CN107590878A - A kind of unmanned plane during flying safe prediction apparatus for evaluating and method - Google Patents
A kind of unmanned plane during flying safe prediction apparatus for evaluating and method Download PDFInfo
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Abstract
The present invention discloses a kind of unmanned plane during flying safe prediction apparatus for evaluating and method.The present invention includes data acquisition unit, data prediction unit, data evaluation unit and data outputting unit；By being predicted to the state of flight under the conditions of current control instruction, safety evaluation is carried out to following state of flight.The input of unmanned plane during flying status safety prediction and evaluation method is unmanned plane during flying state parameter, and output is the safe condition based on these flight status parameters, and unrelated at the time of with flight status parameter.Input past, the flight status parameter of current and future, unmanned plane Security Evaluation Model will provide corresponding past, the safe condition of current and future.The state of flight following by predicting unmanned plane, is prejudged to its safe condition, so as to evade security risk in advance, improves the security of UAS.
Description
Technical field
The present invention relates to a kind of unmanned plane during flying security fields, especially a kind of unmanned plane during flying safe prediction apparatus for evaluating and
Method.
Background technology
With growing application demand, increasing unmanned plane enters fusion spatial domain, brings great safety wind
Danger.It is to improve a kind of important means of unmanned plane during flying safety that security evaluation is carried out to unmanned plane during flying state.Currently nobody flies
Row device flight safety is predicted with assessing mainly using based on unmanned plane during flying device health control database and flithg rules
Detection and method for diagnosing faults in real time.Gather aircraft critical fligh status data in real time using airborne sensor and it is carried out
Filtering process, divide using health control database is related to status information data progress of the flithg rules to all kinds of key equipments
Analysis, so as to confirm simultaneously isolated fault.
In summary, there is problems with existing method：1st, limited by size and lifting capacity, the sensing of safety monitoring
Device carries quantity and measurement accuracy is difficult to ensure that.2nd, the Man-in-loop control of unmanned plane is completed by measuring and control data link,
There is larger delay, therefore only intervened by the health degree monitoring of state of flight and ground control personnel, be to be difficult to ensure that nobody
Machine flight safety.In order to allow ground control personnel to win the time more intervened, mostly important is following to unmanned plane
State of flight is predicted, and carries out safety evaluation by certain means.
The content of the invention
It is pre- from state of flight it is an object of the invention to provide a kind of unmanned plane during flying safe prediction and apparatus for evaluating and method
Survey and the angle of flight safety envelope curve provides solution for unmanned plane during flying status predication and security evaluation.
To achieve the above object, the invention provides following scheme：
A kind of unmanned plane during flying safe prediction apparatus for evaluating, including data acquisition unit, data prediction unit, data assessment
Unit and data outputting unit；Data acquisition unit is used for the flight parameter for gathering unmanned plane and the control command for accusing personnel,
And it is sent to data prediction unit；Data prediction unit is used to the signal data of data acquisition unit collection being predicted, and
It is sent to data evaluation unit；Data evaluation unit is used to be assessed the data that data prediction unit is predicted, and is sent to
Data outputting unit；Data outputting unit is used for the data output after data evaluation unit is handled.
Optionally, data acquisition unit is ground control station, and data acquisition unit is sent to winged by real-time Transmission link
The real-time security monitoring terminal of row, by re-sending to data prediction unit after filtering process.
Optionally, data prediction unit includes unmanned plane six degree of freedom module and nonlinear unmanned plane dynamical system mould
Block.
A kind of unmanned plane during flying safe prediction appraisal procedure, including step：
(1) gather flight parameter and accuse the control command of personnel, and be sent to data prediction unit；
(2) control command exports flight status parameter in data prediction unit by unmanned plane forecast model；
(3) flight status parameter exports state of flight in data evaluation unit by unmanned plane during flying Security Evaluation Model
Assessment result is to data outputting unit；
(4) state of flight assessment result exports the assessment result of state of flight by data outputting unit.
