quadrotor UAV; constructs a motion model of the quadrotor UAV according to the influence of actuator faults and the total disturbance; obtains the expected value of the motion target of the quadrotor UAV; converts the expected value of the motion target into a smoothing process to calculate the expected value of the system; establishes a state space expression of the quadrotor UAV system; designs a super-twisting extended state observer for observing unknown disturbances existing in the system; uses the design of the adaptive rate to obtain an estimated value of the faults in the system model, and calculates the control parameters of the system based on the estimated value. By combining the self-resistance of the quadrotor UAV, external unknown disturbances, and unknown functions existing in the system model, and combining the influence of actuator faults, the motion model of the quadrotor UAV is modified, the control quantity is optimized according to various fault parameter control quantities of the actuator, and the expected attitude angle is determined based on the optimized control quantity. The expected trajectory is determined based on the expected attitude angle, the trajectory vector is defined using the expected trajectory, and the trajectory vector is smoothed; the estimated error system of the extended state observer is obtained using the optimized super-twisting extended state observer, and the fault parameters in the system are designed using the adaptive rate to obtain the control quantity of the quadrotor UAV. An extended state observer and a sliding mode adaptive controller are designed for the characteristics of each type of disturbance, solving the problem of insufficient disturbance rejection. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] By reading the detailed description of the non-limiting embodiments with reference to the following drawings, other features, objects, and advantages of the present invention will become more apparent: Figure 1 is a schematic flow chart of the multi-source uncertainty sliding mode adaptive control method for a quadrotor UAV provided by an embodiment of the present invention; Figure 2It is the quadrotor UAV in the multi-source uncertainty sliding mode adaptive control method for quadrotor UAVs provided by the embodiments of the present invention Axial direction position loop control quantity diagram; Figure 3 It is the quadrotor UAV in the multi-source uncertainty sliding mode adaptive control method for quadrotor UAVs provided by the embodiments of the present invention Axial direction position loop control quantity diagram; Figure 4 It is the quadrotor UAV in the multi-source uncertainty sliding mode adaptive control method for quadrotor UAVs provided by the embodiments of the present invention Axial direction position loop control quantity diagram; Figure 5 It is the attitude loop control quantity diagram of the quadrotor UAV in the rolling angle direction in the multi-source uncertainty sliding mode adaptive control method for quadrotor UAVs provided by the embodiments of the present invention; Figure 6 It is the attitude loop control quantity diagram of the quadrotor UAV in the pitch angle direction in the multi-source uncertainty sliding mode adaptive control method for quadrotor UAVs provided by the embodiments of the present invention; Figure 7 It is the attitude loop control quantity diagram of the quadrotor UAV in the yaw angle direction in the multi-source uncertainty sliding mode adaptive control method for quadrotor UAVs provided by the embodiments of the present invention; Figure 8 It is the position state curve diagram of the quadrotor UAV in the multi-source uncertainty sliding mode adaptive control method for quadrotor UAVs provided by the embodiments of the present invention; Figure 9 It is the angle state curve diagram of the quadrotor UAV in the multi-source uncertainty sliding mode adaptive control method for quadrotor UAVs provided by the embodiments of the present invention. Specific embodiments

[0015] The present invention will be further described in detail below with reference to the drawings and embodiments. It can be understood that the specific embodiments described herein are only used to explain the present invention, rather than limiting the present invention. In addition, it should be noted that for the sake of description, only parts related to the present invention rather than all structures are shown in the drawings.

[0016] Embodiment 1 Figure 1 It is the flow chart of the multi-source uncertainty sliding mode adaptive control method for quadrotor UAVs provided by Embodiment 1 of the present invention. This embodiment is applicable to the situation of multi-source uncertainty sliding mode adaptive control of quadrotor UAVs against various interferences, and specifically includes the following steps: Step 110: Combine the self-resistance of the quadrotor UAV, external unknown disturbances, and the unknown functions existing in the system model to calculate the total disturbance received by the quadrotor UAV, and construct the motion model of the quadrotor UAV according to the actuator fault influence and the total disturbance.

[0017] Exemplarily, it may include: establishing the dynamic model of the quadrotor UAV; establishing the dynamic model of the quadrotor UAV in the Lagrangian form with multi-source uncertainties based on the dynamic model of the quadrotor UAV.

