CN111538255B - Anti-bee colony unmanned aerial vehicle aircraft control method and system - Google Patents
Anti-bee colony unmanned aerial vehicle aircraft control method and system Download PDFInfo
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Abstract
The application relates to an aircraft control method and system of an anti-bee colony unmanned aerial vehicle, comprising the steps of creating a model of an unmanned aerial vehicle component and an environment component, wherein the unmanned aerial vehicle component is used for simulating performance parameters of the anti-bee colony unmanned aerial vehicle, and the environment component is used for simulating simulation environment parameters; generating a simulation model according to the unmanned aerial vehicle assembly model, the environment assembly model and preset configuration information in an unmanned aerial vehicle controller; setting a flight route of unmanned aerial vehicle flight, and inputting the flight route into the simulation model; and acquiring the simulation flight parameters output by the simulation model in real time, and sending a flight mode switching instruction to the unmanned aerial vehicle assembly when the simulation flight parameters reach a set threshold value. The unmanned aerial vehicle has the advantages that the vertical take-off and landing functions of the unmanned aerial vehicle are realized through the vertical flight mode, the long-endurance and quick-cruising functions of the unmanned aerial vehicle are realized through the horizontal flight mode, and the multifunctional integrated structure is realized, so that the requirement of executing special tasks in a complex environment is met.
Description
Technical Field
The application relates to the technical field of unmanned aerial vehicle flight control, in particular to an anti-bee colony unmanned aerial vehicle aircraft control method and system.
Background
With the continuous development of aerospace technology, unmanned aerial vehicles have been increasingly widely used in various fields such as communication, navigation positioning, resource exploration, dangerous situation detection, scientific research, military and the like. Flight control systems are an important component of unmanned aerial vehicles.
The traditional unmanned aerial vehicle is mainly divided into two main types of fixed-wing unmanned aerial vehicles and multi-rotor unmanned aerial vehicles, and the fixed-wing unmanned aerial vehicle can realize long-endurance and quick cruising, but is difficult to have a vertical take-off and landing function; the multi-rotor unmanned aerial vehicle can realize the vertical take-off and landing function, but has the characteristics of long endurance and quick cruising.
In this case, the two unmanned aerial vehicles cannot perform some special tasks in some complex environments, so that it is necessary to design a novel flight control system and method for the unmanned aerial vehicles.
Disclosure of Invention
Based on the above, it is necessary to provide a method and a system for controlling an aircraft of an anti-bee colony unmanned aerial vehicle, so as to ensure that the anti-bee colony unmanned aerial vehicle using the control system and the method can integrate functions of long voyage, quick cruising, vertical take-off and landing and the like.
A method of controlling an aircraft of a antifungus drone, the method comprising:
creating a model of an unmanned aerial vehicle component and an environment component, wherein the unmanned aerial vehicle component is used for simulating performance parameters of the anti-bee colony unmanned aerial vehicle, and the environment component is used for simulating environment parameters;
generating a simulation model according to the unmanned aerial vehicle assembly model, the environment assembly model and preset configuration information in an unmanned aerial vehicle controller;
setting a flight route of unmanned aerial vehicle flight, and inputting the flight route into the simulation model;
collecting simulation flight parameters output by the simulation model in real time, and sending a flight mode switching instruction to the unmanned aerial vehicle assembly when the simulation flight parameters reach a set threshold value; the flight mode includes: vertical flight mode, horizontal flight mode, and transitional flight mode.
In one embodiment, the preset configuration information at least includes a route, a waypoint, a position, a speed, an acceleration, a distance, a pitch angle, a yaw angle, a track angle, a sideslip angle, an attack angle, a force, a control moment, and a moment of inertia; wherein,,
the force at least comprises the total pulling force generated by four propellers of the unmanned aerial vehicle, the pulling force of any propeller, air pressure, lifting force and resistance;
the control moment at least comprises a rolling control moment, a pitching control moment and a yawing control moment;
the thresholds include at least a distance threshold, a track angle threshold, and a yaw angle threshold.
In one embodiment, the simulated flight parameters simultaneously satisfy when the unmanned aerial vehicle assembly switches from a vertical flight mode to a horizontal flight mode: the distance to the next preset waypoint is greater than the set distance threshold, the desired track angle to the next preset waypoint is less than the set track angle threshold, and the desired yaw angle threshold to the next preset waypoint is less than the set yaw angle threshold.
In one embodiment, the simulated flight parameters satisfy when the unmanned aerial vehicle assembly switches from a horizontal flight mode to a vertical flight mode: the distance to the next preset waypoint is less than the set distance threshold or the desired track angle to the next preset waypoint is greater than the set track angle threshold.
In one embodiment, the unmanned aerial vehicle adopts a vertical take-off and landing control mode to carry out vertical flight control, the unmanned aerial vehicle adopts a rapid flat flight control mode to carry out horizontal flight control, and the unmanned aerial vehicle adopts a hybrid control mode to realize transition flight control.
In one embodiment, the unmanned aerial vehicle is required to establish a dynamic model and a kinematic model based on the anti-bee colony unmanned aerial vehicle in a vertical flight mode; analyzing the functional relation between the pressure born by the unmanned aerial vehicle component and the air speed, the air density, the shape and the gesture of the unmanned aerial vehicle according to the dynamic model; and analyzing the action type and the motion trail of the unmanned aerial vehicle component according to the kinematic model.
