CN112859913A - Multi-quad-rotor unmanned aerial vehicle attitude consistency optimal control method considering output constraint - Google Patents

Abstract

The utility model provides a multi-quad-rotor unmanned aerial vehicle attitude consistency optimal control method and system considering output constraints. Firstly, carrying out mathematical modeling on the attitude dynamic characteristics of the quad-rotor unmanned aerial vehicle; then, converting the system attitude control problem with output constraint into an optimal control problem under the unconstrained condition by adopting system conversion based on a barrier function; aiming at the transformed stateless constraint system, a single-network self-adaptive dynamic programming method is adopted to solve a distributed Hamilton-Jacobian-Bellman equation so as to obtain a distributed optimal attitude control law; the output of the attitude system of the multi-quad rotor unmanned aerial vehicle can effectively track the attitude signal of the leader and keep in the required safety range.

Description

Attitude-consistent optimal control method for multi-quadcopter UAV considering output constraints

technical field

The present disclosure belongs to the technical field of quadrotor unmanned aerial vehicle control, and in particular relates to an optimal control method for a multi-quadrotor unmanned aerial vehicle that considers output constraints with consistent attitude.

Background technique

The statements in this section merely provide background information related to the present disclosure and do not necessarily constitute prior art.

Due to the characteristics of light weight, small size, strong maneuverability and strong adaptability, quadrotor UAVs are becoming more and more popular in both civilian and military fields. Compared with a single quad-rotor UAV to perform tasks alone, the collaboration of multiple quad-rotor UAVs has greater advantages. For example, in the context of high-rise fire extinguishing problems, using multiple quad-rotor drones for fire detection is undoubtedly an effective solution for high-rise building fire protection. However, in the high-rise building fire environment, due to the complexity of the building structure, the posture of the quadrotor UAV is limited by the environment and cannot swing greatly. Therefore, it is of great practical significance to consider the attitude consistency control of quadrotor UAV with limited attitude angle.

The inventor found that in recent years, the attitude control of quadrotor UAV with output constraints has received extensive attention, and many important research results have been achieved; however, most of the results have not considered the optimal control problem, and because the quadrotor has no The output of the human-machine attitude system needs to meet a certain safety range, and it is very difficult to design an effective optimal controller for it.

SUMMARY OF THE INVENTION

In order to solve the above problems, the present disclosure provides an optimal control method for a multi-quadrotor unmanned aerial vehicle that considers output constraints with consistent attitude.

According to a first aspect of the embodiments of the present disclosure, there is provided a multi-quadrotor UAV attitude-consistent optimal control method considering output constraints, including:

Model the attitude physics of a single quadrotor UAV;

According to the physical characteristics of a single quadrotor UAV, the equation model obtained by modeling is transformed into a state equation with constraints;

Determine the communication topology of the multi-quadcopter UAV, and convert the state equation with output constraints into an unconstrained state equation based on the obstacle function;

For the unconstrained state equation, determine the synergy consistency error and its performance index function;

The distributed Hamilton-Jacobi-Bellman equation is determined, and the single-network adaptive dynamic programming method is used to approximately solve the Hamilton-Jacobi-Bellman equation, thereby obtaining the distributed optimal attitude control law.

Further, the physical characteristics of the attitude of a single quad-rotor unmanned aerial vehicle are modeled, and the built model is a quad-rotor unmanned aerial vehicle attitude dynamics model described based on Euler angles, and the model is specifically expressed as follows:

Among them, Θ _i = [φ _i , θ _i , ψ _i ] ^T represents the Euler angle in the body coordinate system, and φ _i , θ _i , ψ _i represent the roll angle and pitch angle of the quadrotor UAV attitude, respectively and yaw angle; Ω _i =[ω _ix ,ω _iy ,ω _iz ] ^T represents the angular velocity vector, ω _ix , ω _iy , ω _iz represent the roll angular velocity, pitch angular velocity and yaw angular velocity respectively; I _i =diag(I _ix , I _iy , I _iz ) represent the positive definite inertia matrix; M _i =[u _iφ , u _iθ , u _iψ ] ^T represents the rotational torque input by the attitude angle of the quadrotor unmanned aerial vehicle; T _i represents the transformation matrix, the transformation matrix for:

Further, the equation model obtained by modeling is transformed into a state equation with constraints, and its state equation is expressed as follows:

y _i =[x _i1 ,x _i3 ,x _i5 ] ^T

in,

g(x _i )=diag[1/I _ix , 1/I _iy , 1/I _iz ];

u _i =[u _iφ u _iθ u _iψ ] ^T ; x _i =[x _i1 ,x _i2 ,x _i3 ,x _i4 ,x _i5 ,x _i6 ] ^T

Here, x _i1 =φ _i , x _i2 =ω _ix , x _i3 =θ _i , x _i4 =ω _iy , x _i5 =ψ _i , x _i6 =ω _iz , and it is necessary to satisfy

Further, the determining of the communication topology of the multi-quadcopter UAV includes the following steps:

表示图中有向边的集合，A＝[a_ij]∈R^n×n表示有向图G的权重矩阵；Use the directed graph G={V,E,A} to describe the communication connection between the UAVs in the formation; where V={0,1,...,N-1} represents the set of nodes in the graph G ,

Represents the set of directed edges in the graph, A=[a _ij ]∈R ^n×n represents the weight matrix of the directed graph G;

假设a_ii＝0，有向图为严格连接；僚机i和领机的连接关系表示为对角矩阵B＝diag{b₁,...,b_N}，若僚机i能够从领导者接收信息，则b_i＝1，否则b_i＝0。If wingman i can receive information from wingman j, then a _ij = 1 (i≠j), otherwise, a _ij =0; the neighbor node of node i is defined as N _i ={j∈V|(i,j) ∈E, i≠j}, the in-degree matrix D is D=diag{d ₁ ,...d _N }, where

Assuming a _ii = 0, the directed graph is strictly connected; the connection relationship between wingman i and the leader is expressed as a diagonal matrix B=diag{b ₁ ,...,b _N }, if wingman i can receive information from the leader , then b _i =1, otherwise b _i =0.

Further, converting the state equation with output constraints into an unconstrained state equation includes the following steps:

Pre-defined state transition mapping relationship;

The state equation with output constraints is transformed into an unconstrained state equation by using the mapping relationship.

Further, the state transition mapping relationship is:

in,

Further, for the unconstrained state equation, determine the synergy consistency error and the performance index function as follows:

The synergy consistency error is defined as

Among them, s _d is the desired trajectory of the leader to be tracked.

Define the performance indicator function as

in,

Further, the determining the distributed Hamilton-Jacobi-Bellman equation includes:

Determine the Hamiltonian function, the optimal performance index function and the distributed optimal cooperative control law function respectively;

Substitute the distributed optimal cooperative control law function into the Hamiltonian function to obtain the Hamilton-Jacobi-Bellman equation.

Further, the single-network adaptive dynamic programming method is used to approximately solve the Hamilton-Jacobi-Bellman equation, including:

Based on the approximation ability of the neural network to nonlinear functions, construct the evaluation network online approximation optimal performance index function;

The actual distributed optimal attitude control law is obtained based on the online approximation of the optimal performance index function.

According to a second aspect of the embodiments of the present disclosure, there is provided an attitude-consistent control system for a multi-quadcopter unmanned aerial vehicle considering output constraints, which includes a processor unit, and the processor executes the above-mentioned multi-rotor UAV attitude control system considering output constraints. The steps of the quadrotor UAV attitude consistent optimal control method.

Compared with the prior art, the beneficial effects of the present disclosure are:

(1) The solution described in this disclosure introduces a state transition technology to generate an equivalent unconstrained nonlinear system, which transforms the output-constrained optimal control problem of the original quadrotor UAV attitude system into a traditional unconstrained one Optimal control problem; for the transformed unconstrained equivalent system, the adaptive dynamic programming method is used to obtain the optimal controller, which not only ensures that the attitude angle of the UAV remains within a safe range, but also optimizes its control performance.

(2) The solution described in this disclosure approximates the performance index function by using a single network structure, and then obtains the optimal cooperative control law. It is more meaningful to use a single evaluation network instead of the typical execution-evaluation dual network structure in the multi-quadrotor attitude system. Significant, can reduce memory requirements and computational burden.

Advantages of additional aspects of the disclosure will be set forth in part in the description that follows, and in part will become apparent from the description below, or will be learned by practice of the disclosure.