[0018] First, establish the dynamic model of the quadrotor UAV: , , , wherein, is the position quantity of the quadrotor UAV, are the roll angle, pitch angle, and yaw angle of the quadrotor UAV, are the velocity quantities of the quadrotor UAV on the x-axis, y-axis, and z-axis respectively, are the roll angular velocity, pitch angular velocity, and yaw angular velocity of the quadrotor UAV, is the total weight of the quadrotor UAV, is the gravitational acceleration, is the position loop control quantity of the quadrotor UAV, are the roll angle control quantity, pitch angle control quantity, and yaw angle control quantity of the quadrotor UAV, is the inertia moment of the propeller, is the rotational speed of the th propeller, is the resultant force vector relative to the earth-fixed frame, where is the resultant force vector in the axis direction relative to the earth-fixed frame, is the resultant force vector in the axis direction relative to the earth-fixed frame,

[0019] is the velocity vector relative to the earth-fixed frame, is the acceleration vector relative to the earth-fixed frame, is the resultant torque vector, where is the torque vector in the roll angle direction, is the torque vector in the pitch angle direction, is the torque vector in the yaw angle direction, is the angular velocity vector with respect to the fixed coordinate system of the UAV, is the roll angular velocity vector with respect to the fixed coordinate system of the UAV, is the pitch angular velocity vector with respect to the fixed coordinate system of the UAV, is the yaw angular velocity vector with respect to the fixed coordinate system of the UAV, is the angular acceleration vector with respect to the fixed coordinate system of the UAV, is the diagonal inertia matrix, where is the moment of inertia in the roll angle direction, is the moment of inertia in the pitch angle direction, is the moment of inertia in the yaw angle direction. In the embodiments of the present invention, represents the derivative of, for example, is the derivative of. Assuming that the axis of the body-fixed frame coincides with the inertial principal axis of the quadrotor UAV, is a static transformation matrix from the quadrotor UAV frame to the Earth-fixed frame, and is specifically defined as follows: , obtain the dynamic transformation matrix for the relationship between the Euler angle rate and the angular velocity: wherein, .

[0020] Generally, for the convenience of controller design, the changes in the roll angle and the pitch angle are very small. It is set that the changes in the roll angle and the pitch angle are less than the set change threshold. Therefore, is close to the identity matrix. The angular velocity can be replaced by the Euler angle rate. Accordingly, substituting the dynamic transformation matrix for the relationship between the Euler angle rate and the angular velocity into the quadrotor UAV dynamics model, the following results are obtained: , wherein, is the acceleration quantity in the axis direction of the quadrotor UAV, axis direction of the acceleration quantity and axis direction of the acceleration quantity, is the roll angular acceleration, pitch angular acceleration and yaw angular acceleration of the quadrotor UAV.

[0021] Correspondingly, the motion model of the quadrotor UAV constructed according to the actuator fault influence and the total disturbance may include: establishing a multiplicative or additive uncertainty model in the actuator output according to the influence of common actuator faults; determining the constraint conditions of the control quantity according to the extreme cases of the faults; constructing the motion model of the quadrotor UAV according to the multiplicative or additive uncertainty model and the total disturbance.

[0022] First, the unknown external disturbances acting on the quadrotor UAV system can be expressed as: , where D1, D2... D6 respectively correspond to the external disturbances of the six system states of the quadrotor UAV.

[0023] Combining the self-resistance of the quadrotor UAV, the external unknown disturbance D, and the unknown functions existing in the system model, the total disturbance acting on the quadrotor UAV is obtained and expressed as: , where: .

[0024] Regarding the total disturbance of the quadrotor, is continuously differentiable, and is bounded, that is , where is a positive constant, is the total disturbance acting on the quadrotor UAV in the axis direction, is the total disturbance acting on the quadrotor UAV in the axis direction, is the total disturbance acting on the quadrotor UAV in the axis direction, is the total disturbance acting on the quadrotor UAV in the roll angle direction, is the total disturbance acting on the quadrotor UAV in the pitch angle direction, is the total disturbance acting on the quadrotor UAV in the yaw angle direction.