In one embodiment, the method further comprises:
when the unmanned aerial vehicle unit adopts the vertical take-off and landing mode control, executing the stable control of take-off, landing and emergency;
when the unmanned aerial vehicle assembly adopts the fast plane flight mode control, executing self-adaptive coordination control, and expanding a safe flight envelope of the unmanned aerial vehicle cluster;
when the unmanned aerial vehicle is subjected to mixed mode switching control, the pitch angle of the unmanned aerial vehicle is used as a scheduling variable, and the transitional flight process is controlled according to the value of the pitch angle.
An anti-swarm drone aircraft control system, the system comprising:
the system comprises a building module, a simulation module and a simulation module, wherein the building module is used for building a model of an unmanned aerial vehicle component and an environment component, the unmanned aerial vehicle component is used for simulating performance parameters of the anti-bee colony unmanned aerial vehicle, and the environment component is used for simulating simulation environment parameters;
the model generation module is used for generating a simulation model according to the unmanned aerial vehicle assembly model, the environment assembly model and preset configuration information in the unmanned aerial vehicle controller;
the guidance module is used for setting a flight route of unmanned aerial vehicle flight and inputting the flight route into the simulation model;
and the simulation analysis module is used for collecting the simulation flight parameters output by the simulation model in real time, and sending a flight mode switching instruction to the unmanned aerial vehicle assembly when the simulation flight parameters reach a set threshold value.
A computer device comprising a memory storing a computer program and a processor which when executing the computer program performs the steps of:
creating a model of an unmanned aerial vehicle component and an environment component, wherein the unmanned aerial vehicle component is used for simulating performance parameters of the anti-bee colony unmanned aerial vehicle, and the environment component is used for simulating environment parameters;
generating a simulation model according to the unmanned aerial vehicle assembly model, the environment assembly model and preset configuration information in an unmanned aerial vehicle controller;
setting a flight route of unmanned aerial vehicle flight, and inputting the flight route into the simulation model;
collecting simulation flight parameters output by the simulation model in real time, and sending a flight mode switching instruction to the unmanned aerial vehicle assembly when the simulation flight parameters reach a set threshold value; the flight mode includes: vertical flight mode, horizontal flight mode, and transitional flight mode.
A computer readable storage medium having stored thereon a computer program which when executed by a processor performs the steps of:
creating a model of an unmanned aerial vehicle component and an environment component, wherein the unmanned aerial vehicle component is used for simulating performance parameters of the anti-bee colony unmanned aerial vehicle, and the environment component is used for simulating environment parameters;
generating a simulation model according to the unmanned aerial vehicle assembly model, the environment assembly model and preset configuration information in an unmanned aerial vehicle controller;
setting a flight route of unmanned aerial vehicle flight, and inputting the flight route into the simulation model;
collecting simulation flight parameters output by the simulation model in real time, and sending a flight mode switching instruction to the unmanned aerial vehicle assembly when the simulation flight parameters reach a set threshold value; the flight mode includes: vertical flight mode, horizontal flight mode, and transitional flight mode.
Compared with the prior art, the invention has the following advantages:
according to the aircraft control method, the system, the computer equipment and the storage medium of the anti-bee colony unmanned aerial vehicle, the unmanned aerial vehicle is simulated in a component mode according to the performance parameters of the unmanned aerial vehicle, so that an unmanned aerial vehicle component is constructed, in order to ensure system simulation, the unmanned aerial vehicle component is taken as a core, an environment component is created, the environment component is used for simulating the environment parameters, the unmanned aerial vehicle is converted into data executed by a computer through the processing, preset configuration information is input, the unmanned aerial vehicle component and the environment component are called, so that a simulation model is generated, a flight route of the unmanned aerial vehicle in flight is set and is input into the simulation model, the simulation flight parameters are acquired in real time, and a flight mode switching instruction is sent when the set threshold value is reached; the purpose of switching the flight mode is to realize the vertical take-off and landing function of the unmanned aerial vehicle through the vertical flight mode, realize the long-endurance and quick cruising function of the unmanned aerial vehicle through the horizontal flight mode, realize the integrative integration of multi-function, thereby satisfy the requirement of executing special tasks under the complex environment.
Drawings
Fig. 1 is a schematic flow chart of an aircraft control method of an anti-swarm unmanned aerial vehicle according to the present invention;
FIG. 2 is a frame assembly diagram of the unmanned aerial vehicle flight control system;
fig. 3 is a schematic view of a flight mode status of the unmanned aerial vehicle;
FIG. 4 is a flow chart of selection of the unmanned aerial vehicle flight mode;
FIG. 5 is a frame diagram of a kinetic model of the drone;
FIG. 6 is a graph of the relationship between the lift coefficient and angle of attack of the unmanned aerial vehicle;
FIG. 7 is a diagram of a total energy control system framework of the unmanned aerial vehicle;
fig. 8 and 9 are simulation results of speed and track climbing angle control of the unmanned aerial vehicle;
FIGS. 10 and 11 are simulation results of the control of the unmanned aerial vehicle to continuously vary the flight speed;
FIG. 12 is a frame diagram of a guidance module of the drone;
fig. 13 is a diagram of switching conditions of the horizontal flight mode and the vertical flight mode of the unmanned plane;
FIG. 14 is a flight trajectory of the drone;
FIG. 15 is a graph of the unmanned aerial vehicle fly height over time;
FIG. 16 is a graph of the position of the north of the drone as a function of time;
fig. 17 is an internal structural view of the computer device.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application will be further described in detail with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the present application.
