A Formation Cooperative Maneuvering Control Method for Quadrotor UAVs

Abstract

The present invention relates to a cooperative maneuver control method for a quadrotor UAV formation, which includes establishing an endogenous conversion relationship from a flat space trajectory to all states of the system according to the nonlinear model of the quadrotor UAV; introducing a variable scaling coefficient and establishing cooperative maneuver constraints to generate a single-vehicle trajectory solution model; modeling the quadrotor formation maneuver constraints according to waypoints and maneuver requirements, which are characterized as parametric linear equality / inequality constraints of the virtual centroid trajectory and the variable scaling coefficient, and using the minimization of the second derivative of acceleration as the optimization index to transform it into a quadratic programming problem; giving the analytical forms of the trajectories, attitudes and their derivative reference signals of each single vehicle for generating the motor control commands of the single vehicle to complete the cooperative maneuver control of the quadrotor UAV formation. This method can make the behavior of the quadrotor UAV formation approximate to a six-degree-of-freedom rigid body that can be scaled as a whole, can achieve consistent behavior at the attitude level transiently, and has the characteristics of high formation control accuracy, low computing power requirement and easy deployment.

Description

Technical Field

[0001] The present invention belongs to the technical field of unmanned aerial vehicle control, and particularly relates to a cooperative maneuver control method for a quadrotor UAV formation. Background Art

[0002] Due to characteristics such as low cost, vertical takeoff and landing, small size and flexibility, quadrotor UAVs have been widely applied to fields such as aerial photography, transportation, agriculture, and inspection. In recent years, with the development of technologies such as automation and artificial intelligence, the scenario of quadrotor UAV formation has gradually attracted the common attention of the academic and industrial circles. Formation can give play to the collaborative advantages and greatly broaden the application scope of quadrotor UAVs. For example, it can enhance the transportation capacity, improve the search efficiency, and improve the performance viewing experience. However, the formation flight of UAVs brings many new problems compared with the single UAV scenario. On the one hand, traditional UAV trajectory planning methods are difficult to be directly extended to the multi-UAV task scenario. It is necessary to not only consider the challenges brought by the environment and task requirements to trajectory generation, but also consider how to coordinately plan the trajectories of each single UAV while avoiding inter-UAV collisions. On the other hand, formation flight also poses new technical challenges, including problems such as the system architecture arrangement of multiple UAVs and trajectory consistency. Therefore, it is very important for the development of the UAV industry to design a new cooperative maneuver control method for quadrotor UAV formation, and it has broad application prospects.

[0003] Currently, the research on quadrotor UAV formation control mainly focuses on the realization level of the absolute spatial position consistency of the formation, and there is less research on the coordinated maneuver problem of quadrotor UAV formation. The literature "High-Order Consensus Formation Control Method for Quadrotor UAVs" simplifies the nonlinear mathematical model of quadrotor UAVs into two fourth-order linear subsystems and two second-order linear subsystems, uses the position deviation matrix to describe the formation shape, and designs a high-order consensus formation control algorithm for the linear model, which can realize the aggregation and maintenance of the formation. Chinese invention patent CN201810980595.X proposes a quadrotor UAV swarm control method based on the artificial potential field method, uses the velocity control function to perform the motion control of a single UAV, and can realize the formation moving towards the target and obstacle avoidance. Chinese invention patent CN202011509312.7 designs a hierarchical control framework, uses the consensus theory to generate virtual positions and velocities, and designs a PID control law in the tracking control layer to track the virtual positions and velocities. The above three methods can all realize the basic functions of the formation, but generally there are three deficiencies: First, the control methods designed based on the linear system model do not describe the kinematic and dynamic characteristics of the system sufficiently and cannot fully consider the system constraints; second, they only realize the formation behavior at the absolute spatial position level and cannot achieve the formation behavior at the attitude level; third, they cannot generate smooth high-order derivative signals of the single-UAV trajectory, which is not conducive to the design of the tracking controller and affects the formation accuracy.