[0025] As the actuator of the quadrotor control system, the rotor has the possibility of faults such as too low power supply voltage or damaged propeller blades. The influence of common actuator faults can be modeled as multiplicative or additive uncertainties in the actuator output, as follows: , where is the position loop control quantity of the quadrotor UAV excluding the influence of external uncertainties and is the attitude loop control quantity of the quadrotor UAV excluding the influence of external uncertainties, where is the control quantity in the roll angle direction, is the control quantity in the pitch angle direction, is the control quantity in the yaw angle direction, represents the multiplicative loss of the position loop thrust caused by the fault, represents the multiplicative loss of the torque in the roll angle direction caused by the fault, represents the multiplicative loss of the torque in the pitch angle direction caused by the fault, represents the multiplicative loss of the torque in the yaw angle direction caused by the fault, Additive parameter representing the position loop deviation caused by a fault is an additive parameter used to represent the deviation in the pitch angle direction caused by a fault is an additive parameter used to represent the deviation in the pitch angle direction caused by a fault is an additive parameter used to represent the deviation in the yaw angle direction caused by a fault. Since there is no fault detection or identification device in the flight control system, the fault parameters and The real-time values are unknown

[0026] Based on the above content, the quadrotor UAV model can be rewritten as: ,

[0027] Using the above steps, the motion model of the quadrotor UAV can be obtained

[0028] Step 120, obtain the expected value of the motion target of the quadrotor UAV, transform the expected value of the motion target into a smoothing process, and calculate the expected value of the system

[0029] Exemplarily, it may include: transforming the expected value of the motion target into a smoothing process and calculating the expected value of the system, including: According to the expected roll angle , determine the new control inputs for the x-axis, y-axis, and z-axis; determine the state space expression of the quadrotor UAV according to the new control inputs for the x-axis, y-axis, and z-axis, and determine the expected trajectory; define the expected vector using the expected roll angle, expected pitch angle, and expected trajectory; input the expected vector into the nonlinear tracking differentiator to obtain the smoothed expected value of the system

[0030] Receive the expected value of the motion target of the quadrotor UAV, that is The expected value of the target in the axis direction The expected value of the target in the axis direction The expected value of the target in the axis direction and the expected value of the yaw angle axis, axis and axis control amounts in the model are respectively defined as , as follows: , Due to the faults in the actuators of the system, considering the control amounts with unknown parameters, define the new axis, axis and axis control inputs as and , respectively satisfy: , According to the above control quantities, the state - space expression of the quad - rotor UAV can be rewritten as: ; Where: , ; , , , ; , ; ; ; , The intermediate quantity calculated from the above formula, is the system - state vector composed of the six - dimensional states of the UAV system, is the derivative of the UAV system - state vector, representing the velocity and angular velocity of the system, is the vector converted from the UAV gravity, is the vector converted from the actuator - fault multiplicative coefficient, is the matrix converted from the actuator - fault additive coefficient.

[0031] According to the new axis, axis and axis control inputs and , the desired position of the quad - rotor UAV and the desired angles at each position can be obtained, and the motion trajectory, that is, the desired orbit, can be obtained.

[0032] ,

[0033] According to the desired roll angle and the desired pitch angle , the control input can be defined as: .

[0034] Define the desired orbit and the desired attitude angles as a new vector as: , The nonlinear tracking differentiator is as follows: , Where the nonlinear function is defined as follows: , Among them, is the required deflection angle of the tracking signal, is the differential signal of and are respectively the speed factor and the filtering factor of the tracking differentiator, , is the intermediate parameter of the non - linear function for calculating the non - linear function. Since the control space is 6 - dimensional, all subscripts in the above formula are , for example .

[0035] The above non - linear tracking differentiator obtains the differential signal of the state value through the input state value of the quadrotor UAV. Using the above non - linear function, the expected value can be transformed into a smooth process to avoid overshoot phenomenon during system tracking.

[0036] Step 130, design a super - twisting extended state observer for observing the total disturbance existing in the system.

[0037] Although various disturbances inside and outside the UAV system are given in the previous steps, there are still some unknown disturbances. Therefore, it is necessary to add the position disturbance existing in the system.

[0038] In this embodiment, it may include: expanding the state - space expression of the quadrotor UAV system; using the designed super - twisting extended state observer, adjusting the adjustable gain of the extended state observer, obtaining the estimated error system of the extended state observer, and calculating the unknown disturbance existing in the observed system.