The method for controlling the aircraft of the anti-bee colony unmanned aerial vehicle shown in fig. 1 mainly comprises the following steps:
s1, creating a model of an unmanned aerial vehicle component and an environment component, wherein the unmanned aerial vehicle component is used for simulating performance parameters of an anti-bee colony unmanned aerial vehicle, and the environment component is used for simulating simulation environment parameters;
in one embodiment, based on the component concept, in software engineering, a reusable software component is taken as an assembly block to construct models of unmanned aerial vehicle components and environment components; for the method, the unmanned plane component and the environment component are basic model components, if complex resistance simulation is required, a large number of basic model components are required to be called, the basic model components can be assembled in a matched mode, different basic model components can interact with each other, and therefore a combined model can be obtained by the plurality of basic model components;
s2, generating a simulation model according to the unmanned aerial vehicle assembly model, the environment assembly model and preset configuration information in an unmanned aerial vehicle controller;
in one embodiment, the preset configuration information includes a route, a waypoint, a position, a speed, an acceleration, a distance, a pitch angle, a yaw angle, a track angle, a sideslip angle, an attack angle, a force, a control moment, a moment of inertia, and the like, and is preset and stored for an operator through a user terminal; wherein the force comprises the total pulling force generated by four propellers of the unmanned aerial vehicle, the pulling force of any one propeller, air pressure, lifting force and resistance; the control moment comprises a rolling control moment, a pitching control moment and a yawing control moment; the threshold value at least comprises a distance threshold value, a track angle threshold value and a yaw angle threshold value;
s3, setting a flight route of unmanned aerial vehicle flight, and inputting the flight route into the simulation model;
in one embodiment, the current flight attitude and flight altitude of the unmanned aerial vehicle, the distance and angle of the relative obstacle, the position of the destination and the like are combined, and after a simulation model is executed, a desired route and a desired track angle are calculated and simulated;
s4, acquiring simulation flight parameters output by the simulation model in real time, and sending a flight mode switching instruction to the unmanned aerial vehicle unit when the simulation flight parameters reach a set threshold value; when the flight parameter reaches the set threshold value, switching the flight mode, and when the flight parameter does not reach the set threshold value, returning to the step S2;
in one embodiment, the method further comprises:
when the unmanned aerial vehicle unit adopts the vertical take-off and landing mode control, executing the stable control of take-off, landing and emergency;
when the unmanned aerial vehicle assembly adopts the fast plane flight mode control, executing self-adaptive coordination control, and expanding a safe flight envelope of the unmanned aerial vehicle cluster;
when the unmanned aerial vehicle is subjected to mixed mode switching control, the pitch angle of the unmanned aerial vehicle is used as a scheduling variable, and the transitional flight process is controlled according to the value of the pitch angle;
in one embodiment, the flight mode mainly comprises three parts, namely a vertical flight mode, a horizontal flight mode and a transition flight mode between the vertical flight mode and the horizontal flight mode; the transition process between the horizontal flight mode and the vertical flight mode is called a mode switching process, and comprises a vertical transition flight mode and a horizontal transition flight mode, wherein the mode switching process is a bridge for realizing vertical take-off and landing and horizontal high-speed cruising; the thresholds include a distance threshold, a track angle threshold, and a yaw angle threshold.
More specifically, in the switching process of each flight mode, in order to ensure the safety and stability of the mode switching process, as shown in fig. 3 to 4:
when the unmanned aerial vehicle assembly is switched from the vertical flight mode to the horizontal flight mode, the required judging conditions need to be satisfied simultaneously:
1) The distance d to the next waypoint is greater than the set distance threshold d * I.e. d.gtoreq.d * ；
2) The expected track angle gamma to the next waypoint is less than the set track angle threshold gamma * I.e. gamma is not more than gamma * ；
3) The expected yaw angle χ to the next waypoint is less than the set yaw angle threshold χ * I.e. χ is not more than χ * 。
When the unmanned aerial vehicle assembly is switched from the horizontal flight mode to the vertical flight mode, the required judging conditions only need to meet any one of the following:
1) The distance d to the next waypoint is smaller than the set distance threshold d * I.e. d < d * ；
2) The expected track angle gamma to the next waypoint is greater than the set track angle threshold gamma * I.e. gamma > gamma * 。
More specifically, regarding the vertical lift mode control technique:
the drone assembly, in vertical flight mode, creates a pressure distribution around it that is a function of air speed, air density, drone shape and attitude. According to the method, a dynamics model based on the anti-bee colony unmanned aerial vehicle is established, as shown in fig. 5, wherein a left module is a controller, a right module in a virtual frame is an unmanned aerial vehicle dynamics model, the model can be divided into an aerodynamic model, a rotary motion model and a translational motion model, a signal bus in the figure comprises the motion parameters (position and gesture) of the freedom degree of the aircraft 6 and derivatives (speed and angular speed) thereof, signals of 12 paths of motion parameters in total, and the pressure can be modeled by using a lifting force, a resistance and a moment, and can be generally expressed as:
wherein F is lift Representing lift force, F drag Represents resistance, M air Representing moment, C L 、C D 、C m S is the wing area, and c is the average chord of the wing.
Generally, the equations of these forces and moments are nonlinear, and when the unmanned aerial vehicle flies at a small attack angle and sideslip angle, the equations can be approximated by linear equations, however, the antifungus unmanned aerial vehicle needs to cover a very large range of vertical take-off and landing and horizontal flying in the flying process, the airframe needs to tilt by 90 degrees, and in order to be able to more accurately establish the relationship between lift, resistance and attack angle in the range, the lift and resistance expressions in the above equation are rewritten as follows:
where α is the angle of attack, when the angle of attack exceeds the threshold for stall condition, the wing appears as a flat plate whose lift coefficient can be expressed as:
C L，plate ＝2sign(α)sin 2 αcosα
thus, in the simulation the following lift model is used, which contains the normal linear lift action and the lift action in stall condition:
in the method, in the process of the invention,
wherein M and alpha 0 The demarcation point and conversion rate of the blend function are determined as positive constants.
