CN113985918A - Unmanned aerial vehicle intensive formation modeling method and system considering pneumatic coupling - Google Patents
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Abstract
The invention discloses an unmanned aerial vehicle intensive formation modeling method and system considering pneumatic coupling, wherein a long aircraft automatic pilot model is constructed according to the flight state of a long aircraft; a wing plane automatic pilot model under the influence of the pneumatic coupling relationship of a lead plane and a wing plane is established; processing a pilot plane automatic pilot model and a wing plane automatic pilot model to obtain a relative kinematics model between the pilot plane and the wing plane; processing the relative kinematics model to obtain a relative position relationship model between a captain plane and a bureaucratic plane; dividing the relative kinematics model into different channels according to the result of the decoupling relative kinematics equation; constructing a controller model of intensive formation according to the divided interval instructions among different channels; and combining a pilot automatic pilot model, a wing automatic pilot model, a relative kinematics model, a relative position relation model and a controller model to construct a control model of the intensive formation. The invention can effectively improve the stability and dynamic characteristics of formation flight.
Description
Technical Field
The invention belongs to the field of control of aviation aircrafts, and relates to an unmanned aerial vehicle dense formation modeling method and system considering pneumatic coupling.
Background
The unmanned aerial vehicle has the characteristics of strong nonlinearity, strong coupling characteristic and the like in flight, the flight environment is complex, and factors such as delay exist in control response. The unmanned aerial vehicle formation control flight not only faces the difficult problem faced by the unmanned aerial vehicle control, but also overcomes the problems of coupling, relative position keeping, formation transformation, collision prevention and the like among formations.
The aerodynamic relationship among unmanned aerial vehicle formation is fully utilized, a good control method is applied, and the key of design is to maintain the stability and good dynamic characteristics of a formation flight control system.
When the unmanned aerial vehicle is considered to be in loose formation flight, the pneumatic coupling effect between formations can be ignored. However, as the aviation systems of various countries are improved and the task environments are more and more complex, the task requirements are difficult to meet by the loose formation flying. Therefore, the close formation of unmanned aerial vehicles becomes a research hotspot. When carrying out close formation research, the coupling influence of the wake of a longplane on a bureaucratic plane needs to be considered.
Disclosure of Invention
The invention aims to solve the problems in the prior art, and provides an unmanned aerial vehicle dense formation modeling method and system considering pneumatic coupling, which can effectively improve the stability and good dynamic characteristics of a flight control system.
In order to achieve the purpose, the invention adopts the following technical scheme to realize the purpose:
an unmanned aerial vehicle dense formation modeling method considering pneumatic coupling comprises the following steps:
constructing a long aircraft autopilot model according to the flight state of the long aircraft;
a wing plane automatic pilot model under the influence of the pneumatic coupling relationship of a lead plane and a wing plane is established;
processing a pilot plane automatic pilot model and a wing plane automatic pilot model to obtain a relative kinematics model between the pilot plane and the wing plane;
processing the relative kinematics model to obtain a relative position relationship model between a captain plane and a bureaucratic plane;
dividing the relative kinematics model into different channels according to the result of the decoupling relative kinematics equation;
constructing a controller model of intensive formation according to the divided interval instructions among different channels;
and combining a pilot automatic pilot model, a wing automatic pilot model, a relative kinematics model, a relative position relation model and a controller model to construct a control model of the intensive formation.
The invention is further improved in that:
the flight state of a long aircraft includes speed, heading, and altitude.
The method for constructing the long-distance automatic pilot model specifically comprises the following steps:
wherein v, ψ, h represent the speed, heading and altitude of the aircraft, respectively; the subscript c denotes the formation control instruction, τvIs a velocity time constant, τψIs a course time constant, τhIs a height time constant.
The pneumatic coupling relation of the fixed planes and the fixed planes is the washing force caused by the washing flow of the fixed planes to the fixed planes; the washing force causes the change of the incidence angle of the wing plane, which leads to the rotation and the change of the magnitude of the lift force and the drag force vector; according to the root of the generation of the coupling factors, the eddy current influence is simplified and calculated, and the influence is expressed as the changes of wing plane lift force L, resistance D and side force Y;
wherein,
is dynamic pressure; s is the wing area and C is the lift coefficient.