[0039] First, expand the state - space expression of the quadrotor UAV system: , Among them, ,, .

[0040] The set super - twisting extended state observer is as follows: ,

[0041] Among them, is the output state of the extended state observer, is the speed observation value of the extended state observer, is the disturbance observation value of the extended state observer, is the adjustable gain of the extended state observer. Assuming the estimated error state is and , The following is the detailed form: ,

[0042] , Using the state - space expression of the above - expanded quadrotor UAV system and the super - twisting extended state observer, the estimated error system of the extended state observer can be obtained: ,

[0043] where, , , 。The existing unknown disturbances can be obtained by the above method.

[0044] Step 140, using the design of the adaptation rate, obtain the estimated value of the fault in the system model, and calculate the control parameters of the system based on the estimated value.

[0045] Exemplarily, it may include: obtaining the unknown fault and the corresponding parameters in the system by the adaptation law, and according to the position fault and the corresponding parameters in the system: using the designed global fast terminal sliding mode surface to design the control quantity to represent the control quantity of the position loop of the quadrotor UAV and the control quantity of the attitude loop of the quadrotor UAV.

[0046] Exemplarily, design the following control quantity for the UAV: , where, is the control quantity of the position loop of the quadrotor UAV, where is the control quantity of the quadrotor UAV axis direction, is axis direction control quantity and is axis direction control quantity, is the control quantity of the attitude loop of the quadrotor UAV, where is the control quantity of the roll angle direction of the quadrotor UAV, is the control quantity of the pitch angle direction, is the control quantity of the yaw angle direction, and are the designed global fast terminal sliding mode surfaces, where is the sliding mode surface of the quadrotor UAV axis direction, is axis direction sliding mode surface, is The sliding surface in the axial direction is the sliding mode surface in the roll angle direction of the quadrotor UAV, is the sliding mode surface in the pitch angle direction, and is the sliding mode surface in the yaw angle direction, and are the position and velocity tracking errors. and are the tracking errors of the angular velocity and angular acceleration. Among them, and are both greater than 0, and are positive odd numbers, and , and are , is the control gain of the controller, which is a strictly positive constant, , , , . Figure 2 is the control quantity diagram of the position loop in the axial direction of the quadrotor UAV in the multi-source uncertainty sliding mode adaptive control method for quadrotor UAVs provided by the embodiments of the present invention; Figure 3 is the control quantity diagram of the position loop in the axial direction of the quadrotor UAV in the multi-source uncertainty sliding mode adaptive control method for quadrotor UAVs provided by the embodiments of the present invention; Figure 4 is the control quantity diagram of the position loop in the axial direction of the quadrotor UAV in the multi-source uncertainty sliding mode adaptive control method for quadrotor UAVs provided by the embodiments of the present invention; Figure 5 is the control quantity diagram of the attitude loop in the roll angle direction of the quadrotor UAV in the multi-source uncertainty sliding mode adaptive control method for quadrotor UAVs provided by the embodiments of the present invention; Figure 6 is the control quantity diagram of the attitude loop in the pitch angle direction of the quadrotor UAV in the multi-source uncertainty sliding mode adaptive control method for quadrotor UAVs provided by the embodiments of the present invention; Figure 7 is the control quantity diagram of the attitude loop in the yaw angle direction of the quadrotor UAV in the multi-source uncertainty sliding mode adaptive control method for quadrotor UAVs provided by the embodiments of the present invention. It can be seen from Figures 2 - 7 the control quantities of the position loop and attitude loop of the quadrotor UAV changing with time. In the tracking control of the quadrotor UAV, by designing an appropriate sliding mode surface, the system can be made stable.

[0047] , where: , ; , ; , , , 。

[0048] Among them, 、 、 and are unknown parameters of system internal faults 、 、 and for online estimation, designed by the following adaptation law: , Among them, is a positive constant, is the transpose of the position loop sliding mode surface vector, is the transpose of the attitude loop sliding mode surface vector.

[0049] Using the above method, the control quantities and of the system can be calculated. Using the calculated control quantities, smooth adaptive stable control can be achieved when the quadrotor UAV is under multi-source uncertainty factors.