Optionally, in step (2) unmanned plane forecast model by using time domain Hammerstein series models to unmanned plane
Dynamical system carries out Nonlinear Modeling, and time domain Hammerstein series models are defined as follows：
Wherein u (t) and y (t) are the input and output of system respectively, function { gn(τ) }, n=1,2 ..., it is referred to as
The response characteristic of Hammerstein kernel functions, respectively linear, the secondary and high order of describing system,
Time domain Hammerstein series models generally with the non-linear order of p ranks and memory span m are represented by：
Wherein e (t) is with inputting and exporting mutually independent zero-mean white noise；
Modeling input-output data Z is treated assuming that having obtained includingN∈{u(1),y(1),...,u(N),y(N)}
Data acquisition system, then (2) formula can be written as matrix form：
Y=Φ θ+e (3)
Wherein
Φ=(X1 X2 ... Xp) (4)
θ=(g1 g2 ... gp)T (6)
gk=(gk(0) gk(1) … gk(m))T (7)
Y=(y (1) ... y (N))T (8)
E=(e (1) ... e (N))T (9)
From formula (3) least square method can be utilized to obtain the θ of Hammerstein kernel functions to estimate：
Optionally, unmanned plane during flying Security Evaluation Model operation principle in step (3)：Flight parameter is classified, selected
Selecting influences some maximum parameters on flight safety as decisive parameter, and qualitative parameter of fighting to the finish establishes flight safety envelope curve, and
Flight status parameter security function and control parameter security function are established according to the safe envelope curve of thru-flight, to intuitively
Characterize the security of a certain moment unmanned plane during flying state and control parameter；Parameter includes：Air speed, the angle of attack, overload, roll angle speed
Degree；
In order to intuitively quantify the safe condition of unmanned plane, air force envelope curve, flight attitude envelope curve, attitude maneuver bag are defined
Line, level flight envelope and maneuvering flight envelope curve, provide its corresponding cost function；When unmanned plane is in certain flight safety envelope curve model
When enclosing interior, cost function be equal to 0, when beyond safe envelope curve epoch valency function be equal to 1；
Air force envelope curve cost function：
Posture envelope curve cost function：
Attitude maneuver envelope curve cost function：
Level flight envelope cost function：
Maneuvering flight envelope curve cost function：
It is as follows according to 5 kinds of safe envelope curve cost function definable flight safety functions：
S=CAERO(α,β)+CATT(φ,θ)+CATT_MAN(p,q)+CLEVEL(VE,H)+CMAN(VE,ny)
Obviously, when within unmanned plane key parameter is all in safe envelope curve, S=0；According to a large amount of empirical data suggests that,
When occur 3 kinds exceed flight envelope situation when, unmanned plane is just difficult to change from precarious position.
According to specific embodiment provided by the invention, the invention discloses following technique effect：
The present invention is predicted with the flight forecast model state of flight following to unmanned plane, and Security Evaluation Model can divide
Class, some decisive parameters that maximum is influenceed on flight safety are selected, qualitative parameter of fighting to the finish establishes flight safety envelope curve, and root
Flight status parameter security function and control parameter security function are established according to the safe envelope curve of thru-flight, to earth's surface directly perceived
Levy the security of a certain moment unmanned plane during flying state and control parameter.The method tool of the Health database monitoring to compare above
There is more preferable adaptability.
Brief description of the drawings
In order to illustrate more clearly about the embodiment of the present invention or technical scheme of the prior art, below will be to institute in embodiment
The accompanying drawing needed to use is briefly described, it should be apparent that, drawings in the following description are only some implementations of the present invention
Example, for those of ordinary skill in the art, without having to pay creative labor, can also be according to these accompanying drawings
Obtain other accompanying drawings.
Fig. 1 is a kind of structural representation of unmanned plane during flying safe prediction apparatus for evaluating of the present invention；
Fig. 2 is a kind of step schematic flow sheet of unmanned plane during flying safe prediction appraisal procedure of the present invention；
Fig. 3 is a kind of unmanned plane during flying forecast model schematic diagram of unmanned plane during flying safe prediction appraisal procedure of the present invention.