And the linear lift coefficient portion may be expressed using the following equation:
further, AR.b 2 And S is the aspect ratio of the wing, b is the span, and S is the wing area.
When the lift model is adopted, the relation curve between the lift coefficient and the attack angle is shown in fig. 6, so that the aerodynamic lift can be accurately described in a large attack angle range, and the simulation requirement of the embodiment is met; the flight control system of the anti-bee colony unmanned aerial vehicle is designed by taking the nonlinear model as an object, the linearization of the nonlinear object and decoupling between channels can be effectively realized by adopting a dynamic inverse control algorithm, the nonlinearity of the controlled object is eliminated, global linearization is formed, visual understanding of the attitude of the unmanned aerial vehicle is facilitated, and the unmanned aerial vehicle has good control performance and anti-interference performance, and the control precision, robustness and self-adaption of the aircraft control system and the attitude adjustment and flight stability of the unmanned aerial vehicle are effectively improved.
Coefficient of resistance C D Is also a nonlinear function of angle of attack α, and consists of two parts, induced resistance and waste resistance, respectively. The waste resistance being caused by shear stresses caused by air drawn across the wing, the coefficient of waste resistance being substantially constant, determined by C Dp And (3) representing. For small angles of attack, the induced drag is proportional to the square of the lift. Simultaneously combining the induced resistance and the waste resistance to obtain:
where e is an Ostwald efficiency factor, and is usually preferably 0.8 to 1.0.
The above model can provide a more accurate aerodynamic profile over a larger range of angles of attack. The aerodynamic generated pitching moment is also typically a nonlinear function of the angle of attack and must be determined by a specific wind tunnel or flight test. In the preliminary simulation model, the following linear model is used:
the thrust required by the unmanned aerial vehicle during flight and the control moment required by the attitude stability control are all provided by four motors, and the expression is as follows:
wherein F is c Representing the total tension produced by the four propellers, L c Representing roll control moment, M c Representing pitch control moment, N c Representing yaw control moment, T i For the tension of the ith propeller, Ω i For the rotation speed of the ith propeller, l represents the distance from the motor shaft to the longitudinal axis of the unmanned aerial vehicle, J r Is the gyro effect coefficient of the propeller, r is the yaw angular velocity of the unmanned aerial vehicle, Q is the pitch angular velocity of the unmanned aerial vehicle, and Q i The reactive torque generated for the ith propeller.
Further, building an attitude control system model based on the unmanned aerial vehicle according to three flight modes of the unmanned aerial vehicle, and performing decoupling and linearization processing on the attitude control system model to obtain an actual attitude angle and a target attitude angle of the unmanned aerial vehicle; the gesture control system model at least comprises a dynamics model and a kinematics model; neglecting the curvature of the earth, under the assumption of a planar earth, the 6 degrees of freedom kinematic model equation of the antifungus unmanned aerial vehicle is as follows:
wherein u, v and w respectively represent velocity components of the unmanned aerial vehicle in x, y and z directions under a body coordinate system, m is the mass of the unmanned aerial vehicle,p, q, r denote the rotational angular velocity along the body axis, I x 、I y 、I z For the rotational inertia of the unmanned aerial vehicle along the x, y and z directions, F x 、F y 、F z Force components along x, y and z directions, L, M, N moment components along body axis direction, p N 、p E H is the north and east positions and the altitude information of the unmanned aerial vehicle, B is the rotation matrix from the north-east coordinate system to the unmanned aerial vehicle system, g x 、g y 、g z Representing local gravitational acceleration g 0 Projection in the x, y, z direction system of the drone is shown as follows:
in particular, for vertical flight modes, the kinematic model expressed by vertical euler angles is as follows:
in the method, in the process of the invention,
define horizontal Euler angle c as X b Roll angle of axis, θ is about Y b Pitch angle of axis, ψ is the angle around Z b Yaw angle of the shaft; vertical Euler angle phi v Is that
Roll angle of shaft, θ v For winding->
Pitch angle of shaft, ψ v For winding the shaft->
Is>
For the rotational acceleration of the unmanned aerial vehicle, +.>
Is the pitch angle acceleration of the unmanned aerial vehicle, +.>
Yaw acceleration for unmanned aerial vehicle, I xx 、I yy 、I zz The moment of inertia of the unmanned aerial vehicle in the x, y and z directions are respectively.
In the anti-bee colony unmanned aerial vehicle cluster, due to the requirement of formation configuration, the speed and the gesture instruction of a weapon unit need to be frequently adjusted according to formation change, however, for the air unmanned aerial vehicle cluster, obvious coupling exists between the track angle and the speed, and only a power compensation system is designed, the coupling between the track angle and the speed can be released, so that the accurate control of the track is realized. To solve the problem of coupling between the track angle and the speed, the invention provides a total energy comprehensive flight attitude control method of an anti-bee colony unmanned aerial vehicle based on a particle swarm optimization algorithm, which has good control performance.
Total energy control system as shown in fig. 7, the total energy of the antifungus drone when flying can be expressed as follows:
wherein E is T The energy-saving system is the total energy of the unmanned plane and consists of potential energy and kinetic energy, m is mass, g is gravitational acceleration, V is flying speed, and h is flying height.
