CN106569507A - Method and system for correcting flight state parameters of unmanned airplane - Google Patents
Method and system for correcting flight state parameters of unmanned airplane Download PDFInfo
- Publication number
- CN106569507A CN106569507A CN201610933233.6A CN201610933233A CN106569507A CN 106569507 A CN106569507 A CN 106569507A CN 201610933233 A CN201610933233 A CN 201610933233A CN 106569507 A CN106569507 A CN 106569507A
- Authority
- CN
- China
- Prior art keywords
- unmanned plane
- flight status
- status parameter
- prediction
- parameter
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 27
- 239000011159 matrix material Substances 0.000 claims description 8
- 206010008190 Cerebrovascular accident Diseases 0.000 claims description 4
- 208000006011 Stroke Diseases 0.000 claims description 4
- 238000006243 chemical reaction Methods 0.000 claims description 4
- 238000004088 simulation Methods 0.000 claims description 4
- 230000000694 effects Effects 0.000 claims description 3
- 238000001914 filtration Methods 0.000 abstract description 6
- 230000009286 beneficial effect Effects 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 238000005096 rolling process Methods 0.000 description 2
- 230000001133 acceleration Effects 0.000 description 1
- 230000005484 gravity Effects 0.000 description 1
- 230000010354 integration Effects 0.000 description 1
- 238000005259 measurement Methods 0.000 description 1
- 239000002002 slurry Substances 0.000 description 1
Classifications
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
- G05D1/10—Simultaneous control of position or course in three dimensions
- G05D1/101—Simultaneous control of position or course in three dimensions specially adapted for aircraft
Landscapes
- Engineering & Computer Science (AREA)
- Aviation & Aerospace Engineering (AREA)
- Radar, Positioning & Navigation (AREA)
- Remote Sensing (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Automation & Control Theory (AREA)
- Aerodynamic Tests, Hydrodynamic Tests, Wind Tunnels, And Water Tanks (AREA)
- Control Of Position, Course, Altitude, Or Attitude Of Moving Bodies (AREA)
Abstract
The invention relates to the field of unmanned airplanes and particularly relates to a method and a system for correcting the flight state parameters of an unmanned airplane. The method for correcting the flight state parameters of the unmanned airplane comprises the steps of obtaining the flight state parameters of the unmanned airplane within a preset time window; presetting a forecast pneumatic environment parameter function during the flight process of the unmanned airplane; according to the flight state parameters and the forecast pneumatic environment parameter function, calculating to obtain the offset of the actual pneumatic environment parameters of the unmanned airplane within the preset time window; according to the offset, correcting the flight state parameters of the unmanned airplane. According to the technical scheme of the invention, the influence of the pneumatic environment during the filtering process is considered, so that the prediction precision of state parameters is improved. Meanwhile, the hardware cost is reduced.
Description
Technical field
The present invention relates to unmanned plane field, more particularly to a kind of flight status parameter bearing calibration and the system of unmanned plane.
Background technology
At present, the winged control algorithm of most of four rotor wing unmanned aerial vehicle does not consider the impact of wind in modeling, and simply in control
The impact of wind is considered as disturbance treatment by link.For the problems referred to above, there is part that wind speed sensing is increased on four rotor wing unmanned aerial vehicles
Device is measuring wind speed, but at present the price of air velocity transducer is higher, increased cost, and the slurry of four rotor wing unmanned aerial vehicles is turning
Air-flow can be produced in dynamic process, the air-flow of generation can cause interference to the measurement of air velocity transducer.
The content of the invention
The technical problem to be solved is:A kind of flight status parameter bearing calibration of unmanned plane is provided and is
System.
In order to solve above-mentioned technical problem, the technical solution used in the present invention is:
A kind of flight status parameter bearing calibration of unmanned plane, including:
Obtain the flight status parameter of unmanned plane Preset Time window;The prediction Airflow Environment of default unmanned plane during flying process
Parametric function;
According to the flight status parameter and prediction Airflow Environment parametric function, unmanned plane is calculated in Preset Time window
The side-play amount of actual Airflow Environment parameter in mouthful;
The flight status parameter of unmanned plane is corrected according to the side-play amount.