In figure, 1- data acquisition units, 2- data prediction units, 3- data evaluation units, 4- data outputting units.
Embodiment
Below in conjunction with the accompanying drawing in the embodiment of the present invention, the technical scheme in the embodiment of the present invention is carried out clear, complete
Site preparation describes, it is clear that described embodiment is only part of the embodiment of the present invention, rather than whole embodiments.It is based on
Embodiment in the present invention, those of ordinary skill in the art are obtained every other under the premise of creative work is not made
Embodiment, belong to the scope of protection of the invention.
It is an object of the invention to provide a kind of unmanned plane during flying safe prediction apparatus for evaluating and method, Security Evaluation Model meeting
To classify, select some decisive parameters that maximum is influenceed on flight safety, qualitative parameter of fighting to the finish establishes flight safety envelope curve, and
Flight status parameter security function and control parameter security function are established according to the safe envelope curve of thru-flight, to intuitively
Characterize the security of a certain moment unmanned plane during flying state and control parameter.The method of the Health database monitoring to compare above
With more preferable adaptability.
In order to facilitate the understanding of the purposes, features and advantages of the present invention, it is below in conjunction with the accompanying drawings and specific real
Applying mode, the present invention is further detailed explanation.
Embodiment：
As shown in figure 1, a kind of unmanned plane during flying safe prediction apparatus for evaluating, including data acquisition unit (1), data prediction
Unit (2), data evaluation unit (3) and data outputting unit (4)；Data acquisition unit (1) is used for the flight for gathering unmanned plane
Parameter and the control command for accusing personnel, and it is sent to data prediction unit (2)；Data prediction unit (2) is used to adopt data
The signal data of collection unit (1) collection is predicted, and is sent to data evaluation unit (3)；Data evaluation unit (3) is used for will
The data of data prediction unit (2) prediction are assessed, and are sent to data outputting unit (4)；Data outputting unit (4) is used for
Data output after data evaluation unit is handled.
Data acquisition unit (1) is ground control station, and data acquisition unit (1) is sent to flight by real-time Transmission link
Real-time security monitoring terminal, by re-sending to data prediction unit (2) after filtering process.
Data prediction unit (2) includes unmanned plane six degree of freedom module and nonlinear unmanned plane dynamical system module.
A kind of unmanned plane during flying safe prediction appraisal procedure, including step：
(1) gather flight parameter and accuse the control command of personnel, and be sent to data prediction unit (1)；
(2) control command exports flight status parameter in data prediction unit (2) by unmanned plane forecast model；
(3) flight status parameter exports flight shape in data evaluation unit (3) by unmanned plane during flying Security Evaluation Model
State assessment result is to data outputting unit (4)；
(4) state of flight assessment result exports the assessment result of state of flight by data outputting unit (4).
The mentality of designing of the present invention is by being predicted to the state of flight under the conditions of current control instruction, to future
State of flight carries out safety evaluation.As shown in Fig. 2 the input of unmanned plane during flying status safety prediction and evaluation method is unmanned plane
Flight status parameter, output are the safe conditions based on these flight status parameters, and unrelated at the time of with flight status parameter.
That is, input past, the flight status parameter of current and future, unmanned plane Security Evaluation Model will provide mistake accordingly
Go, the safe condition of current and future.Utilize this characteristic, if it is possible to predict following state of flight of unmanned plane, it is possible to
Its safe condition is prejudged, so as to evade security risk in advance, improves the security of UAS.
Unmanned plane during flying safe prediction assess the step of be：
1st, ground control station by the flight parameter received and accuses that the control command of personnel passes through real-time Transmission chain together
Road is sent to flight safety real-time monitoring terminal, and the input of unmanned plane safe prediction assessment models is used as by filtering process.
2nd, establish unmanned plane six degrees of freedom model and nonlinear unmanned plane dynamical system model construction unmanned plane is pre- safely
Model is surveyed, following unmanned plane during flying parameter is predicted using input data.
3rd, unmanned plane during flying state parameter enter unmanned plane Security Evaluation Model after, by series of rules judge its whether
In permissible range, then by quantitative evaluation, intuitively unmanned plane safe condition is exported.