The two sides of the unmanned aerial vehicle are differentiated and then subjected to dimensionless treatment to obtain the total energy change rate of the unmanned aerial vehicle
The method comprises the following steps:
the tangential force equation for unmanned centroid motion can be expressed as:
wherein T is engine thrust, and gamma is track angle; d is aerodynamic resistance, and the method can be used for finishing the above materials:
therefore, the total energy change rate of the unmanned aerial vehicle can be changed by the engine thrust, and the thrust increment delta T required for changing the flight attitude of the unmanned aerial vehicle is as follows:
in the method, in the process of the invention,
for the desired total energy rate of change +.>
And the actual rate of energy change +.>
The difference, i.e.)>
It can be seen that the change in thrust force changes the rate of change of energy of the unmanned aerial vehicle in a certain proportion. In order to achieve better attitude control effect and eliminate steady-state errors, a proportional integral control law can be adopted to form a control quantity of thrust based on the deviation of the energy change rate, and the expression is as follows:
wherein T is c K for changing the engine thrust required by the attitude of the unmanned aerial vehicle TP Is a proportionality coefficient, K TI Is an integral coefficient. The control law is used for enabling deviation of total energy change rate caused by change of flight attitude
And tends to zero.
The total energy change rate describes the total trend of change in potential energy and kinetic energy of the aircraft. To describe the proportional relationship between the two, the distribution ratio of the total energy is defined as follows:
the energy distribution rate converts the kinetic energy and potential energy of the aircraft to each other through a pitch attitude loop. Considering the damping items required for improving the quality of the short-period motion of the airplane comprehensively, the control law similar to the thrust is adopted to represent the control quantity of the thrust differential, and the control quantity is as follows:
wherein: delta T is the difference in thrust between the propellers; k (K) EP Is a proportionality coefficient; k (K) EI Is an integral coefficient;
distribution rate D for desired total energy c And the actual energy distribution rate +.>
The difference, i.e.)>
K θ And K q The feedback gains for pitch angle and pitch rate, respectively. The control law has the function of enabling the deviation of the energy distribution rate to be close to zero and improving the quality of the short-period gesture of the unmanned aerial vehicle.
Determining an attitude angle deviation value to be adjusted according to a target attitude angle to be adjusted of the unmanned aerial vehicle and a current actual attitude angle of the unmanned aerial vehicle, and establishing an Euler attitude model and an error model according to the attitude angle deviation value, wherein the error model has very important significance for optimizing a target and optimizing a controller parameter, and a time weighted error absolute value integral index is selected to serve as an adaptability function:
wherein e (t) is the calculated deviation value after the current position of the particle is brought into the error model, e (t) =y (t) -y (infinity), which is different from the conventional error definition because y (infinity) +. c (t), if according to e (t) =y (t) -y c (t) defining the deviation value, eventually making all the integrals infinite and meaningless, also proves the effectiveness of the model in reducing errors.
Considering the stability of the flight attitude of the unmanned aerial vehicle, the unmanned aerial vehicle is not expected to instantaneously execute excessive actions, and meanwhile, the change rate of the unmanned aerial vehicle is expected to be smaller as much as possible, and the actions are gentle, so the fitness function is changed into the following form:
where δ is the control amount, and δ' is the rate of change of the control amount.
Parameter K in anti-swarm unmanned aerial vehicle attitude control system by adopting particle swarm optimization algorithm TP 、K TI 、K EP And K EI Optimizing, setting particles with number of 100, iteration number of 200 and parameter optimization range of (0, 2)]The optimization result is K TP ＝0.6315，K TI ＝0.2338，K EP ＝1.6983，K EI = 0.1362. Meanwhile, step instructions of the flying speed and the track climbing angle are given to the unmanned aerial vehicle in the cruising state, and simulation comparison results are shown in fig. 8 to 9.
By comparing simulation results before and after optimization, we can clearly see that compared with artificial experience parameters, the parameters optimized by adopting the particle swarm optimization algorithm have the advantages of small overshoot, fast convergence and high steady-state precision, and the designed method can simultaneously and accurately control the flight speed and the track climbing angle, thereby meeting the multivariable integrated coordination control of the track and speed parameters of the weapon unit. In order to further verify the effectiveness of the designed comprehensive flight control method of the weapon unit based on total energy, continuous change of the flight speed is carried out aiming at a comprehensive flight control system of the weapon unit in a certain long-voyage space, and meanwhile, the simulation of the flight height is maintained. The control parameter is K TP ＝0.5217，K TI ＝0.2135，K EP ＝1.3217，K EI = 0.1127. As shown in fig. 10 to 11, as the target flying speed increases, the altitude of the anti-bee colony unmanned aerial vehicle fluctuates due to the increase of the lift force caused by the increase of the speed, and can be quickly recovered to the target altitude under the action of the total energy control method, and the change range is less than 0.5 meter. The accelerator can quickly respond along with the change of the speed command and is stabilized at a new balance position after the speed is stabilized to a target value; the pitch angle is reduced to reduce the lift coefficient of the attack angle, and the total lift is kept unchanged under the condition of increasing the speed, so that the flying height is kept unchanged. From the above simulation results, it can be concluded that:the attitude control system can enable the flying speed to track the command value faster, the steady-state precision is high, and meanwhile the fluctuation of the flying height is small.
Robustness and stability judgment about unmanned aerial vehicle control system model:
the transition between the horizontal flight mode and the vertical flight mode is called a mode switching process, including the vertical transition flight mode and the vertical transition flight mode, and the mode switching process is a bridge for realizing vertical take-off and landing and horizontal high-speed cruising. In the transitional flight process, the pitch angle of the anti-swarm unmanned aerial vehicle is in a large-angle maneuver of +/-90 degrees, and the airspeed is also in a large change, so that the dynamic model of the unmanned aerial vehicle is in a severe change, and the design difficulty of the transitional flight mode controller is increased due to the nonlinearity and the strong coupling of the system. The working state of the anti-bee colony unmanned aerial vehicle is greatly changed in the transitional flight process, so that the inner loop adopts a control technology based on nonlinear dynamic inverse in the mode switching process.