[0050] The multi-source uncertainty sliding mode adaptive control method for a quadrotor UAV provided by the embodiment of the present invention combines the self-resistance of the quadrotor UAV, external unknown disturbances, and unknown functions existing in the system model to calculate the total disturbance received by the quadrotor UAV; constructs the motion model of the quadrotor UAV according to the actuator fault influence and the total disturbance; obtains the expected value of the motion target of the quadrotor UAV; converts the motion target expected value into a smoothing process to calculate the expected value of the system; establishes the state space expression of the quadrotor UAV system; designs a super-twisting extended state observer for observing the unknown disturbances existing in the system; uses the design of the adaptive rate to obtain the estimated value of the faults in the system model, and calculates the control parameters of the system based on the estimated value. By combining the self-resistance of the quadrotor UAV, external unknown disturbances, and unknown functions existing in the system model, and combining the actuator fault influence to modify the motion model of the quadrotor UAV, and optimizing the control quantity according to various fault parameter control quantities of the actuator, and determining the expected attitude angle based on the optimized control quantity, determining the expected trajectory based on the expected attitude angle, defining the trajectory vector using the expected trajectory, and smoothing the trajectory vector; obtaining the estimated error system of the extended state observer using the optimized super-twisting extended state observer, and designing the fault parameters in the system using the adaptive rate to obtain the control quantity of the quadrotor UAV. An extended state observer and a sliding mode adaptive controller are designed according to the characteristics of the unknown disturbances, solving the problem of insufficient disturbance rejection.

[0051] Figure 8 It is the position state curve graph of the quadrotor UAV adopting the multi-source uncertainty sliding mode adaptive control method for the quadrotor UAV provided by the embodiment of the present invention; Figure 9 It is the angle state curve graph of the quadrotor UAV adopting the multi-source uncertainty sliding mode adaptive control method for the quadrotor UAV provided by the embodiment of the present invention. It can be seen that when adopting the multi-source uncertainty sliding mode adaptive control method for the quadrotor UAV provided by the embodiment of the present invention, the state of the UAV can converge smoothly within a finite time.

[0052] Note that the above is only the preferred embodiment of the present invention and the technical principles applied. Those skilled in the art will understand that the present invention is not limited to the specific embodiments described herein. Various obvious changes, re-adjustments, and substitutions can be made by those skilled in the art without departing from the protection scope of the present invention. Therefore, although the present invention has been described in detail through the above embodiments, the present invention is not limited to the above embodiments. Without departing from the concept of the present invention, more other equivalent embodiments can be included, and the scope of the present invention is determined by the scope of the appended claims.