Unmanned plane during flying forecast model implementation method is in the present invention：For normal arrangement fixed-wing unmanned plane, controling power
With control moment by controlling unmanned plane dynamical system and control surface deflection to realize, wherein rudder face includes aileron, lifting
Rudder and rudder.The controlled quentity controlled variable of dynamical system then needs
Throttle opening, and the controlled quentity controlled variable of motor is then pwm signal.Therefore, the input of unmanned plane during flying forecast model is：Dynamical system
Controlled quentity controlled variable, aileron controlled quentity controlled variable, elevator controlled quentity controlled variable and rudder controlled quentity controlled variable, it designs as shown in Figure 3.Unmanned plane in reality all
It is the system with compared with strong nonlinearity, therefore forecast model is a multiple input single output nonlinear model.It is pre- in dotted line frame
Surveying model actually includes two parts：Traditional unmanned plane six degrees of freedom model and unmanned plane dynamical system model.
Because controling power and control moment can not be accurately learnt, it is necessary to be calculated by System Discrimination in dynamical system model
Method carries out parameter to the multiple input single output nonlinear dynamic system and recognized.Use time domain Hammerstein series models
Nonlinear Modeling is carried out to unmanned plane dynamical system.
Time domain Hammerstein series models are defined as follows：
Wherein u (t) and y (t) is the input and output of system respectively.Function { gn(τ) }, n=1,2 ..., it is referred to as
The response characteristic of Hammerstein kernel functions, respectively linear, the secondary and high order of describing system.
Time domain Hammerstein series models generally with the non-linear order of p ranks and memory span m are represented by：
Wherein e (t) is with inputting and exporting mutually independent zero-mean white noise..
Modeling input-output data Z is treated assuming that having obtained includingN∈{u(1),y(1),...,u(N),y(N)}
Data acquisition system, then (2) formula can be written as matrix form：
Y=Φ θ+e (3)
Wherein
Φ=(X1 X2 ... Xp) (4)
θ=(g1 g2 ... gp)T (6)
gk=(gk(0) gk(1) … gk(m))T (7)
Y=(y (1) ... y (N))T (8)
E=(e (1) ... e (N))T (9)
From formula (3) least square method can be utilized to obtain the θ of Hammerstein kernel functions to estimate：
It is to unmanned plane during flying Security Evaluation Model realization principle in the present invention：Flight parameter is classified, selection pair
Flight safety influences some maximum parameters as decisive parameter.Qualitative parameter of fighting to the finish establishes flight safety envelope curve, and according to
The safe envelope curve of thru-flight establishes flight status parameter security function and control parameter security function, intuitively to characterize
The security of a certain moment unmanned plane during flying state and control parameter.When unmanned plane is disturbed by various factors, such as fitful wind, hold
Row mechanism is not in place, undesirable control instruction etc., and kinematic parameter also changes therewith.Some of which kinematic parameter, can be to nothing
Man-machine motion produces conclusive influence, and such as the generation of angle of attack decision lift, if the angle of attack is excessive, aircraft will lose major part
Lift source, so as to cause stall.Such kinematic parameter to be played a decisive role to unmanned plane during flying state is referred to as certainly
Qualitative parameter.Common decisive parameter includes：Air speed, the angle of attack, overload, angular velocity in roll etc..In order to intuitively quantify unmanned plane
Safe condition, define air force envelope curve, flight attitude envelope curve, attitude maneuver envelope curve, level flight envelope and maneuvering flight bag
Line, provide its corresponding cost function.When unmanned plane is in certain flight safety envelope, cost function is equal to 0, when super
Go out safe envelope curve epoch valency function equal to 1.Air force envelope curve cost function：
Posture envelope curve cost function：
Attitude maneuver envelope curve cost function：
Level flight envelope cost function：
Maneuvering flight envelope curve cost function：
It is as follows according to 5 kinds of safe envelope curve cost function definable flight safety functions：