Description of drawings

The accompanying drawings that constitute a part of the present disclosure are used to provide further understanding of the present disclosure, and the exemplary embodiments of the present disclosure and their descriptions are used to explain the present disclosure and do not constitute an improper limitation of the present disclosure.

1 is a structural model diagram of the quadrotor unmanned aerial vehicle described in the first embodiment of the disclosure;

2 is a communication topology diagram of the multi-quadcopter UAV described in Embodiment 1 of the present disclosure;

3 is an effect diagram of the roll angle tracking described in Embodiment 1 of the present disclosure;

FIG. 4 is an effect diagram of the pitch angle tracking described in Embodiment 1 of the present disclosure;

FIG. 5 is an effect diagram of the yaw angle tracking described in Embodiment 1 of the present disclosure.

Detailed ways

The present disclosure will be further described below with reference to the accompanying drawings and embodiments.

It should be noted that the following detailed description is exemplary and intended to provide further explanation of the present disclosure. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure belongs.

It should be noted that the terminology used herein is for the purpose of describing specific embodiments only, and is not intended to limit the exemplary embodiments according to the present disclosure. As used herein, unless the context clearly dictates otherwise, the singular is intended to include the plural as well, furthermore, it is to be understood that when the terms "comprising" and/or "including" are used in this specification, it indicates that There are features, steps, operations, devices, components and/or combinations thereof.

The embodiments of this disclosure and features of the embodiments may be combined with each other without conflict. Example 1:

The purpose of this embodiment is to provide an attitude consistency optimization control method for a multi-quadcopter UAV considering output constraints.

A multi-quadcopter UAV attitude consistency optimization control method considering output constraints, including the following steps:

S1: Model the physical characteristics of the attitude of a single quadrotor UAV;

The quadrotor UAV studied in this example has a coaxial structure with four rotors. The structure is shown in Figure 1. Four rotors are installed in pairs at the end of the connecting rod to provide power for various flight missions. The attitude dynamics model of the quadrotor UAV based on the Euler angle description is established as follows:

Among them, Θ _i = [φ _i , θ _i , ψ _i ] ^T represents the Euler angle in the body coordinate system, and φ _i , θ _i , ψ _i represent the roll angle and pitch angle of the quadrotor UAV attitude, respectively and yaw angle; Ω _i =[w _ix , w _iy , w _iz ] ^T represents angular velocity vector, w _ix , w _iy , w _iz represent roll angular velocity, pitch angular velocity and yaw angular velocity respectively; I _i =diag(I _ix , I _iy , I _iz ) represent positive definite inertial matrices. M _i =[u _iφ , u _iθ , u _iψ ] ^T represents the rotational torque input by the attitude angle of the quadrotor UAV.

transformation matrix

Then, the quadrotor UAV model can be further expressed as

Among them, the attitude angles φ _i , θ _i , ψ _i need to satisfy

The control objective of this embodiment is that the output of the multi-quadcopter UAV attitude system can track a given signal in an optimal way, and at the same time, the performance index function is minimized, so as to ensure that all signals in the system are consistent and ultimately bounded.

S2: According to the physical characteristics of a single quadrotor UAV, the equation model obtained by modeling is transformed into the state equation as follows:

Let x _i1 =φ _i , x _i2 =ω _ix , x _i3 =θ _i , x _i4 =ω _iy , x _i5 =ψ _i , x _i6 =ω _iz . Therefore, the state space of the quadrotor UAV attitude system is expressed as

y _i =[x _i1 ,x _i3 ,x _i5 ] ^T

Among them, y _i is the system output and needs to meet the

Write the quadrotor UAV attitude dynamics model as the following compact structure

y _i =[x _i1 ,x _i3 ,x _i5 ] ^T

in,

g(x _i )=diag[1/I _ix , 1/I _iy , 1/I _iz ];

u _i =[u _iφ u _iθ u _iψ ] ^T ; x _i =[x _i1 ,x _i2 ,x _i3 ,x _i4 ,x _i5 ,x _i6 ] ^T

S3: Determine the communication topology of the multi-quadcopter UAV as follows:

Use the directed graph G={V,E,A} to describe the communication connection between the UAVs in the formation;

表示图中有向边的集合，A＝[a_ij]∈R^n×n表示有向图G的权重矩阵；Among them, V={0,1,...,N-1} represents the set of nodes in the graph G,