[0004] In summary, the existing methods are difficult to be applied to the fast formation maneuver scenarios of quadrotor UAVs. They lack a complete mathematical description of the formation behavior and are not conducive to the realization of single-vehicle tracking control. Therefore, it is urgent to overcome the cooperative maneuver control method of quadrotor UAVs. Summary of the Invention

[0005] Aiming at the problems of formation mathematical model representation, high-order derivative continuity of trajectories, and single-vehicle trajectory solution during the formation flight of quadrotor UAVs, in order to overcome the deficiencies of the existing technologies, the present invention provides a cooperative maneuver control method for quadrotor UAV formations, which realizes the formation behavior of quadrotor UAVs similar to a six-degree-of-freedom rigid body that can be scaled as a whole. It can achieve consistent behavior at the attitude level instantaneously and ensure the continuity of high-order derivatives of each single-vehicle trajectory at the same time.

[0006] To achieve the above object, the technical solution adopted by the present invention is as follows:

[0007] A cooperative maneuver control method for quadrotor UAV formations includes the following steps:

[0008] In the first step, based on the differential flatness theory according to the dynamic model of quadrotor UAVs, an endogenous conversion relationship from the single-vehicle trajectory to the system state is established.

[0009] In the second step, based on the virtual rigid body, a variable scaling coefficient is introduced to represent the spatial configuration of the formation, and a cooperative maneuver constraint is introduced to generate a single-vehicle trajectory solution model.

[0010] In the third step, the formation maneuver actions are designed, modeled as parametric constraints of the centroid trajectory and the scaling coefficient of the virtual rigid body, and the minimization of the second derivative of acceleration is used as the optimization index, which is transformed into a quadratic programming problem for solution.

[0011] In the fourth step, according to the endogenous conversion relationship and the single-vehicle trajectory mapping, the reference signals of the trajectories, attitudes, and their derivatives of each single-vehicle are given to generate the motor control commands of the single-vehicle.

[0012] Furthermore, the attitude of the quadrotor UAV is represented by Euler angles, and the corresponding rotation matrix R is defined as:

[0013]

[0014] In the above formula, φ, θ, ψ are the Euler angles from the body coordinate system to the inertial coordinate system, corresponding to the roll angle, yaw angle, and pitch angle respectively;

[0015] The nonlinear dynamic model of the quadrotor UAV is established as follows:

[0016]

[0017] In the above equation, the superscript represents the coordinate system corresponding to the vector, where B represents the body frame of the quadrotor UAV, E represents the inertial coordinate system (using the Earth coordinate system); G E = [0 0 mg] T represents gravity, F E = R[0 0 f] T represents the total lift force in the inertial frame,

[0018]

[0019] represents the projection relationship between the angular velocity measurement value in the body axis system and the Euler angle derivative, where:

[0020]

[0021] According to the differential flatness theory, we can obtain:

[0022]

[0023] where, represents the second-order time derivative of the UAV's position, and are obtained from the following equation:

[0024]

[0025] where,

[0026] Combined with the definition of the rotation matrix, the corresponding pitch and roll angles are solved from R;

[0027] Let ω B = [p q r] T , according to the differential flatness property, we can obtain:

[0028]

[0029]

[0030] where:

[0031]

[0032]

[0033] In the above equation, f is the magnitude of the UAV's lift force vector, represents the first-order and second-order time derivatives of the UAV's acceleration;

[0034] Select the flat output as σ = [x y z ψ] T, where x, y, and z are the positions of the UAV, and ψ is the yaw angle of the UAV. Thus, the reference signals of all states of the corresponding quadrotor UAV, including positions, attitudes, and their derivatives, can be obtained from the trajectory of the flat output space and its derivatives of each order. This process is called endogenous conversion.

[0035] Further, in the second step, the trajectory P of the i-th UAV in the formation r i is expressed as:

[0036]

[0037] where P v is the trajectory of the virtual centroid of the formation, α is a variable scaling coefficient, R v is the rotation matrix of the overall attitude of the formation, and r i is the position vector of the i-th UAV relative to the center of the formation, which is determined by the specified formation shape;

[0038] The cooperative maneuver constraint is introduced as:

[0039]

[0040] where Φ represents the endogenous conversion relationship established in the first step, represents the second-order time derivative of the trajectory of the virtual centroid of the formation, and ψ v represents the yaw angle of the overall formation; this constraint realizes the cooperative maneuver behavior of the quadrotor UAV formation, that is, the formation behavior is similar to a six-degree-of-freedom rigid body that can be scaled as a whole.