The automatic wing plane pilot model is:
wherein x, y, z are error amounts of the formation interval relative to the nominal interval.
The relative kinematic model between a nominator and a bureaucratic is:
where ξ is an intermediate variable, expressed in a matrix form:
U＝[vwc ψwc hwc vL ψL hLc]T (7)
the specific steps for dividing the relative kinematic model into different channels are as follows:
according to the natural structural relationship of the formation motion of the unmanned aerial vehicles, the motion of the unmanned aerial vehicles is divided into three groups:
an X channel:
a Y channel:
a Z channel:
the controller model for constructing the dense formation is as follows: firstly, designing a controller model for a lateral Y channel and a height Z channel, and then designing a longitudinal X channel;
the controller model is as follows:
in the formula, VwcFor controller speed command, psiwcIs a heading command H of the controllerwcFor controller height commands, KXp、KYp、KZpIs a proportionality coefficient, KXI、KYI、KxIIs an integral coefficient, vE、ψERepresenting speed, heading error, kx、ky、kzControlling gain for directional deviation, Δ xE、ΔyE、ΔzEAre the spacing distance errors in the respective x, y, z directions.
An unmanned aerial vehicle dense formation modeling system considering pneumatic coupling, comprising:
the first construction module is used for constructing a long-machine automatic pilot model according to the flight state of the long machine;
a second building module for building a wing autopilot model under the influence of the aerodynamic coupling of a farm machine and a wing machine;
the first model processing module is used for processing a farm aircraft autopilot model and a wing aircraft autopilot model and acquiring a relative kinematics model between a farm aircraft and a wing aircraft;
the second model processing module is used for processing the relative kinematics model to obtain a relative position relationship model between a captain plane and a bureaucratic plane;
the dividing module is used for dividing the relative kinematics model into different channels according to the result of decoupling the relative kinematics model;
a third construction module for constructing a densely-queued controller model according to the divided interval instructions between the different channels;
the combination module is used for combining a pilot autopilot model, a wing autopilot model, a relative kinematics model, a relative position relationship model and a controller model to construct a control model of the intensive formation.
Compared with the prior art, the invention has the following beneficial effects:
the invention discloses an unmanned aerial vehicle intensive formation modeling method and system considering pneumatic coupling, and under the condition that long aircraft wake flow has influence on wing aircraft flight when unmanned aerial vehicles are intensively formed and fly, the unmanned aerial vehicle intensive formation modeling method provided by the invention improves the problems of in-team position change and inter-aircraft collision avoidance in the unmanned aerial vehicle intensive formation, and improves the formation reliability and safety when facing a complex flying environment. Meanwhile, when the model is established, the unmanned aerial vehicle autopilot in the formation adopts an improved second-order unmanned aerial vehicle autopilot model considering starting coupling. Compared with a first-order autopilot model, the second-order autopilot model not only enables course and altitude responses to be obviously improved, but also is more practical than the response of a first-order autopilot model with a large time constant.
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In order to more clearly explain the technical solutions of the embodiments of the present invention, the drawings needed to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present invention, and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained according to the drawings without inventive efforts.
FIG. 1 is a flow chart of a method for modeling a dense formation of unmanned aerial vehicles considering pneumatic coupling according to the present invention;
FIG. 2 is a simplified model diagram of eddy currents;
fig. 3 is an analysis diagram of the forces of a wing;
fig. 4 is a diagram of the relative movements of a lead plane and a wing plane;
FIG. 5 is a diagram of an intensive formation flight control model of unmanned aerial vehicles considering pneumatic coupling according to the present invention;
fig. 6 is a structural diagram of the unmanned aerial vehicle dense formation modeling system considering pneumatic coupling of the invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. The components of embodiments of the present invention generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations.
Thus, the following detailed description of the embodiments of the present invention, presented in the figures, is not intended to limit the scope of the invention, as claimed, but is merely representative of selected embodiments of the invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, it need not be further defined and explained in subsequent figures.