More specifically, with respect to fast fly-by-fly mode control techniques:
the anti-bee colony unmanned aerial vehicle flies according to a track planned in advance or in real time under a fast plane flying mode, the problem that a path is accurately followed in a wind field and the problem that the flying safety is improved in the process of multi-machine cooperation tight formation flying are solved, the self-adaptive coordination control and performance optimization of each unmanned aerial vehicle under the condition of a high dynamic complex environment are realized, the safe flying envelope of the unmanned aerial vehicle is expanded, and the higher coordination performance index and space-time constraint requirement of a cluster system are realized.
In the process, the guidance system plays a vital role, and as shown in fig. 12, the guidance system outputs a desired track angle according to the current flight state of the unmanned aerial vehicle and a preset route point; the guidance strategies corresponding to the horizontal flight mode and the vertical flight mode are different, the guidance of the horizontal flight mode is divided into two relatively independent parts, namely lateral guidance and longitudinal guidance, and the guidance of the vertical flight mode is implemented according to the guidance strategy of multiple rotors.
For the altitude control problem, it is assumed that the control law in the climbing and descending region will enable the drone to ascend or descend to the altitude maintenance region; in the altitude holding area, the elevation of the drone is controlled using the pitch attitude. Assuming that the continuous closed loop has been properly implemented, the outer loop dynamics equation can be expressed as:
defining the height error as:
e h ·h-h d ＝h-h c
the method can obtain the following steps:
the application of the final value theorem is available:
Wherein h is the height of the unmanned aerial vehicle, e h Is an oswald efficiency factor.
Analysis shows that constant disturbances will be removed. Therefore, the embodiment can track a constant altitude and an inclined straight line path, so that the flying speed tracks the command value faster, has zero steady-state altitude error, and has small fluctuation of the flying altitude.
More specifically, with respect to the hybrid mode switching control technique:
in the mode switching process, the pitch angle of the unmanned aerial vehicle unit is used as a scheduling variable, the value of the pitch angle can be measured in real time, and a corresponding local controller is called according to the value of the pitch angle to complete the whole transitional flight process so as to divide the whole process into two stages, as shown in fig. 13:
at pitch angle theta > theta * When the vertical flight mode is adopted, the pitch angle theta is smaller than theta * A horizontal flight mode is used. In order to ensure the safety and stability of the hybrid mode switching process, when the hybrid mode is switched from the vertical take-off and landing mode to the fast fly-down mode, the required judgment conditions also need to meet the condition that the distance from the next waypoint is larger than the set threshold value.
When the Euler attitude model of the unmanned aerial vehicle is processed, the Euler attitude model is generally divided into a longitudinal subsystem and a lateral subsystem, and obviously, the state quantities of the lateral subsystem of the unmanned aerial vehicle, such as a rolling angle, a yaw angle, a sideslip angle and the like, are kept unchanged in the transitional flight process, and only the pitch angle, the airspeed and the attack angle of the lateral subsystem are changed. In order to facilitate analysis and design of the transition flight mode controller, a mathematical model of the transition flight mode needs to be simplified, here we ignore the lateral subsystem model of the unmanned aerial vehicle to treat the model as an interference amount, and only analyze the longitudinal subsystem model of the unmanned aerial vehicle, so that the six-degree-of-freedom model of the unmanned aerial vehicle can be simplified into a two-degree-of-freedom model. From the simplified model we can consider the whole transitional flight process as being completed in one two-dimensional plane, i.e. the conventional longitudinal plane. In the whole transitional flight process, the pitch angle and the airspeed of the unmanned aerial vehicle are greatly changed, and in order to ensure the smooth implementation of the transitional flight process, a wide airspace without barriers around must be selected at a switching point. In the transitional flight process, we mainly pay attention to the longitudinal movement of the unmanned aerial vehicle, and then further analyze the longitudinal model of the unmanned aerial vehicle, wherein the longitudinal dynamics model is as follows:
mV a ＝D+Tcosa-mgsing
mV a g＝L+Tsina-mgcosg
q v ＝G 2 pr+T m /J y
wherein L, D, T is respectively the lift, the resistance and the pull of the propeller, g is the flight path angle and g=q-a, T m Is the pitching moment.
From the analysis of the system dynamics model in the transitional flight process, the pitch angle and the airspeed are mainly controlled in the transitional flight process, the roll angle and the yaw angle are relatively kept constant in the transitional flight process, and the key of transitional flight control is to control the pitch angle q and the airspeed V a . The transition flight controller does not adopt a new controller structure, but is controlled by the state scheduling of the pitch angle on the basis of the original vertical flight controller and the horizontal flight controller, so that the design difficulty of the controller is simplified.