Another technical scheme for adopting of the present invention for:
A kind of flight status parameter correction system of unmanned plane, including:Acquisition module, computing module and correction module;
The acquisition module, for obtaining the flight status parameter of unmanned plane Preset Time window;Default unmanned plane during flying
The prediction Airflow Environment parametric function of process;
The computing module, for according to the flight status parameter and prediction Airflow Environment parametric function, being calculated
The side-play amount of unmanned plane actual Airflow Environment parameter in Preset Time window;
The correction module, for being corrected to the flight status parameter of unmanned plane according to the side-play amount.
The beneficial effects of the present invention is:
The flight status parameter bearing calibration of the unmanned plane that the present invention is provided and system, by obtaining unmanned plane Preset Time
The flight status parameter of window;The prediction Airflow Environment parametric function of default unmanned plane during flying process;According to the state of flight
Parameter and prediction Airflow Environment parametric function, be calculated unmanned plane in Preset Time window actual Airflow Environment parameter it is inclined
Shifting amount;The flight status parameter of unmanned plane is corrected according to the side-play amount, Airflow Environment is considered in filtering
Affect, improve the precision of prediction of state parameter, reduce hardware cost.
Description of the drawings
The step of Fig. 1 is the flight status parameter bearing calibration of the unmanned plane of present invention flow chart;
Fig. 2 is the structural representation that the flight status parameter of the unmanned plane of the present invention corrects system;
Label declaration:
1st, acquisition module;2nd, computing module;3rd, correction module.
Specific embodiment
To describe the technology contents of the present invention in detail, being realized purpose and effect, below in conjunction with embodiment and coordinate attached
Figure is explained.
Refer to Fig. 1, a kind of flight status parameter bearing calibration of unmanned plane that the present invention is provided, including:
Obtain the flight status parameter of unmanned plane Preset Time window;The prediction Airflow Environment of default unmanned plane during flying process
Parametric function;
According to the flight status parameter and prediction Airflow Environment parametric function, unmanned plane is calculated in Preset Time window
The side-play amount of actual Airflow Environment parameter in mouthful;
The flight status parameter of unmanned plane is corrected according to the side-play amount.
Knowable to foregoing description, the beneficial effects of the present invention is:The flight status parameter of the unmanned plane that the present invention is provided
Bearing calibration, by the flight status parameter for obtaining unmanned plane Preset Time window;The prediction gas of default unmanned plane during flying process
Rotating ring border parametric function;According to the flight status parameter and prediction Airflow Environment parametric function, unmanned plane is calculated pre-
If the side-play amount of actual Airflow Environment parameter in time window;The flight status parameter of unmanned plane is carried out according to the side-play amount
Correction, considers the impact of Airflow Environment in filtering, improves the precision of prediction of state parameter, reduces hardware cost.
Further, the acquisition methods of the prediction Airflow Environment parametric function are:
S1, set up earth axes Se={ xe, ye, zeAnd body axis system Sb={ xb, yb, zb, and determine by ground seat
Mark system SeTo body axis system SbCoordinate conversion matrix R;
Under S2, Airflow Environment effect, the air force situation of each rotor is analyzed;
S3, the torque M that unmanned plane is caused by rotor lift is determined according to the analysis result of S2BWith the torque caused by wind-force
Mw;
S4, the line equation of motion is set up in earth axes respectively and rotation equation is set up in body axis system;
S5, the prediction Airflow Environment parameter letter for calculating the rotor wing unmanned aerial vehicle of six degree of freedom four with aerodynamic disturbance item
Number.
Assume that four rotor wing unmanned aerial vehicles are rigid bodies and structure is full symmetric in step S1, the origin of earth axes is ground
Unmanned plane takeoff point on face, zeAxle straight down, longitudinal axis xeIt is just y to point to headingeAxle is perpendicular to oexezePlane, it is just
Direction is determined by the right-hand rule;Body axis system is fixed on body, and its origin is connected in fuselage barycenter, longitudinal axis xbIn aircraft pair
Claim in plane, to overlap with the body longitudinal axis, point to body head for just;zbAxle is just perpendicular to unmanned plane symmetrical plane, downwards;yb
Axle is directly in obxbzbPlane, its positive direction is determined by the right-hand rule.
The lift F for obtaining each rotor is analyzed in the S2Ti, wind-force Fwi, moment of torsion MQiAnd torque Mwi, wherein i=1,
2,3,4, it is rotor label, it is that 2, the left-handed wing is 4 for 3, the dextrorotation wing that front rotor is 1, rear rotor.