In the description of the embodiments of the present invention, it should be noted that if the terms "upper", "lower", "horizontal", "inner", etc. are used for indicating the orientation or positional relationship based on the orientation or positional relationship shown in the drawings or the orientation or positional relationship which is usually arranged when the product of the present invention is used, the description is merely for convenience and simplicity, and the indication or suggestion that the referred device or element must have a specific orientation, be constructed and operated in a specific orientation, and thus, cannot be understood as limiting the present invention. Furthermore, the terms "first," "second," and the like are used merely to distinguish one description from another, and are not to be construed as indicating or implying relative importance.
Furthermore, the term "horizontal", if present, does not mean that the component is required to be absolutely horizontal, but may be slightly inclined. For example, "horizontal" merely means that the direction is more horizontal than "vertical" and does not mean that the structure must be perfectly horizontal, but may be slightly inclined.
In the description of the embodiments of the present invention, it should be further noted that unless otherwise explicitly stated or limited, the terms "disposed," "mounted," "connected," and "connected" should be interpreted broadly, and may be, for example, fixedly connected, detachably connected, or integrally connected; can be mechanically or electrically connected; they may be connected directly or indirectly through intervening media, or they may be interconnected between two elements. The specific meanings of the above terms in the present invention can be understood by those skilled in the art according to specific situations.
The invention is described in further detail below with reference to the accompanying drawings:
referring to fig. 1, fig. 1 discloses a pneumatic coupling modeling method for airplane multi-airplane intensive formation, which specifically comprises the following steps:
the intensive formation strategy in the modeling method of the invention adopts a formation mode of leading-following, and has a captain aircraft and a plurality of bureaucratic aircraft, the flight of the captain aircraft is completely independent of the bureaucratic aircraft, and the bureaucratic aircraft have the same flight quality and adopt the same autopilot.
The steps for establishing the airplane intensive formation modeling considering the aerodynamic coupling are as follows:
the method comprises the following steps: and constructing an autopilot model of the long aircraft according to the flight state of the long aircraft.
The automatic pilot of the pilot aircraft in the intensive formation adopts a conventional mode to establish a mathematical model, the flight of the automatic pilot is not influenced by the wake flow of the wing aircraft, and the design of the controller adopts the design of the flight control law of the conventional unmanned aerial vehicle. Assuming that each aircraft in the formation is the same, in order to describe the real aircraft pilot model more accurately, the automatic pilot which keeps the formation flying stably adopts a second-order model.
Specifically, the established long-range automatic pilot model is shown as formula (1):
step two: pneumatic coupling relationship.
Vortex model a simplified model of horseshoe vortices was used to study the effect of wing machines in tight formation on the vortices at the tips of the long wings, as shown in figure 2. In fig. 2, b is the span of the wing,
indicating the longitudinal relative distance between the two machines,
the transverse relative distance between the two machines is shown, and gamma is the strength of the eddy current generated by the long machine.
The basic horseshoe vortex model is used for replacing the unmanned plane in the formation by utilizing the lifting line theory. The stress analysis of a wing of a wing-wing is carried out on the basis of a simplified model of a horseshoe vortex, and the specific analysis is shown in figure 3. Alpha is the airplane incidence angle without the influence of the washing flow, delta alpha is the wing airplane incidence angle increment caused by the washing flow on the pilot plane, W is the washing flow speed, v is the wing airplane speed without the influence of the vortex flow, v ' is the speed after the influence of the washing flow, L is the lift force without the influence of the vortex flow, L ' is the lift force generated by the influence of the washing flow, delta L is the lift force increment, D is the lift force without the influence of the vortex flow, D ' is the lift force generated by the influence of the washing flow, and delta D is the lift force increment.
The pneumatic coupling relation of the fixed planes and the fixed planes is the washing force caused by the washing flow of the fixed planes to the fixed planes; the washing force causes the change of the incidence angle of the wing plane, which leads to the rotation and the change of the magnitude of the lift force and the drag force vector; according to the root of the generation of the coupling factors, the eddy current influence is simplified and calculated, and the influence is expressed as the changes of wing plane lift force L, resistance D and side force Y;
wherein,
is dynamic pressure; s is the wing area and C is the lift coefficient.
Step three: a bureau plane automatic pilot model is established.