S=CAERO(α,β)+CATT(φ,θ)+CATT_MAN(p,q)+CLEVEL(VE,H)+CMAN(VE,ny)
Obviously, when within unmanned plane key parameter is all in safe envelope curve, S=0.According to a large amount of empirical data suggests that,
When occur 3 kinds exceed flight envelope situation when, unmanned plane is just difficult to change from precarious position.Normal arrangement fixed-wing unmanned plane
Executing agency include aileron, elevator, rudder and throttle (to control thrust size, electronic unmanned plane is motor control
Amount).Wherein aileron to produce rolling axial direction control moment, elevator to produce pitching axial direction control moment, direction
For rudder to produce the control moment of driftage axial direction, throttle then produces thrust.Therefore, when exception occurs in the decisive parameter of unmanned plane
When, it can be modified by above-mentioned executing agency.In unmanned plane Security Evaluation Model described above, pass through flight
Safe envelope curve can detect roll angle, the angle of pitch, the angle of attack, yaw angle and the air speed of unmanned plane whether in permissible range, provide
Accordingly exceed the correction measure of the decisive parameter of safe envelope curve.Assuming that in tkMoment obtains the flight status parameter of unmanned plane
With flight control parameter, the unmanned plane during flying forecast model established using chapter 4, can calculate always using current control
In the case of parameter, tk+1The unmanned plane during flying state parameter at moment, to tk+1The unmanned plane during flying state parameter at moment is flown
Row status safety function inspection, if there is decisive parameter to exceed safe envelope curve, illustrate that its corresponding executing agency currently controls
Amount needs are modified.Said process is repeated at each time point, you can realizes the security evaluation to flight control parameter.
Specific case used herein is set forth to the principle and embodiment of the present invention, and above example is said
It is bright to be only intended to help the method and its core concept for understanding the present invention；Meanwhile for those of ordinary skill in the art, foundation
The thought of the present invention, in specific embodiments and applications there will be changes.In summary, this specification content is not
It is interpreted as limitation of the present invention.
Claims (6)
1. a kind of unmanned plane during flying safe prediction apparatus for evaluating, it is characterised in that including data acquisition unit, data prediction list
Member, data evaluation unit and data outputting unit；The data acquisition unit is used for flight parameter and the charge for gathering unmanned plane
The control command of personnel, and it is sent to the data prediction unit；The data prediction unit is used for the data acquisition list
The signal data of member collection is predicted, and is sent to the data evaluation unit；The data evaluation unit is used for by described in
The data of data prediction unit prediction are assessed, and are sent to the data outputting unit；The data outputting unit is used for
By the data output after data evaluation unit processing.
A kind of 2. unmanned plane during flying safe prediction apparatus for evaluating according to claim 1, it is characterised in that the data acquisition
Unit is ground control station, and the data acquisition unit is sent to flight safety real-time monitoring terminal by real-time Transmission link,
By re-sending to the data prediction unit after filtering process.
A kind of 3. unmanned plane during flying safe prediction apparatus for evaluating according to claim 1, it is characterised in that the data prediction
Unit includes unmanned plane six degree of freedom module and nonlinear unmanned plane dynamical system module.
4. a kind of unmanned plane during flying safe prediction appraisal procedure, it is characterised in that including step：
(1) gather flight parameter and accuse the control command of personnel, and be sent to data prediction unit；
(2) control command exports flight status parameter in the data prediction unit by unmanned plane forecast model；
(3) flight status parameter exports state of flight in data evaluation unit by unmanned plane during flying Security Evaluation Model
Assessment result is to data outputting unit；
(4) the state of flight assessment result exports the assessment result of state of flight by the data outputting unit.