[0041] Further, in the third step, the generation process of the trajectory of the virtual centroid of the formation and the scaling coefficient is as follows:

[0042] First, the trajectory P v (t) and the time-varying scaling coefficient α(t) in the three-dimensional space are regarded as four independent dimensions. For any dimension, piecewise polynomials are used for description, and the waypoints that must be passed are used as nodes for segmentation. The time functions of each dimension are expressed as polynomials:

[0043]

[0044] where k is the number of segments of the trajectory, and p i is the parameter vector c of the i-th short trajectory;

[0045] The equality / inequality constraints on the position, velocity, and acceleration of the waypoints required by the formation are converted into linear equalities / inequalities about p; the continuity requirements at the nodes are also expressed by linear equalities about p; for the scaling coefficient, corresponding values are specified at different nodes to control the smooth dispersion or contraction of the formation;

[0046] The acceleration of each single aircraft can be obtained by performing chain differentiation on the single-aircraft trajectory solution model established in the second step as follows:

[0047]

[0048] Among them, is the second-order time derivative of the position of the i-th unmanned aircraft, and are the first-order and second-order time derivatives of the variable scaling coefficient, and are the first-order and second-order time derivatives of the virtual rigid body rotation matrix.

[0049] According to the endogenous conversion relationship in the first step, at time t w , the attitude reference value corresponding to the single unmanned aircraft is determined by ; the following transient constraints are introduced:

[0050]

[0051] Among them, represents the fourth-order derivative of the virtual center-of-mass position trajectory.

[0052] The above equation realizes that at any specified time t w , the attitudes of all unmanned aircraft are kept consistent and the same as the overall attitude of the formation;

[0053] All the above constraints are written in the following form:

[0054]

[0055] Among them, A and A l are constant matrices determined by the node time, and b and b l are constant vectors set according to the system constraints. Finally, a quadratic programming problem composed of the second-order derivative optimal index of the acceleration and linear equalities / inequalities is solved by means of a common quadratic programming solver.

[0056] Furthermore, the solution process of the state reference signal of the i-th single aircraft is as follows:

[0057]

[0058] Among them, and are both obtained in an analytical form through the chain differentiation rule, and the reference signals of all Euler angles, angular velocities, rotation matrices and their derivatives are obtained through the endogenous conversion relationship established in the first step.

[0059] The advantages of the present invention compared with the prior art are as follows:

[0060] In the present invention, a non-linear dynamic model of a quadrotor UAV is used, which makes the consideration of system dynamic characteristics and constraints closer to engineering practice. By introducing cooperative maneuver constraints, transient attitude constraints, etc., formation behavior at the attitude level is achieved, and the high-order derivatives of the generated formation trajectory are continuous, which is more conducive to the tracking control design of individual UAVs and can significantly improve the formation maneuverability and formation-keeping accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] Figure 1 It is a flowchart of a cooperative maneuver control method for a quadrotor UAV formation according to the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0062] In order to make the objectives, technical solutions and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention. In addition, the technical features involved in the various embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other.

[0063] A cooperative maneuver control method for a quadrotor UAV formation according to the present invention establishes an endogenous conversion relationship through a non-linear model of the quadrotor UAV. Based on a virtual rigid body, a scaling coefficient and cooperative maneuver constraints are introduced to establish a trajectory model of a single UAV. Taking the minimization of the second derivative of acceleration as an optimization index and considering the parametric equality / inequality constraints at each node, the trajectory planning of the virtual centroid is realized, and then all state reference signals of the single UAV are solved, and finally the cooperative maneuver control of the formation is completed. As Figure 1 shown, the specific implementation steps are as follows:

[0064] First step, according to the dynamic model of the quadrotor UAV, based on the differential flatness theory, an endogenous conversion relationship from the trajectory of a single UAV to the system state is established.

[0065] The attitude of the quadrotor UAV is represented by Euler angles, and the corresponding rotation matrix R is defined as:

[0066]

[0067] In the above formula, φ, θ, ψ are the Euler angles from the body coordinate system to the inertial coordinate system, corresponding to the roll angle, yaw angle and pitch angle respectively;

[0068] The non-linear dynamic model of the quadrotor UAV is established as follows:

[0069]

[0070] In the above formula, the superscript on the right represents the coordinate system corresponding to the vector, where B represents the body coordinate system of the quadrotor UAV, and E represents the inertial coordinate system (the earth coordinate system is used here). GE = [0 0 mg] T represents gravity, F E = R[0 0 f] T represents the total lift force in the inertial frame,

[0071]

[0072] represents the projection relationship between the angular velocity measurement in the body axis system and the Euler angle derivative. The meanings of the other parameters are listed in Table 1.