The design of an automatic pilot of a wing plane adds a pneumatic coupling factor, the improvement is carried out on the basis of the automatic pilot of a long plane, and an automatic pilot model considering the pneumatic coupling is established. Specifically, the bureaucratic automatic pilot model is as follows:
wherein x, y, z are error amounts of the formation interval relative to the nominal interval.
Step four: and establishing a relative motion equation.
After respective autopilot models of the lead aircraft and the wing aircraft are established, a relative kinematics model between the densely-formed unmanned aerial vehicles is obtained through analysis and calculation according to the mutual motion relationship of the lead aircraft and the wing aircraft in fig. 4, and the obtained equations are connected to obtain a control equation of the formation.
The relative kinematic model between a nominator and a bureaucratic is:
where ξ is an intermediate variable, expressed in a matrix form:
U＝[vwc ψwc hwc vL ψL hLc]T (7)
the relative motion of the formation aircraft is shown in FIG. 4, where vLAt long machine speed, vWWing aircraft speed, psiLIs the long aircraft heading angle, psiwWing aircraft course angle, psiE＝ψL-ψwIs the course deviation; x and y represent the relative separation distance of the two machines.
Step five: the formation equation sets are decoupled.
The obtained control equations are highly coupled, the equation set is reasonably decoupled according to requirements, the equation set is divided into groups of different channels, the formation controller is designed in groups, and finally the complete dense formation control model is obtained.
According to the natural structural relationship of the formation motion of the unmanned aerial vehicles, the motion of the unmanned aerial vehicles is divided into three groups:
an X channel:
a Y channel:
a Z channel:
step six: and (5) designing a controller model.
The linear continuous time-invariant system for formation flight of unmanned aerial vehicles can be expressed as:
wherein, omega is random disturbance, is Gaussian white noise with zero mean value, and the intensity of omega is more than 0; A. b, C, D is an adaptive matrix.
For the system determined by equation (11), introducing an integration element before the control input point to construct an augmented system can result in:
in the formula:
the state feedback of the augmentation system is set as follows:
uz＝Kz (14)
order to
K＝[K1 K2] (15)
Then the controller in the form of PI of the original system can be obtained:
wherein, K3＝K2(BTB)-1BT，K4＝K1-K2(BTB)-1BTA。
The controller model for constructing the dense formation is as follows: firstly, designing a controller model for a lateral Y channel and a height Z channel, and then designing a longitudinal X channel;
the controller model is as follows:
in the formula, vwcFor controller speed command, psiwcIs a heading command H of the controllerwcFor controller height commands, KXp、KYp、KZpIs a proportionality coefficient, KXI、KYI、KxIIs an integral coefficient, vE、ψERepresenting speed, heading error, kx、ky、kzControlling gain for directional deviation, Δ xE、ΔyE、ΔzEAre the spacing distance errors in the respective x, y, z directions.
Step seven: and establishing a complete model.
As shown in fig. 5, a control model of intensive formation is constructed in combination with a long plane autopilot model, a wing plane autopilot model, a relative kinematics model, a relative position relationship model, and a controller model.
Referring to fig. 6, fig. 6 discloses a system for modeling dense formation of drones considering pneumatic coupling, comprising:
the first construction module is used for constructing a long-machine automatic pilot model according to the flight state of the long machine;
a second building module for building a wing autopilot model under the influence of the aerodynamic coupling of a farm machine and a wing machine;
the first model processing module is used for processing a farm aircraft autopilot model and a wing aircraft autopilot model and acquiring a relative kinematics model between a farm aircraft and a wing aircraft;
the second model processing module is used for processing the relative kinematics model to obtain a relative position relationship model between a captain plane and a bureaucratic plane;
the dividing module is used for dividing the relative kinematics model into different channels according to the result of decoupling the relative kinematics model;
a third construction module for constructing a densely-queued controller model according to the divided interval instructions between the different channels;
the combination module is used for combining a pilot autopilot model, a wing autopilot model, a relative kinematics model, a relative position relationship model and a controller model to construct a control model of the intensive formation.