Claims

1. A multi-source uncertainty sliding mode adaptive control method for a quadrotor UAV, characterized in that Including: Combining the self-resistance of the quadrotor UAV, external unknown disturbances, and unknown functions existing in the system model, calculating the total disturbance received by the quadrotor UAV, and constructing the motion model of the quadrotor UAV according to the actuator fault influence and the total disturbance; Obtaining the expected value of the motion target of the quadrotor UAV; Converting the expected value of the motion target into a smoothing process and calculating the expected value of the system; Establishing the state-space expression of the quadrotor UAV system; Designing a super-twisting extended state observer for observing unknown disturbances existing in the system; Using the design of the adaptive rate to obtain the estimated value of the fault in the system model, and calculating the control parameters of the system based on the estimated value; The combining the self-resistance of the quadrotor UAV, external unknown disturbances, and unknown functions existing in the system model, calculating the total disturbance received by the quadrotor UAV, includes: Establishing the dynamic model of the quadrotor UAV; Based on the dynamic model of the quadrotor UAV, establishing the dynamic model of the quadrotor UAV in the form of multi-source uncertainty Lagrangian; The constructing the motion model of the quadrotor UAV according to the actuator fault influence and the total disturbance, includes: Establishing a multiplication or addition uncertainty model in the actuator output according to the influence of common actuator faults; Constructing the motion model of the quadrotor UAV according to the multiplication or addition uncertainty model and the total disturbance; The dynamic model of the quadrotor UAV includes: ， ， ， Among them, is the position quantity of the quadrotor UAV, are the roll angle, pitch angle and yaw angle of the quadrotor UAV, are the velocity quantities of the quadrotor UAV along the x-axis, y-axis and z-axis respectively, are the roll angular velocity, pitch angular velocity and yaw angular velocity of the quadrotor UAV, is the total weight of the quadrotor UAV, is the gravitational acceleration, is the control quantity of the quadrotor UAV, where is the position loop control quantity of the quadrotor UAV, is the attitude loop control quantity of the quadrotor UAV, is the inertial moment of the propeller, is the rotation speed of the th propeller, is the resultant force vector relative to the earth-fixed frame, is the velocity vector relative to the earth-fixed frame, is the acceleration vector relative to the earth-fixed frame, is the resultant torque vector, is the angular velocity vector relative to the UAV-fixed coordinate system, is the angular acceleration vector relative to the UAV-fixed coordinate system, is the diagonal inertia matrix; When the axis of the fuselage fixed frame coincides with the inertial principal axis of the quadrotor UAV, is a static transformation matrix from the quadrotor UAV frame to the Earth fixed frame: ， Establishing a dynamic transformation matrix through the relationship between the Euler angle rate and the angular velocity: , wherein: ， Among them, is a transformation matrix. The changes in the roll angle and pitch angle are set to be less than a set change threshold so that is close to the identity matrix. Using the Euler angle rate to replace the angular velocity, we get: ， Among them, , is the acceleration quantity in the axis direction of the quadrotor UAV, the acceleration quantity in the axis direction, and is the roll angular acceleration, pitch angular acceleration and yaw angular acceleration of the quadrotor UAV; The establishing the dynamic model of the quadrotor UAV in the form of multi-source uncertainty Lagrangian based on the dynamic model of the quadrotor UAV, includes: Express the unknown external disturbances acting on the quadrotor UAV system as: , where D1, D2,..., D6 respectively correspond to the external disturbances of the six system states of the quadrotor UAV; Combining the self-resistance of the quadrotor UAV, the external unknown disturbance D, and the unknown functions existing in the system model, the total disturbance received by the quadrotor UAV is expressed as: , where: ， Assumption: For the total disturbance of the quadrotor, is continuously differentiable and is bounded, i.e., , where is a positive constant; Correspondingly, the establishing a multiplication or addition uncertainty model in the actuator output according to the influence of common actuator faults, includes: Establishing the following model: ， Among them is the position loop control quantity of the quadrotor UAV under the exclusion of external uncertainties, is the attitude loop control quantity of the quadrotor UAV under the exclusion of external uncertainties. Among them, is the control quantity in the roll angle direction, is the control quantity in the pitch angle direction, is the control quantity in the yaw angle direction, represents the multiplicative loss of the position loop thrust caused by the fault, represents the multiplicative loss of the torque in the roll angle direction caused by the fault, represents the multiplicative loss of the torque in the pitch angle direction caused by the fault, represents the multiplicative loss of the torque in the yaw angle direction, represents the additive parameter of the position loop deviation caused by the fault, is the additive parameter used to represent the pitch angle direction deviation caused by the fault, is the additive parameter used to represent the pitch angle direction deviation caused by the fault, is the additive parameter used to represent the yaw angle direction deviation caused by the fault. The fault parameters and The real-time values of are unknown, and τ is the attitude loop control quantity; Correspondingly, the constructed motion model of the quadrotor UAV is as follows: 。 2. The method according to claim 1, wherein The converting the expected value of the motion target into a smoothing process and calculating the expected value of the system, includes: Based on the desired yaw angle , determine the new x-axis, y-axis, and z-axis control inputs; Determining the state space of the quadrotor UAV according to the new x-axis, y-axis, and z-axis control inputs, and determining the expected trajectory; Defining the expected vector using the expected roll angle, expected pitch angle, and expected trajectory; Inputting the expected vector into the nonlinear tracking differentiator to obtain the smoothed expected value of the system.

3. According to the method described in claim 2, the designing a super-twisting extended state observer for observing unknown disturbances existing in the system, includes: Expanding the state-space expression of the quadrotor UAV system; Using the designed super-twisting extended state observer to adjust the adjustable gain of the extended state observer, obtaining the estimated error system of the extended state observer, and calculating the unknown disturbances existing in the observed system.

4. The method according to claim 3, wherein The using the design of the adaptive rate to obtain the estimated value of the fault in the system model, and calculating the control parameters of the system based on the estimated value, includes: Obtaining the unknown faults and corresponding parameters in the system by the adaptive law, and according to the position faults and corresponding parameters in the system; using the designed global fast terminal sliding mode surface to design the control quantity to express the control quantity of the position loop of the quadrotor UAV and the control quantity of the attitude loop of the quadrotor UAV.