[0073] Table 1 Meanings of the parameters of the quadrotor UAV non - linear model

[0074]

[0075] According to the differential flatness theory, we can obtain:

[0076]

[0077] where, represents the second - order time derivative of the UAV position, and are obtained by the following formula:

[0078]

[0079] where,

[0080] Combined with the definition of the rotation matrix, the corresponding pitch and roll angles are solved from R.

[0081] Let ω B = [p q r] T , according to the differential flatness property, we can obtain:

[0082]

[0083]

[0084] where:

[0085]

[0086]

[0087] In the above formula, f is the magnitude of the UAV lift force vector, represents the first - order and second - order time derivatives of the UAV acceleration;

[0088] Select the flat output as σ = [x y z ψ] T, where x, y, and z are the positions of the UAV, and ψ is the yaw angle of the UAV. The reference signals for all the states (including positions, attitudes, and their derivatives) of the corresponding quadrotor UAV can be obtained from the trajectory in the flat output space and its derivatives of each order. This process is also called endogenous conversion.

[0089] Second, based on the virtual rigid body method, introduce a variable scaling coefficient to characterize the spatial configuration of the formation, and introduce a cooperative maneuver constraint to generate a single-vehicle trajectory solution model;

[0090] The trajectory of the i-th UAV in the formation is expressed as:

[0091]

[0092] where P v is the trajectory of the virtual centroid of the formation, α is the variable scaling coefficient, and R v is the rotation matrix of the overall attitude of the formation, and r i is the position vector of the i-th UAV relative to the formation center, which is determined by the specified formation shape.

[0093] The introduced cooperative maneuver constraint is:

[0094]

[0095] where Φ represents the endogenous conversion relationship established in the first step, represents the second-order time derivative of the trajectory of the virtual centroid of the formation, and ψ v represents the yaw angle of the overall formation; this constraint realizes the cooperative maneuver behavior of the quadrotor UAV formation, that is, the formation behavior is similar to a six-degree-of-freedom rigid body that can be scaled as a whole.

[0096] Third, design the formation maneuver actions, which are modeled as parametric constraints on the trajectory of the virtual rigid body centroid and the scaling coefficient. Using the second derivative index of acceleration, it is transformed into a quadratic programming problem for solution;

[0097] First, regard the trajectory P v (t) and the time-varying scaling coefficient α(t) in the three-dimensional space as four independent dimensions. For any dimension, a piecewise polynomial is used to describe it, and the waypoints that must be passed are used as nodes for segmentation. The time functions of each dimension are expressed as polynomials:

[0098]

[0099] where k is the number of segments of the trajectory, and p i is the parameter vector of the i-th short trajectory, and t i , i = 1, 2,..., n are the power functions of each order of time;

[0100] The second derivative of acceleration is used as the optimization index, i.e.:

[0101]

[0102] In the above formula, p (4) (t) represents the fourth-order time derivative of the virtual center-of-mass trajectory, p i and are the column vector composed of a set of polynomial coefficients and its transpose, p and p T represent the column vector composed of all polynomial coefficients and its transpose.

[0103]

[0104] Among them, r and c are the row index and column index of the matrix respectively, diag(Q 1 , Q 2 ,..., Q k ) represents the block matrix composed of sub-matrices in pairs; the position, velocity, and acceleration equality / inequality constraints of the waypoints passed by the formation are converted into linear equalities / inequalities about p; similarly, the continuity requirements at the nodes are also expressed by linear equalities about p; for the scaling coefficients, corresponding values are specified at different nodes to control the smooth spreading or contraction of the formation. For example, when it is necessary to cooperate to pass through a narrow slit, the scaling coefficient can be set to a value within the interval (0,1) at the waypoint where the narrow slit is located, so that the formation tightens to pass through the narrow slit while avoiding collisions between aircraft.