In order to verify the method described in this embodiment, a flight path shown in fig. 14 is provided, in which 11 is a reference path, 12 is a vertical take-off path, 13 is a transition flight path, 14 is a horizontal flight path, and 15 is a vertical landing path, the method is firstly performed by vertically taking off, climbing up to a safe height of 20m in a vertical flight mode, then performing level flight, climbing up to a height of 100m, and simultaneously flying up to a target point outside 4km, in this process, setting an initial lateral deviation of 10m, and switching to the vertical flight mode and landing when approaching to the upper air of the destination. The change curves of the flying height and the north position of the unmanned plane with time are shown in fig. 15 and 16, wherein in fig. 15, 21 is a vertical take-off track, 22 is a transition flying track, 23 is a horizontal flying track, and 24 is a vertical landing track; in fig. 16, 31 is a vertical take-off trajectory, 32 is a transition flight trajectory, 33 is a horizontal flight trajectory, and 34 is a vertical landing trajectory; . Comparing with the preset flight path, in the horizontal flight mode, the steady state error of the altitude tracking is less than 1m, and the steady state value of the lateral deviation of the linear flight path tracking approaches zero, which indicates the effectiveness of the method in the embodiment.
The embodiment solves the technical problems of vertical take-off and landing mode control technology, fast flat flight mode control technology and mixed mode switching control in the traditional unmanned aerial vehicle flight control method; the unmanned aerial vehicle is realized through the vertical flight mode and the vertical take-off and landing function, the long-endurance and quick cruising functions of the unmanned aerial vehicle are realized through the horizontal flight mode, and the multifunctional integrated structure is realized.
In one embodiment, as shown in fig. 2, an anti-bee colony unmanned aerial vehicle aircraft control system is provided, and no steerable aerodynamic surface (such as ailerons, elevators and rudders) is included, the main structure of the anti-bee colony unmanned aerial vehicle aircraft control system adopts a traditional four-rotor wing plus fixed wing combination, a lifting surface is installed on a motor arm of each rotor wing, when the unmanned aerial vehicle horizontally flies, the additional wing takes an X-shaped configuration and provides lifting force, and the thrust required by the unmanned aerial vehicle during the flight and the moment required by the attitude stabilization control are provided by four motors. In this embodiment, the aircraft control system mainly includes:
the system comprises a building module, a simulation module and a simulation module, wherein the building module is used for building a model of an unmanned aerial vehicle component and an environment component, the unmanned aerial vehicle component is used for simulating performance parameters of the anti-bee colony unmanned aerial vehicle, and the environment component is used for simulating simulation environment parameters;
the model generation module is used for generating a simulation model according to the unmanned aerial vehicle assembly model, the environment assembly model and preset configuration information in the unmanned aerial vehicle controller;
the guidance module is used for setting a flight route of unmanned aerial vehicle flight and inputting the flight route into the simulation model;
and the simulation analysis module is used for collecting the simulation flight parameters output by the simulation model in real time, and sending a flight mode switching instruction to the unmanned aerial vehicle assembly when the simulation flight parameters reach a set threshold value.
The embodiment realizes the functions of taking off and landing of the unmanned aerial vehicle and the stable control under emergency conditions through a vertical take-off and landing mode control technology; the self-adaptive coordination control and the performance optimization of the unmanned aerial vehicle cluster under the high-dynamic complex environmental condition are realized through a rapid flat flight mode control technology, and the safe flight envelope of the flight platform is expanded; and (3) taking the pitch angle of the unmanned aerial vehicle as a scheduling variable through a mixed mode switching control technology, and calling a corresponding local controller according to the value of the pitch angle to complete the whole transitional flight process. The four-rotor-wing-reinforced fixed wing combination can realize the vertical take-off and landing functions of the multi-rotor unmanned aerial vehicle, and has the advantages of long voyage and quick cruising of the fixed-wing unmanned aerial vehicle, thereby meeting the requirement of executing special tasks in a complex environment.
In one embodiment, as shown in FIG. 14, a computer device is provided, which may be a server. The computer device includes a processor, a memory, a network interface, and a database connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The database of the computer device is for storing basic model component data. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program, when executed by the processor, implements a flight control method for a antifungus drone.
It will be appreciated by those skilled in the art that the structure shown in fig. 14 is merely a block diagram of a portion of the structure associated with the present application and is not limiting of the computer device to which the present application applies, and that a particular computer device may include more or fewer components than shown, or may combine certain components, or have a different arrangement of components.
In an embodiment, a computer device is provided, comprising a memory storing a computer program and a processor implementing the steps of the method of the above embodiments when the computer program is executed:
s1, creating a model of an unmanned aerial vehicle component and an environment component, wherein the unmanned aerial vehicle component is used for simulating performance parameters of an anti-bee colony unmanned aerial vehicle, and the environment component is used for simulating simulation environment parameters;
s2, generating a simulation model according to the unmanned aerial vehicle assembly model, the environment assembly model and preset configuration information in an unmanned aerial vehicle controller;
s3, setting a flight route of unmanned aerial vehicle flight, and inputting the flight route into the simulation model;
s4, acquiring simulation flight parameters output by the simulation model in real time, and sending a flight mode switching instruction to the unmanned aerial vehicle unit when the simulation flight parameters reach a set threshold value; the flight mode includes: vertical flight mode, horizontal flight mode, and transitional flight mode.
In one embodiment, a computer readable storage medium is provided, on which a computer program is stored which, when executed by a processor, implements the steps of the method of the above embodiments.
Those skilled in the art will appreciate that implementing all or part of the above described methods may be accomplished by way of a computer program stored on a non-transitory computer readable storage medium, which when executed, may comprise the steps of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in the various embodiments provided herein may include non-volatile and/or volatile memory. The nonvolatile memory can include Read Only Memory (ROM), programmable ROM (PROM), electrically Programmable ROM (EPROM), electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double Data Rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous Link DRAM (SLDRAM), memory bus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), among others.
The technical features of the above embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.