The lift F of rotorTiSize is:FTi=b Ωi2, the moment of torsion M of rotorQiSize be:MQi=d Ωi2;B is to rise
Force coefficient d is resistance coefficient, ΩiIt is the angular velocity of rotation of rotor i.
Unmanned plane is by the torque that rotor lift causes:
L is the brachium of body.
Unmanned plane is by the torque that wind-force causes:
L is the brachium of body.
S4 is to set up the line equation of motion and rotation equation using newton-Eulerian equation, and the line equation of motion and rotation equation have
Body is
In formula, X=[x, y, z]TIt is the position of four rotor wing unmanned aerial vehicle barycenter, m is quality,WithIt is respectively rotor i
Lift and wind-force, G=[0,0 ,-g]TIt is acceleration of gravity, ω=[p, q, r]TIt is body rotational angular velocity, JrIt is turning for rotor
Dynamic inertia, ω × [0,0, JrΩr] item represents is the gyroscopic torque produced due to rotor wing rotation, J is the moment of inertia diagonal square
Battle array:
Ixx, Iyy, IzzFor axial principal moment of inertia, MBIt is torque that unmanned plane is caused by rotor lift, MwIt is unmanned plane by wind
The torque that power causes, ΩrIt is the relative velocity Ω of rotorr=-Ω1+Ω2-Ω3+Ω4。
The S5 derives the kinetic model tool for calculating the rotor wing unmanned aerial vehicle of six degree of freedom four with wind disturbance item
Body is:
In formula, [x, y, z]TIt is the position of four rotor wing unmanned aerial vehicle barycenter, m is quality, the flight attitude of four rotor wing unmanned aerial vehicles
By attitude angle Θ=[φ, θ, ψ]TDescription, roll angle φ is axis zbWith by axis xbVertical guide between angle, to the right
For just during rolling;Pitching angle theta is axis xbThe angle between horizontal plane, upwards for just during pitching;Yaw angle ψ is axis xb
Projection on horizontal plane and earth's axis xeBetween angle, to the right driftage is for just;U=[U1, U2, U3, U4]TIt is dominant vector, U1It is lifting
Or Hovering control amount, U2, U3, U4It is respectively rolling, pitching and driftage controlled quentity controlled variable;Ixx, Iyy, IzzFor axial principal moment of inertia;JrIt is
The rotary inertia of rotor;L is the brachium of body;ΩrIt is the relative velocity of rotor;
W=[W1, W2, W3, W4, W5, W6]TFor wind disturbance item.
Further, the prediction Airflow Environment parametric function is simulation unmanned plane practical flight process apoplexy parameter letter
Number.
A kind of flight status parameter correction system of the unmanned plane also provided refering to Fig. 2, the present invention, including:Acquisition module
1st, computing module 2 and correction module 3;
The acquisition module 1, for obtaining the flight status parameter of unmanned plane Preset Time window;Default unmanned plane during flying
The prediction Airflow Environment parametric function of process;
The computing module 2, for according to the flight status parameter and prediction Airflow Environment parametric function, being calculated
The side-play amount of unmanned plane actual Airflow Environment parameter in Preset Time window;
The correction module 3, for being corrected to the flight status parameter of unmanned plane according to the side-play amount.
The flight status parameter correction system of the unmanned plane that the present invention is provided, by obtaining unmanned plane Preset Time window
Flight status parameter;The prediction Airflow Environment parametric function of default unmanned plane during flying process;According to the flight status parameter and
Prediction Airflow Environment parametric function, is calculated the side-play amount of unmanned plane actual Airflow Environment parameter in Preset Time window;
The flight status parameter of unmanned plane is corrected according to the side-play amount, the impact of Airflow Environment is considered in filtering,
The precision of prediction of state parameter is improved, hardware cost is reduced.
Further, the acquisition module also includes default unit;The default unit sets up unit, analysis including first
Unit, determining unit, second set up unit and computing unit;
Described first sets up unit, for setting up earth axes Se={ xe, ye, zeAnd body axis system Sb={ xb,
yb, zb, and determine by earth axes SeTo body axis system SbCoordinate conversion matrix R;
The analytic unit, under acting on for Airflow Environment, is analyzed to the air force situation of each rotor;
The determining unit, for determining the torque that unmanned plane is caused by rotor lift according to the analysis result of analytic unit
MBWith the torque M caused by wind-forcew;
Described second sets up unit, in earth axes setting up the line equation of motion and in body axis system respectively
Set up rotation equation;
The computing unit, for calculating the prediction gas of the rotor wing unmanned aerial vehicle of six degree of freedom four with aerodynamic disturbance item
Rotating ring border parametric function.