[0105] Taking the chain derivative of the single-aircraft trajectory solution model established in the second step, the acceleration of each single aircraft can be obtained as:

[0106]

[0107] Among them, is the second-order time derivative of the position of the i-th UAV, and are the first-order and second-order time derivatives of the variable scaling coefficient, and are the first-order and second-order time derivatives of the virtual rigid body rotation matrix.

[0108] According to the endogenous conversion relationship in the first step, at time t w , the attitude reference value corresponding to the single UAV is determined by ; the following transient constraints are introduced:

[0109]

[0110] Among them, represents the fourth-order derivative of the virtual center-of-mass position trajectory.

[0111] The above formula is realized at any specified t w moment, so that the attitudes of all UAVs are kept consistent and the same as the overall attitude of the formation;

[0112] All the above constraints are written in the following form:

[0113]

[0114] where, A and A l are constant matrices determined by the node moments, and b and b l are constant vectors set according to the system constraints. Finally, a quadratic programming problem composed of minimizing the second derivative index of acceleration and linear equalities / inequalities is solved by means of a common quadratic programming solver (for example: Gurobi).

[0115] In the fourth step, according to the endogenous conversion relationship and the single - machine trajectory mapping, reference signals such as the trajectories, attitudes and their derivatives of each single machine are given for generating the motor control commands of the single machine.

[0116] The solution process of the state reference signal of the i - th single machine is as follows:

[0117]

[0118] Similarly, and can both be obtained in an analytical form through the chain - rule of differentiation, and all reference signals such as Euler angles, angular velocities, rotation matrices and their derivatives, etc., can be obtained through the endogenous conversion relationship established in the first step.

[0119] In the process of designing the single - machine control law, the form of cascade PID can be adopted, and the corresponding reference signal information is introduced as feed - forward in each level of control or used to solve the tracking error to improve the tracking accuracy. It should be noted that the present invention does not involve the design of the single - machine control law of quadrotor UAVs. The high - order differentiable reference trajectory signals designed for formation flight in the present invention can be combined with most flight control algorithms for application to improve the formation flight control accuracy.

[0120] The content not described in detail in the specification of the present invention belongs to the prior art well - known to those skilled in the art. It is easy for those skilled in the art to understand that the above - mentioned is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. A method for cooperative maneuver control of a quadrotor UAV formation, characterized in that, it includes the following steps: First step, based on the differential flatness theory according to the dynamics model of the quadrotor UAV, establish the endogenous conversion relationship from the single - machine trajectory to the system state; Second step, based on the virtual rigid body, introduce a variable scaling coefficient to characterize the spatial configuration of the formation, and introduce cooperative maneuver constraints to generate a single - machine trajectory solution model; Third step, design the formation maneuver action, model it as the parametric constraints of the virtual rigid body centroid trajectory and the scaling coefficient, and use the second - derivative index of acceleration to transform it into a quadratic programming problem for solution; Fourth step, according to the endogenous conversion relationship and the single - machine trajectory mapping, give the reference signals of the trajectory, attitude and their derivatives of each single - machine, which are used to generate the motor control instructions of the single - machine.

2. A method for cooperative maneuver control of a quadrotor UAV formation according to claim 1, characterized in that: The specific implementation of the first step is as follows: Use Euler angles to represent the attitude of the quadrotor UAV, and the corresponding rotation matrix R is defined as: In the above formula, φ, θ, ψ are the Euler angles from the body coordinate system to the inertial coordinate system, corresponding to the roll angle, yaw angle and pitch angle respectively; Establish the following non - linear dynamics model of the quadrotor UAV: In the above formula, the superscript represents the coordinate system corresponding to the vector, where B represents the body frame of the quadrotor UAV, E represents the inertial coordinate system, which adopts the Earth coordinate system; G E = [0 0 mg] T represents gravity, F E = R[0 0 f] T represents the total lift force in the inertial coordinate system, It represents the projection relationship between the angular velocity measurement value and the Euler angle derivative in the body axis system. p represents the position vector of the quadrotor UAV, v represents the velocity vector, ω represents the angular velocity vector, and η = [φ θ ψ] T is the Euler angle, and J = [J xx J yy J zz T is the moment of inertia of the UAV, τ is the torque generated by the UAV actuator, F is the lift of the UAV, m is the mass of the UAV, and g is the acceleration due to gravity;​ From the differential flatness theory, it can be obtained that: Among them, represents the second time derivative of the UAV position, and is obtained by the following formula: Among them, Combined with the definition of the rotation matrix, solve the corresponding pitch and roll angles from R; Let ω B = [p q r] T , according to the differential flatness property, we can obtain: Where: In the above formula, f is the magnitude of the lift vector of the UAV, represents the first-order and second-order time derivatives of the UAV's acceleration; Select the flat output as σ = [x y z ψ] T , where x, y, and z are the positions of the UAV, and ψ is the yaw angle of the UAV. That is, the reference signal of all states of the quadrotor UAV including position, attitude, and their derivatives is obtained from the trajectory and its derivatives in the flat output space. This process is called endogenous conversion.