The above is only a preferred embodiment of the present invention, and is not intended to limit the present invention, and various modifications and changes will occur to those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (9)
1. An unmanned aerial vehicle dense formation modeling method considering pneumatic coupling is characterized by comprising the following steps:
constructing a long aircraft autopilot model according to the flight state of the long aircraft;
a wing plane automatic pilot model under the influence of the pneumatic coupling relationship of a lead plane and a wing plane is established;
processing a pilot plane automatic pilot model and a wing plane automatic pilot model to obtain a relative kinematics model between the pilot plane and the wing plane;
processing the relative kinematics model to obtain a relative position relationship model between a captain plane and a bureaucratic plane;
dividing the relative kinematics model into different channels according to the result of the decoupling relative kinematics equation;
constructing a controller model of intensive formation according to the divided interval instructions among different channels;
and combining a pilot automatic pilot model, a wing automatic pilot model, a relative kinematics model, a relative position relation model and a controller model to construct a control model of the intensive formation.
2. The method of claim 1, wherein the flight state of the long aircraft comprises speed, heading, and altitude.
3. The method for modeling unmanned aerial vehicle dense formation considering pneumatic coupling according to claim 1, wherein the building of the long-aircraft autopilot model specifically comprises:
wherein v, ψ, h represent the speed, heading and altitude of the aircraft, respectively; the subscript c denotes the formation control instruction, τvIs a velocity time constant, τψIs a course time constant, τhIs a height time constant.
4. A method for modeling an intensive formation of unmanned aerial vehicles taking into account aerodynamic coupling as defined in claim 1, wherein the aerodynamic coupling relationship between a farm machine and a wing machine is the up-wash force caused by the up-wash current of a farm machine to a wing machine; the washing force causes the change of the incidence angle of the wing plane, which leads to the rotation and the change of the magnitude of the lift force and the drag force vector; according to the root of the generation of the coupling factors, the eddy current influence is simplified and calculated, and the influence is expressed as the changes of wing plane lift force L, resistance D and side force Y;
wherein,
is dynamic pressure; s is the wing area and C is the lift coefficient.
5. Method for the dense formation of unmanned aerial vehicles considering aerodynamic coupling as in claim 1, characterized in that said wing plane autopilot model is:
wherein x, y, z are error amounts of the formation interval relative to the nominal interval.
6. Method for the dense formation modeling of unmanned aerial vehicles considering aerodynamic coupling as claimed in claim 1, characterized in that the relative kinematics model between the prolonged and bureaucratic aircraft is:
where ξ is an intermediate variable, expressed in a matrix form:
U=[vwc ψwc hwc VL ψL hLc]。 (7)
7. the method for modeling unmanned aerial vehicle dense formation considering pneumatic coupling according to claim 1, wherein the dividing of the relative kinematic model into different channels is specifically:
according to the natural structural relationship of the formation motion of the unmanned aerial vehicles, the motion of the unmanned aerial vehicles is divided into three groups:
an X channel:
a Y channel:
a Z channel:
8. the method of claim 1, wherein the controller model for constructing the dense formation is: firstly, designing a controller model for a lateral Y channel and a height Z channel, and then designing a longitudinal X channel;
the controller model is as follows:
in the formula, vwcFor controller speed command, psiwcIs a heading command H of the controllerwcFor controller height commands, KXp、KYp、KZpIs a proportionality coefficient, KXI、KYI、KxIIs an integral coefficient, vE、ψERepresenting speed, heading error, kx、ky、kzControlling gain for directional deviation, Δ xE、ΔyE、ΔzEAre the spacing distance errors in the respective x, y, z directions.
9. An unmanned aerial vehicle dense formation modeling system considering pneumatic coupling, comprising:
the first construction module is used for constructing a long-machine automatic pilot model according to the flight state of the long machine;
a second building module for building a wing autopilot model under the influence of the aerodynamic coupling of a farm machine and a wing machine;
the first model processing module is used for processing a farm aircraft autopilot model and a wing aircraft autopilot model and acquiring a relative kinematics model between a farm aircraft and a wing aircraft;
the second model processing module is used for processing the relative kinematics model to obtain a relative position relationship model between a captain plane and a bureaucratic plane;
the dividing module is used for dividing the relative kinematics model into different channels according to the result of decoupling the relative kinematics model;
a third construction module for constructing a densely-queued controller model according to the divided interval instructions between the different channels;
the combination module is used for combining a pilot autopilot model, a wing autopilot model, a relative kinematics model, a relative position relationship model and a controller model to construct a control model of the intensive formation.