A kind of 5. unmanned plane during flying safe prediction appraisal procedure according to claim 4, it is characterised in that the step
(2) unmanned plane forecast model described in is carried out non-by using time domain Hammerstein series models to unmanned plane dynamical system
Linear modelling, time domain Hammerstein series models are defined as follows：
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Wherein u (t) and y (t) are the input and output of system respectively, function { gn(τ) }, n=1,2 ..., it is referred to as
The response characteristic of Hammerstein kernel functions, respectively linear, the secondary and high order of describing system,
Time domain Hammerstein series models generally with the non-linear order of p ranks and memory span m are represented by：
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Wherein e (t) is with inputting and exporting mutually independent zero-mean white noise；
Modeling input-output data Z is treated assuming that having obtained includingN∈ { u (1), y (1) ..., u (N), y (N) } data
Set, then can be written as matrix form by (2) formula：
Y=Φ θ+e (3)
Wherein
Φ=(X1 X2 ... Xp) (4)
θ=(g1 g2 ... gp)T (6)
gk=(gk(0) gk(1) … gk(m))T (7)
Y=(y (1) ... y (N))T (8)
E=(e (1) ... e (N))T (9)
From formula (3) least square method can be utilized to obtain the θ of Hammerstein kernel functions to estimate：
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6. a kind of unmanned plane during flying safe prediction appraisal procedure according to claim 4, it is characterised in that including the step
Suddenly unmanned plane during flying Security Evaluation Model operation principle described in (3)：The flight parameter is classified, selects to pacify flight
Umbra rings some maximum parameters as decisive parameter, and qualitative parameter of fighting to the finish establishes flight safety envelope curve, and according to all winged
The safe envelope curve of row establishes flight status parameter security function and control parameter security function, intuitively to characterize certain for the moment
Carve the security of unmanned plane during flying state and control parameter；Parameter includes：Air speed, the angle of attack, overload, angular velocity in roll；
In order to intuitively quantify the safe condition of unmanned plane, define air force envelope curve, flight attitude envelope curve, attitude maneuver envelope curve,
Level flight envelope and maneuvering flight envelope curve, provide its corresponding cost function；When unmanned plane is in certain flight safety envelope
When interior, cost function be equal to 0, when beyond safe envelope curve epoch valency function be equal to 1；
Air force envelope curve cost function：
Posture envelope curve cost function：
Attitude maneuver envelope curve cost function：
Level flight envelope cost function：
Maneuvering flight envelope curve cost function：
It is as follows according to 5 kinds of safe envelope curve cost function definable flight safety functions：
S=CAERO(α,β)+CATT(φ,θ)+CATT_MAN(p,q)+CLEVEL(VE,H)+CMAN(VE,ny)
Obviously, when within unmanned plane key parameter is all in safe envelope curve, S=0；According to a large amount of empirical data suggests that, when going out
Existing 3 kinds when exceeding flight envelope situation, unmanned plane is just difficult to change from precarious position.
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| CN108445906A (en) * | 2018-04-25 | 2018-08-24 | 深圳臻迪信息技术有限公司 | A kind of unmanned aerial vehicle control system based on android system and method |
| CN111176329A (en) * | 2020-02-12 | 2020-05-19 | 中国空气动力研究与发展中心高速空气动力研究所 | Formation flight mixing performance function construction method based on wind tunnel test data |
| CN111781946A (en) * | 2020-06-11 | 2020-10-16 | 彩虹无人机科技有限公司 | Unmanned aerial vehicle control and control system based on link |
| CN111942602A (en) * | 2020-08-10 | 2020-11-17 | 中国人民解放军海军航空大学青岛校区 | Flight parameter data comprehensive processing system |
| CN115630531A (en) * | 2022-12-19 | 2023-01-20 | 中南大学 | Automated safety assessment method for unmanned aerial vehicle control system |