3. A method for cooperative maneuver control of a quadrotor UAV formation according to claim 2, characterized in that: In the second step, the trajectory of the i-th UAV in the formation is expressed as: Among them, P v is the trajectory of the formation virtual centroid, α is the variable scaling coefficient, R v is the rotation matrix of the overall formation attitude, r i is the position vector of the i-th UAV relative to the formation center, which is determined by the specified formation shape; The introduced cooperative maneuver constraint is: where Φ represents the endogenous conversion relationship established in the first step, represents the second-order time derivative of the virtual centroid trajectory of the formation, and ψ v represents the yaw angle of the entire formation; this constraint realizes the cooperative maneuvering behavior of the quadrotor UAV formation, that is, the formation behavior is similar to a six-degree-of-freedom rigid body that can be scaled as a whole.

4. A method for cooperative maneuver control of a quadrotor UAV formation according to claim 3, characterized in that: In the third step, the generation process of the formation virtual centroid trajectory and the scaling coefficient is as follows: First, consider the trajectory P v (t) and the time-varying scaling factor α(t) as four independent dimensions. For any dimension, piecewise polynomials are used for description, and the piecewise is carried out with the waypoints that must be passed as nodes. The time functions of each dimension are expressed as polynomials: where k is the number of segments of the trajectory, and p i is the parameter vector of the i-th shortest trajectory, and t i , i = 1, 2, ..., n are the power functions of each order of time; Use the minimization of the second - derivative of acceleration as the optimization index, that is: In the above formula, p (4) (t) represents the fourth-order time derivative of the virtual centroid trajectory, p i and are the column vector composed of a segment of polynomial coefficients and its transpose, p and p T represent the column vector composed of all polynomial coefficients and its transpose, where r and c are the row index and column index of the matrix, respectively, diag(Q 1 , Q 2 ,..., Q k ) represents a sub-matrix composed of paired comparison block matrices; The equality / inequality constraints of the track point positions, speeds, and accelerations that the formation is required to pass through are converted into linear equalities / inequalities about p; the continuity requirements at the nodes are also expressed by linear equalities about p; for the scaling coefficient, corresponding values are specified at different nodes to control the smooth dispersion or contraction of the formation; Taking the chain derivative of the single - machine trajectory solution model established in the second step, the acceleration of each single - machine can be obtained as: wherein, is the second-order time derivative of the position of the i-th unmanned aerial vehicle, and are the first-order and second-order time derivatives of the variable scaling coefficient, and are the first-order and second-order time derivatives of the rotation matrix of the virtual rigid body; According to the endogenous conversion relationship in the first step, at time t w , the attitude reference value corresponding to a single UAV is determined by . The following transient constraints are introduced: Among them, represents the fourth derivative of the virtual centroid position trajectory; The above formula is realized at any specified t w moment, so that the attitudes of all UAVs are consistent and the same as the overall attitude of the formation; All the above - mentioned constraints are written in the following form: where A and A l are constant matrices determined by the node time, and b and b l are constant vectors set according to system constraints; finally, a quadratic programming problem composed of minimizing the second derivative index of acceleration and linear equalities / inequalities is solved by means of a common quadratic programming solver.

5. A method for cooperative maneuver control of a quadrotor UAV formation according to claim 4, characterized in that: In the fourth step, the solution process of the state reference signal of the i - th single - machine is as follows: Similarly, higher-order time derivatives and can all be obtained in an analytical form through the chain rule of differentiation. The reference signals of all Euler angles, angular velocities, rotation matrices, and their derivatives are obtained through the endogenous conversion relationships established in the first step.

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