5. The method according to claim 4, wherein According to the desired yaw angle , determining new x-axis, y-axis, and z-axis control inputs, including: According to the target expected value of the received yaw angle , respectively define in the quadrotor UAV model axis, axis and axis control quantity as follows: ， According to the characteristics of the control quantity with unknown parameters due to actuator errors, new axis, axis and axis control quantity inputs are respectively and , and satisfy the following conditions: ， The state - space expression of the quad - rotor UAV is determined according to the control inputs of the new x - axis, y - axis, and z - axis as follows: ， Among them, , , ， ， ， ， ， ， ， ， , The intermediate quantity calculated from the above formula; is the system state vector composed of the six-dimensional states of the UAV system, is the derivative of the system state vector composed of the six-dimensional states of the UAV system, is the derivative of the UAV system state vector, is the second derivative of the system state vector composed of the six-dimensional states of the UAV system, expressed as the velocity and angular velocity of the system, is the vector converted from the gravity of the UAV, is the vector converted from the multiplicative coefficient of the actuator fault, is the matrix converted from the additive coefficient of the actuator fault; Determining the state - space of the quad - rotor UAV according to the control inputs of the new x - axis, y - axis, and z - axis and determining the desired trajectory includes: Determine the desired roll angle according to the new x-axis, y-axis, and z-axis control inputs and pitch angle , and determine the desired trajectory according to the desired roll angle and pitch angle : ， Defining the desired vector using the desired roll angle, desired pitch angle, and desired trajectory includes: Generating the desired vector using the desired trajectory and desired attitude angles: ， The non - linear tracking differentiator includes: ， Among them, the non-linear function is defined as follows: ， Among them, is the required deflection angle of the tracking signal, is the differential signal of and are respectively the speed factor and the filtering factor of the tracking differentiator, , is the intermediate parameter of the non-linear function for calculating the non-linear function.

6. The method according to claim 5, characterized in that The state - space expression of the expanded quad - rotor UAV system is: ， Among them, , , The super - twisting extended state observer is: ， Among them, is the output state of the extended state observer, is the speed observation value of the extended state observer, is the disturbance observation value of the extended state observer, is the adjustable gain of the extended state observer. Assume the estimated error state is and . The detailed form of the super - twisting algorithm is: ， ， Using the designed super - twisting extended state observer, adjusting the adjustable gain of the extended state observer to obtain the estimated error system of the extended state observer, and calculating the unknown disturbance existing in the observation system is achieved in the following way: ， Correspondingly, obtaining the unknown faults and corresponding parameters in the system from the adaptive law, according to the position faults and corresponding parameters in the system, includes: Settings , , and are unknown parameters of system internal faults , , and for online estimation, designed by the following adaptation law: ， Among them, is a positive constant, is the transpose of the position-loop sliding-mode surface vector, is the transpose of the attitude-loop sliding-mode surface vector; Using the designed global fast terminal sliding mode surface to design the control quantity to represent the control quantity of the position loop of the quad - rotor UAV and the control quantity of the attitude loop of the quad - rotor UAV includes: The UAV designs the following control quantity: ， Among them, is the control quantity of the position loop of the quadrotor UAV, where is the control quantity of the quadrotor UAV in the axis direction, is the control quantity in the axis direction and is the control quantity in the is the control quantity of the attitude loop of the quadrotor UAV, where is the control quantity in the roll angle direction of the quadrotor UAV, is the control quantity in the pitch angle direction and is the control quantity in the yaw angle direction, and are the designed global fast terminal sliding mode surfaces, where is the sliding mode surface of the quadrotor UAV in the axis direction, is the sliding mode surface in the axis direction, is the sliding mode surface in the axis direction of the quadrotor UAV, is the sliding mode surface in the pitch angle direction, is the sliding mode surface in the yaw angle direction, and are the position and velocity tracking errors, and are the tracking errors of angular velocity and angular acceleration, where and are both greater than 0, and are , is a strictly positive constant of the control gain of the controller, , , , , ， Where: ， ， ， ， ， ， ， 。

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