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Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102591358A (en) * | 2012-03-12 | 2012-07-18 | 北京航空航天大学 | Multi-UAV (unmanned aerial vehicle) dynamic formation control method |
| US20170269612A1 (en) * | 2016-03-18 | 2017-09-21 | Sunlight Photonics Inc. | Flight control methods for operating close formation flight |
| WO2017161304A1 (en) * | 2016-03-18 | 2017-09-21 | Sunlight Photonics Inc. | Systems, methods, and apparatus for airflow sensing and close formation flight |
| CN108762299A (en) * | 2018-05-30 | 2018-11-06 | 上海交通大学 | A kind of unmanned plane formation method and fleet system |
| CN111061296A (en) * | 2019-12-17 | 2020-04-24 | 中国人民解放军空军工程大学 | Research method for unmanned aerial vehicle swarm formation and maintenance based on aerodynamic resistance analysis |
| CN111158395A (en) * | 2020-01-13 | 2020-05-15 | 哈尔滨工程大学 | Multi-unmanned aerial vehicle tight formation control method based on pigeon swarm optimization |
| CN111596684A (en) * | 2020-05-11 | 2020-08-28 | 西安爱生技术集团公司 | Fixed-wing unmanned aerial vehicle dense formation and anti-collision obstacle avoidance semi-physical simulation system and method |
| CN112699622A (en) * | 2021-01-29 | 2021-04-23 | 北京航空航天大学 | Close formation pneumatic coupling effect modeling method for fixed-wing unmanned aerial vehicle |
-
2021
- 2021-10-29 CN CN202111277517.1A patent/CN113985918B/en active Active
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102591358A (en) * | 2012-03-12 | 2012-07-18 | 北京航空航天大学 | Multi-UAV (unmanned aerial vehicle) dynamic formation control method |
| US20170269612A1 (en) * | 2016-03-18 | 2017-09-21 | Sunlight Photonics Inc. | Flight control methods for operating close formation flight |
| WO2017161304A1 (en) * | 2016-03-18 | 2017-09-21 | Sunlight Photonics Inc. | Systems, methods, and apparatus for airflow sensing and close formation flight |
| CN108762299A (en) * | 2018-05-30 | 2018-11-06 | 上海交通大学 | A kind of unmanned plane formation method and fleet system |
| CN111061296A (en) * | 2019-12-17 | 2020-04-24 | 中国人民解放军空军工程大学 | Research method for unmanned aerial vehicle swarm formation and maintenance based on aerodynamic resistance analysis |
| CN111158395A (en) * | 2020-01-13 | 2020-05-15 | 哈尔滨工程大学 | Multi-unmanned aerial vehicle tight formation control method based on pigeon swarm optimization |
| CN111596684A (en) * | 2020-05-11 | 2020-08-28 | 西安爱生技术集团公司 | Fixed-wing unmanned aerial vehicle dense formation and anti-collision obstacle avoidance semi-physical simulation system and method |
| CN112699622A (en) * | 2021-01-29 | 2021-04-23 | 北京航空航天大学 | Close formation pneumatic coupling effect modeling method for fixed-wing unmanned aerial vehicle |
Non-Patent Citations (3)
| Title |
|---|
| 徐跃鉴;董新民;陈博;: "近距编队飞行气动影响建模与分析", 飞行力学, no. 06, 15 December 2008 (2008-12-15) * |
| 李博;李学仁;杜军;张鹏;: "无人机紧密编队气动耦合分析与仿真", 计算机仿真, no. 08, 15 August 2015 (2015-08-15) * |
| 陈春东;魏瑞轩;董志;张立鹏;钮磊;: "无人机紧密编队协同控制设计与仿真", 电光与控制, no. 07, 1 July 2012 (2012-07-01) * |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115542943A (en) * | 2022-10-21 | 2022-12-30 | 北京计算机技术及应用研究所 | Unmanned aerial vehicle formation maintaining control method based on active disturbance rejection controller |
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