| CN111582740B (en) * | 2020-05-13 | 2023-05-23 | 电子科技大学 | Multi-rotor unmanned aerial vehicle risk assessment system |
| CN117330084A (en) * | 2023-12-01 | 2024-01-02 | 中国航空工业集团公司西安飞机设计研究所 | Civil aircraft attitude envelope determining method |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102279568A (en) * | 2011-07-12 | 2011-12-14 | 重庆大学 | Data control method used for formation flying |
| CN102298329A (en) * | 2011-08-19 | 2011-12-28 | 北京航空航天大学 | Small-size unmanned rotary wing aircraft dynamic model identification method based on adaptive genetic algorithm |
| CN104729506A (en) * | 2015-03-27 | 2015-06-24 | 北京航空航天大学 | Unmanned aerial vehicle autonomous navigation positioning method with assistance of visual information |
| CN105004354A (en) * | 2015-06-19 | 2015-10-28 | 北京航空航天大学 | Unmanned aerial vehicle visible light and infrared image target positioning method under large squint angle |
| CN105069187A (en) * | 2015-07-15 | 2015-11-18 | 北京航空航天大学 | Flight parameter panel data model based heavy landing prediction method |
| CN105427674A (en) * | 2015-11-02 | 2016-03-23 | 国网山东省电力公司电力科学研究院 | System and method for real-time unmanned plane flight state evaluation early warning |
| CN107061032A (en) * | 2017-05-25 | 2017-08-18 | 中国人民解放军火箭军工程大学 | The Forecasting Methodology and forecasting system of a kind of engine operating state |
-
2017
- 2017-09-13 CN CN201710823356.9A patent/CN107590878A/en active Pending
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102279568A (en) * | 2011-07-12 | 2011-12-14 | 重庆大学 | Data control method used for formation flying |
| CN102298329A (en) * | 2011-08-19 | 2011-12-28 | 北京航空航天大学 | Small-size unmanned rotary wing aircraft dynamic model identification method based on adaptive genetic algorithm |
| CN104729506A (en) * | 2015-03-27 | 2015-06-24 | 北京航空航天大学 | Unmanned aerial vehicle autonomous navigation positioning method with assistance of visual information |
| CN105004354A (en) * | 2015-06-19 | 2015-10-28 | 北京航空航天大学 | Unmanned aerial vehicle visible light and infrared image target positioning method under large squint angle |
| CN105069187A (en) * | 2015-07-15 | 2015-11-18 | 北京航空航天大学 | Flight parameter panel data model based heavy landing prediction method |
| CN105427674A (en) * | 2015-11-02 | 2016-03-23 | 国网山东省电力公司电力科学研究院 | System and method for real-time unmanned plane flight state evaluation early warning |
| CN107061032A (en) * | 2017-05-25 | 2017-08-18 | 中国人民解放军火箭军工程大学 | The Forecasting Methodology and forecasting system of a kind of engine operating state |
Cited By (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108445906A (en) * | 2018-04-25 | 2018-08-24 | 深圳臻迪信息技术有限公司 | A kind of unmanned aerial vehicle control system based on android system and method |
| CN111176329A (en) * | 2020-02-12 | 2020-05-19 | 中国空气动力研究与发展中心高速空气动力研究所 | Formation flight mixing performance function construction method based on wind tunnel test data |
| CN111176329B (en) * | 2020-02-12 | 2020-09-18 | 中国空气动力研究与发展中心高速空气动力研究所 | Formation flight mixing performance function construction method based on wind tunnel test data |
| CN111582740B (en) * | 2020-05-13 | 2023-05-23 | 电子科技大学 | Multi-rotor unmanned aerial vehicle risk assessment system |
| CN111781946A (en) * | 2020-06-11 | 2020-10-16 | 彩虹无人机科技有限公司 | Unmanned aerial vehicle control and control system based on link |
| CN111781946B (en) * | 2020-06-11 | 2024-03-19 | 彩虹无人机科技有限公司 | Unmanned aerial vehicle monitoring and control system based on link |
| CN111942602A (en) * | 2020-08-10 | 2020-11-17 | 中国人民解放军海军航空大学青岛校区 | Flight parameter data comprehensive processing system |
| CN115630531A (en) * | 2022-12-19 | 2023-01-20 | 中南大学 | Automated safety assessment method for unmanned aerial vehicle control system |
| CN117330084A (en) * | 2023-12-01 | 2024-01-02 | 中国航空工业集团公司西安飞机设计研究所 | Civil aircraft attitude envelope determining method |
| CN117330084B (en) * | 2023-12-01 | 2024-02-23 | 中国航空工业集团公司西安飞机设计研究所 | Civil aircraft attitude envelope determining method |
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