Represents the set of directed edges in the graph, A=[a _ij ]∈R ^n×n represents the weight matrix of the directed graph G;

假设a_ii＝0，有向图为严格连接；僚机i和领机的连接关系表示为对角矩阵B＝diag{b₁,...,b_N}，若僚机i能够从领导者接收信息，则b_i＝1，否则b_i＝0。If wingman i can receive information from wingman j, then a _ij = 1 (i≠j), otherwise, a _ij =0; the neighbor node of node i is defined as N _i ={j∈V|(i,j) ∈E, i≠j}, the in-degree matrix D is D=diag{d ₁ ,...d _N }, where

Assuming a _ii = 0, the directed graph is strictly connected; the connection relationship between wingman i and the leader is expressed as a diagonal matrix B=diag{b ₁ ,...,b _N }, if wingman i can receive information from the leader , then b _i =1, otherwise b _i =0.

S4: Based on the barrier function, the state equation with output constraints is transformed into an unconstrained state equation as follows:

To deal with output-constrained problems, barrier function transformation techniques are introduced. Define a state transition map as follows:

in,

Then the system dynamics without output constraints after transformation is

Among them, s _i =[s _i1 ,s _i2 ,s _i3 ,s _i4 ,s _i5 ,s _i6 ] ^T ,

S5: For the unconstrained state equation, define the synergy consistency error and the performance index function as follows:

The synergy consistency error is defined as

Among them, s _d is the desired trajectory of the leader to be tracked.

Define the performance indicator function as

in,

S6: Derive the distributed Hamilton-Jacobi-Bellman equation as follows:

The Hamiltonian function can be defined as

The optimal performance index function can be expressed in the following form

Among them, U(Ω) is the set of allowed control.

可以得到分布式最优协同控制律如下：According to Bellman's principle of optimality, by

The distributed optimal cooperative control law can be obtained as follows:

Substituting the optimal cooperative control law into the Hamiltonian function, the corresponding distributed Hamiltonian-Jacobi-Bellman equation is

It is noted that the Hamilton-Jacobi-Bellman equation is difficult to obtain its analytical solution, in order to overcome this problem, the single-network ADP method is used to approximate the solution.

S7: The single-network adaptive dynamic programming method is used to approximately solve the Hamilton-Jacobi-Bellman equation, so as to obtain the distributed optimal attitude control law as follows:

Based on the approximation ability of the neural network to nonlinear functions, the optimal performance index function of the online approximation evaluation network is constructed as follows

表示理想权重向量w_ci的估计值。Among them, w _ci ∈ R ^l represents the ideal weight vector, σ _i (δ _i )∈R ^l represents the excitation function, and l is the number of neurons in the hidden layer. ε _ci (δ _i ) represents the approximation error of the neural network. Its approximation is

represents an estimate of the ideal weight vector _wci .

Then the actual distributed optimal attitude control law u _i is

The weight update law of the design evaluation network is as follows

where λ _i represents the learning rate and is a suitable constant.

In order to confirm the validity of this embodiment, the following simulation experiments are carried out:

各四旋翼无人机姿态初始值In this simulation experiment, the control objective is to track the attitude angle of the lead aircraft φ ₀ =0.1sin(t), θ ₀ =0.1sin(t), ψ ₀ =0. According to the actual system, the physical parameters of the system in the model adopted in this example are selected as I _ix =0.0081Nms ^-2 , I _iy =0.0142Nms ^-2 , and I _iz =0.0081Nms ^-2 . The attitude angle limited parameter is selected as

Initial value of the attitude of each quadrotor UAV

s ₁ =[0.1,-0.5,0.1,-0.5,0.1,-0.5] ^T , s ₂ =[0.2,0.5,0.2,0.5,0.2,0.5] ^T ,s ₃ =[0.2,0.5,0.2,0.5 , 0.2, 0.5] ^T , s ₄ = [0.25, 1, 0.25, 1, 0.25, 1] ^T .

The above scheme proposes a distributed adaptive optimal attitude control scheme for a class of four-rotor UAV formations in the form of leader-wingman collaboration, so that the attitude angles of each wingman and the leader tend to be consistent, and at the same time, each UAV. The attitude angle satisfies certain constraints.