The above examples merely represent a few embodiments of the present application, which are described in more detail and are not to be construed as limiting the scope of the invention. It should be noted that it would be apparent to those skilled in the art that various modifications and improvements could be made without departing from the spirit of the present application, which would be within the scope of the present application. Accordingly, the scope of protection of the present application is to be determined by the claims appended hereto.
Claims (8)
1. A method of controlling an aircraft of a antifungus drone, the method comprising:
creating a model of an unmanned aerial vehicle component and an environment component, wherein the unmanned aerial vehicle component is used for simulating performance parameters of the anti-bee colony unmanned aerial vehicle, and the environment component is used for simulating environment parameters;
generating a simulation model according to the unmanned aerial vehicle assembly model, the environment assembly model and preset configuration information in an unmanned aerial vehicle controller;
setting a flight route of unmanned aerial vehicle flight, and inputting the flight route into the simulation model;
collecting simulation flight parameters output by the simulation model in real time, and sending a flight mode switching instruction to the unmanned aerial vehicle assembly when the simulation flight parameters reach a set threshold value; the flight mode includes: a vertical flight mode, a horizontal flight mode, and a transitional flight mode;
the preset configuration information at least comprises a route, a route point, a position, a speed, acceleration, distance, pitch angle, yaw angle, track angle, sideslip angle, attack angle, force, control moment and moment of inertia; wherein,,
the force at least comprises the total pulling force generated by four propellers of the unmanned aerial vehicle, the pulling force of any propeller, air pressure, lifting force and resistance;
the control moment at least comprises a rolling control moment, a pitching control moment and a yawing control moment;
the threshold value at least comprises a distance threshold value, a track angle threshold value and a yaw angle threshold value;
the simulation flight parameters simultaneously satisfy when the unmanned aerial vehicle assembly is switched from the vertical flight mode to the horizontal flight mode: the distance to the next preset waypoint is greater than the set distance threshold, the desired track angle to the next preset waypoint is less than the set track angle threshold, and the desired yaw angle threshold to the next preset waypoint is less than the set yaw angle threshold.
2. The method of claim 1, wherein the simulation flight parameters are satisfied when the unmanned aerial vehicle is switched from a horizontal flight mode to a vertical flight mode: the distance to the next preset waypoint is less than the set distance threshold or the desired track angle to the next preset waypoint is greater than the set track angle threshold.
3. The method for controlling an aircraft by using an anti-bee colony unmanned aerial vehicle according to claim 1, wherein the unmanned aerial vehicle performs vertical flight mode control by using vertical take-off and landing mode control, the unmanned aerial vehicle performs horizontal flight mode control by using rapid horizontal flight mode control, and the unmanned aerial vehicle performs transition flight mode control by using hybrid mode switching control.
4. The method for controlling the aircraft of the antifungus unmanned aerial vehicle according to claim 3, wherein the unmanned aerial vehicle is further required to establish a dynamic model and a kinematic model based on the antifungus unmanned aerial vehicle in a vertical flight mode; analyzing the functional relation between the pressure born by the unmanned aerial vehicle component and the air speed, the air density, the shape and the gesture of the unmanned aerial vehicle according to the dynamic model; and analyzing the action type and the motion trail of the unmanned aerial vehicle component according to the kinematic model.
5. A method of controlling an aircraft of a antifungus drone of claim 3, further comprising:
when the unmanned aerial vehicle unit adopts vertical take-off and landing mode control, stable control under the conditions of take-off, landing and emergency is executed;
when the unmanned aerial vehicle assembly adopts the rapid plane flight mode control, executing self-adaptive coordination control, and expanding a safe flight envelope of the unmanned aerial vehicle cluster;
when the unmanned aerial vehicle is subjected to mixed mode switching control, the pitch angle of the unmanned aerial vehicle is used as a scheduling variable, and the transitional flight process is controlled according to the value of the pitch angle.
6. An anti-swarm unmanned aerial vehicle aircraft control system, the system comprising:
the system comprises a building module, a simulation module and a simulation module, wherein the building module is used for building a model of an unmanned aerial vehicle component and an environment component, the unmanned aerial vehicle component is used for simulating performance parameters of the anti-bee colony unmanned aerial vehicle, and the environment component is used for simulating simulation environment parameters;
the model generation module is used for generating a simulation model according to the unmanned aerial vehicle assembly model, the environment assembly model and preset configuration information in the unmanned aerial vehicle controller; the preset configuration information at least comprises a route, a route point, a position, a speed, acceleration, distance, pitch angle, yaw angle, track angle, sideslip angle, attack angle, force, control moment and moment of inertia; the force at least comprises total pulling force generated by four propellers of the unmanned aerial vehicle, pulling force of any propeller, air pressure, lifting force and resistance; the control moment at least comprises a rolling control moment, a pitching control moment and a yawing control moment; the threshold values include at least a distance threshold value, a track angle threshold value, and a yaw angle threshold value; the simulation flight parameters simultaneously satisfy when the unmanned aerial vehicle assembly is switched from the vertical flight mode to the horizontal flight mode: the distance to the next preset waypoint is greater than a set distance threshold, the expected track angle to the next preset waypoint is less than a set track angle threshold, and the expected yaw angle threshold to the next preset waypoint is less than a set yaw angle threshold;
the guidance module is used for setting a flight route of unmanned aerial vehicle flight and inputting the flight route into the simulation model;
and the simulation analysis module is used for collecting the simulation flight parameters output by the simulation model in real time, and sending a flight mode switching instruction to the unmanned aerial vehicle assembly when the simulation flight parameters reach a set threshold value.
7. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor implements the steps of the method of any of claims 1 to 5 when the computer program is executed.
8. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the method according to any one of claims 1 to 5.
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