Further, the prediction Airflow Environment parametric function is simulation unmanned plane practical flight process apoplexy parameter letter
Number.
Concrete calculating process is as follows:
1st, the average and evaluated error in the state of flight time window of unmanned plane is calculated;
2nd, according to the evaluated error in step 1, it is calculated evaluated error in the state of flight time window of unmanned plane
Average;
3rd, obtain in the average and step 2 in the state of flight time window of the unmanned plane obtained according to step 1 nobody
The average of evaluated error, is calculated the covariance matrix of process Airflow Environment noise in the state of flight time window of machine;
The covariance matrix of the process Airflow Environment noise that the 4th, integration step 3 is obtained, obtains the variance of status predication process
Matrix;
5th, the observation average in the state of flight observation time window of unmanned plane is calculated;
6th, the error in the state of flight observation time window of unmanned plane is calculated;
7th, the process-noise variance in the state of flight observation time window of unmanned plane is calculated.
Bring the process-noise variance that variance matrix and step 7 that step 4 obtains status predication process are obtained into Kalman
Filtering and its related algorithm, resolve to state, obtain unmanned plane actual Airflow Environment parameter in Preset Time window
Side-play amount;The flight status parameter of unmanned plane is corrected according to the side-play amount.
In sum, a kind of flight status parameter bearing calibration of unmanned plane that the present invention is provided and system, by obtaining
The flight status parameter of unmanned plane Preset Time window;The prediction Airflow Environment parametric function of default unmanned plane during flying process;Root
According to the flight status parameter and prediction Airflow Environment parametric function, unmanned plane actual gas in Preset Time window is calculated
The side-play amount of dynamic ambient parameter;The flight status parameter of unmanned plane is corrected according to the side-play amount, in filtering
Consider the impact of Airflow Environment, improve the precision of prediction of state parameter, reduce hardware cost.
Embodiments of the invention are the foregoing is only, the scope of the claims of the present invention is not thereby limited, it is every using this
The equivalents that bright specification and accompanying drawing content are made, or the technical field of correlation is directly or indirectly used in, include in the same manner
In the scope of patent protection of the present invention.
Claims (6)
1. the flight status parameter bearing calibration of a kind of unmanned plane, it is characterised in that include:
Obtain the flight status parameter of unmanned plane Preset Time window;The prediction Airflow Environment parameter of default unmanned plane during flying process
Function;
According to the flight status parameter and prediction Airflow Environment parametric function, unmanned plane is calculated in Preset Time window
The side-play amount of actual Airflow Environment parameter;
The flight status parameter of unmanned plane is corrected according to the side-play amount.
2. the flight status parameter bearing calibration of unmanned plane according to claim 1, it is characterised in that the prediction is pneumatic
The acquisition methods of ambient parameter function are:
S1, set up earth axes Se={ xe, ye, zeAnd body axis system Sb={ xb, yb, zb, and determine by earth axes
SeTo body axis system SbCoordinate conversion matrix R;
Under S2, Airflow Environment effect, the air force situation of each rotor is analyzed;
S3, the torque that unmanned plane is caused by rotor lift and the torque caused by wind-force are determined according to the analysis result of S2;
S4, the line equation of motion is set up in earth axes respectively and rotation equation is set up in body axis system;
S5, the prediction Airflow Environment parametric function for calculating the rotor wing unmanned aerial vehicle of six degree of freedom four with aerodynamic disturbance item.
3. the flight status parameter bearing calibration of unmanned plane according to claim 1, it is characterised in that the prediction is pneumatic
Ambient parameter function is simulation unmanned plane practical flight process apoplexy parametric function.
4. a kind of flight status parameter of unmanned plane corrects system, it is characterised in that include:Acquisition module, computing module and school
Positive module;
The acquisition module, for obtaining the flight status parameter of unmanned plane Preset Time window;Default unmanned plane during flying process
Prediction Airflow Environment parametric function;
The computing module, for according to the flight status parameter and prediction Airflow Environment parametric function, being calculated nobody
The side-play amount of machine actual Airflow Environment parameter in Preset Time window;
The correction module, for being corrected to the flight status parameter of unmanned plane according to the side-play amount.