Result analysis:

Choose the Lyapunov function

对其求时间导数，可得

那么根据李雅普诺夫稳定性定理，神经网络权值误差

和协同一致性误差δ_i都是一致最终有界的，即神经网络权重可以收敛到理想值，以及所有僚机的姿态角可以和领机的姿态角达到一致。

Taking the time derivative of it, we get

Then according to the Lyapunov stability theorem, the weight error of the neural network

and the synergy consistency error _δi are both consistent and ultimately bounded, that is, the neural network weights can converge to an ideal value, and the attitude angles of all wingmen can be consistent with that of the leader.

As can be seen from Figure 3, Figure 4 and Figure 5, the roll angle, pitch angle and yaw angle of each wingman can be consistent with the lead aircraft, the tracking effect is good, and the amplitude of the output signal is kept within the safe range of ±0.15 .

This embodiment realizes the consistent control of the attitude system of the multi-quadrotor UAV under the directed communication network based on the single-network adaptive dynamic programming method, and considers the problem of limited system output. Through the obstacle function system conversion technology, the attitude system of the quadrotor UAV with limited output is converted into an unconstrained equivalent system. For the unconstrained equivalent system, the adaptive dynamic programming method is used to solve the Hamilton-Jacobi-Bellman equation, and the optimal control strategy considering output constraints is obtained. This scheme not only makes the attitude angle of the wingman tend to be consistent with the leader in an optimal way, but also keeps the output of the attitude system within a certain limited range.

The solution described in the present disclosure provides a new method for system transformation based on barrier functions, which is different from the barrier Lyapunov method in the prior art in that this method can transform an output-constrained system into a non-output-constrained system, etc. The valence system, through the system equivalence conversion, provides convenience for dealing with other control problems, which is not only feasible in theory, but also easier to realize in practice.

Embodiment 2:

The purpose of this embodiment is to provide a multi-quadrotor UAV attitude consistent optimal control system considering output constraints.

A multi-quadrotor unmanned aerial vehicle attitude consistent optimization control system considering output constraints, which includes a processor unit, the processor executes the above-mentioned output constraints of a multi-quadrotor unmanned aerial vehicle attitude consistency optimal control method. step.

The above-mentioned embodiment provides a method and system for optimizing the attitude consistency of a multi-quadcopter UAV considering output constraints, which can be implemented and has broad application prospects.

The above descriptions are only preferred embodiments of the present disclosure, and are not intended to limit the present disclosure. For those skilled in the art, the present disclosure may have various modifications and changes. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present disclosure shall be included within the protection scope of the present disclosure.

Although the specific embodiments of the present disclosure have been described above in conjunction with the accompanying drawings, they do not limit the protection scope of the present disclosure. Those skilled in the art should understand that on the basis of the technical solutions of the present disclosure, those skilled in the art do not need to pay creative efforts. Various modifications or variations that can be made are still within the protection scope of the present disclosure.

Claims (10)

1. a multi-four-rotor unmanned aerial vehicle attitude consistent optimal control method considering output constraints, is characterized in that, comprises: Model the attitude physics of a single quadrotor UAV; According to the physical characteristics of a single quadrotor UAV, the equation model obtained by modeling is transformed into a state equation with constraints; Determine the communication topology of the multi-quadcopter UAV, and convert the state equation with output constraints into an unconstrained state equation based on the obstacle function; For the unconstrained state equation, determine the synergy consistency error and its performance index function; The distributed Hamilton-Jacobi-Bellman equation is determined, and the single-network adaptive dynamic programming method is used to approximately solve the Hamilton-Jacobi-Bellman equation, thereby obtaining the distributed optimal attitude control law. 2. a kind of multi-four-rotor unmanned aerial vehicle attitude consistent optimal control method considering output constraints as claimed in claim 1, is characterized in that, described to the attitude physical characteristic of single four-rotor unmanned aerial vehicle is modeled, so The model is based on the quadrotor UAV attitude dynamics model described by Euler angles, and the model is specifically expressed as follows:

Among them, Θ _i = [φ _i , θ _i , ψ _i ] ^T represents the Euler angle in the body coordinate system, and φ _i , θ _i , ψ _i represent the roll angle and pitch angle of the quadrotor UAV attitude, respectively and yaw angle; Ω _i =[ω _ix ,ω _iy ,ω _iz ] ^T represents the angular velocity vector, ω _ix , ω _iy , ω _iz represent the roll angular velocity, pitch angular velocity and yaw angular velocity respectively; I _i =diag(I _ix , I _iy , I _iz ) represent the positive definite inertia matrix; M _i =[u _iφ , u _iθ , u _iψ ] ^T represents the rotational torque input by the attitude angle of the quadrotor UAV; T _i represents the transformation matrix, the transformation matrix for:

3. a kind of multi-four-rotor unmanned aerial vehicle attitude consistent optimal control method considering output constraints as claimed in claim 1, is characterized in that, described equation model obtained by modeling is converted into the state equation with constraint, Its state equation is expressed as follows:

y _i =[x _i1 ,x _i3 ,x _i5 ] ^T in,

g(x _i )=diag[1/I _ix , 1/I _iy , 1/I _iz ]; u _i =[u _iφ u _iθ u _iψ ] ^T ; x _i =[x _i1 ,x _i2 ,x _i3 ,x _i4 ,x _i5 ,x _i6 ] ^T Here, x _i1 =φ _i , x _i2 =ω _ix , x _i3 =θ _i , x _i4 =ω _iy , x _i5 =ψ _i , x _i6 =ω _iz , and it is necessary to satisfy

4. a kind of multi-quadrotor unmanned aerial vehicle attitude consistent optimal control method considering output constraints as claimed in claim 1, it is characterized in that, the communication topology structure of described determining many quadrotor unmanned aerial vehicles comprises the steps: A directed graph G={V,E,A} is used to describe the communication connection between UAVs in the formation; where V={0,1,...,N-1} represents the set of nodes in the graph G ,

Represents the set of directed edges in the graph, A=[a _ij ]∈R ^n×n represents the weight matrix of the directed graph G; If wingman i can receive information from wingman j, then a _ij = 1 (i≠j), otherwise, a _ij =0; the neighbor node of node i is defined as N _i ={j∈V|(i,j) ∈E, i≠j}, the in-degree matrix D is D=diag{d ₁ ,...d _N }, where

Assuming a _ii = 0, the directed graph is strictly connected; the connection relationship between wingman i and the leader is expressed as a diagonal matrix B=diag{b ₁ ,...,b _N }, if wingman i can receive information from the leader , then b _i =1, otherwise b _i =0. 5. a kind of multi-quadrotor unmanned aerial vehicle attitude consistent optimal control method considering output constraints as claimed in claim 1, it is characterized in that, described state equation with output constraint is converted into unconstrained state equation comprising: Follow the steps below: Pre-defined state transition mapping relationship; The state equation with output constraints is transformed into an unconstrained state equation by using the mapping relationship. 6. a kind of multi-quadcopter unmanned aerial vehicle attitude consistent optimal control method considering output constraints as claimed in claim 1, is characterized in that, described state transition mapping relation is:

in,

7. a kind of multi-quadrotor unmanned aerial vehicle attitude consistent optimal control method considering output constraints as claimed in claim 1, it is characterized in that, described for unconstrained state equation, determine synergy consistency error and performance index function as follows: The synergy consistency error is defined as

Among them, s _d is the desired trajectory of the leader to be tracked; Define the performance indicator function as

in,

8. a kind of multi-quadrotor unmanned aerial vehicle attitude consistent optimal control method considering output constraints as claimed in claim 1 is characterized in that, described determining distributed Hamiltonian-Jacoby-Bellman equation comprises: Determine the Hamiltonian function, the optimal performance index function and the distributed optimal cooperative control law function respectively; Substitute the distributed optimal cooperative control law function into the Hamiltonian function to obtain the Hamilton-Jacobi-Bellman equation. 9. a kind of multi-quadrotor unmanned aerial vehicle attitude consistent optimal control method considering output constraints as claimed in claim 1, is characterized in that, described adopting single-network adaptive dynamic programming method to approximately solve Hamiltonian-Jacobian- Bellman equation, including: Based on the approximation ability of the neural network to nonlinear functions, construct the evaluation network online approximation optimal performance index function; The actual distributed optimal attitude control law is obtained based on the online approximation of the optimal performance index function. 10. A multi-quadcopter unmanned aerial vehicle attitude consistent optimal control system considering output constraints, it comprises a processor unit, it is characterized in that, described processor executes a kind of described in any one of claim 1-7 Steps of an attitude-consistent optimal control method for a multi-quadcopter UAV considering output constraints.

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