5. the flight status parameter of unmanned plane according to claim 4 corrects system, it is characterised in that the acquisition module
Also include default unit;The default unit including first set up unit, analytic unit, determining unit, second set up unit and
Computing unit;
Described first sets up unit, for setting up earth axes Se={ xe, ye, zeAnd body axis system Sb={ xb, yb, zb,
And determine by earth axes SeTo body axis system SbCoordinate conversion matrix R;
The analytic unit, under acting on for Airflow Environment, is analyzed to the air force situation of each rotor;
The determining unit, for according to the analysis result of analytic unit determine torque that unmanned plane causes by rotor lift and by
The torque that wind-force causes;
Described second sets up unit, for setting up in earth axes the line equation of motion respectively and setting up in body axis system
Rotation equation;
The computing unit, for calculating the prediction air ring of the rotor wing unmanned aerial vehicle of six degree of freedom four with aerodynamic disturbance item
Border parametric function.
6. the flight status parameter of unmanned plane according to claim 4 corrects system, it is characterised in that the prediction is pneumatic
Ambient parameter function is simulation unmanned plane practical flight process apoplexy parametric function.
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201610933233.6A CN106569507A (en) | 2016-10-25 | 2016-10-25 | Method and system for correcting flight state parameters of unmanned airplane |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201610933233.6A CN106569507A (en) | 2016-10-25 | 2016-10-25 | Method and system for correcting flight state parameters of unmanned airplane |
Publications (1)
Publication Number | Publication Date |
---|---|
CN106569507A true CN106569507A (en) | 2017-04-19 |
Family
ID=58533448
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN201610933233.6A Pending CN106569507A (en) | 2016-10-25 | 2016-10-25 | Method and system for correcting flight state parameters of unmanned airplane |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN106569507A (en) |
Cited By (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN112925344A (en) * | 2021-01-25 | 2021-06-08 | 南京航空航天大学 | Unmanned aerial vehicle flight condition prediction method based on data driving and machine learning |
Citations (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN103345737A (en) * | 2013-06-04 | 2013-10-09 | 北京航空航天大学 | UAV high resolution image geometric correction method based on error compensation |
CN103625649A (en) * | 2013-12-06 | 2014-03-12 | 北京工商大学 | Aircraft autonomous landing region judging method based on self adaptive region division and window communication |
CN104765272A (en) * | 2014-03-05 | 2015-07-08 | 北京航空航天大学 | Four-rotor aircraft control method based on PID neural network (PIDNN) control |
CN105488295A (en) * | 2015-12-15 | 2016-04-13 | 中国电子科技集团公司信息科学研究院 | Unmanned aerial vehicle modeling system taking wind field disturbances into consideration |
CN105488296A (en) * | 2015-12-15 | 2016-04-13 | 中国电子科技集团公司信息科学研究院 | Unmanned aerial vehicle modeling method covering wind field disturbance term |
-
2016
- 2016-10-25 CN CN201610933233.6A patent/CN106569507A/en active Pending
Patent Citations (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN103345737A (en) * | 2013-06-04 | 2013-10-09 | 北京航空航天大学 | UAV high resolution image geometric correction method based on error compensation |
CN103625649A (en) * | 2013-12-06 | 2014-03-12 | 北京工商大学 | Aircraft autonomous landing region judging method based on self adaptive region division and window communication |
CN104765272A (en) * | 2014-03-05 | 2015-07-08 | 北京航空航天大学 | Four-rotor aircraft control method based on PID neural network (PIDNN) control |
CN105488295A (en) * | 2015-12-15 | 2016-04-13 | 中国电子科技集团公司信息科学研究院 | Unmanned aerial vehicle modeling system taking wind field disturbances into consideration |
CN105488296A (en) * | 2015-12-15 | 2016-04-13 | 中国电子科技集团公司信息科学研究院 | Unmanned aerial vehicle modeling method covering wind field disturbance term |
Non-Patent Citations (1)
Title |
---|
何勇灵等: "四旋翼飞行器在风场扰动下的建模与控制", 《 中国惯性技术学报》 * |
Cited By (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN112925344A (en) * | 2021-01-25 | 2021-06-08 | 南京航空航天大学 | Unmanned aerial vehicle flight condition prediction method based on data driving and machine learning |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
CN109614633B (en) | Nonlinear modeling and linearization balancing method for composite rotor craft | |
CN106249745B (en) | The control method of four axis unmanned planes | |
Colorado et al. | Mini-quadrotor attitude control based on Hybrid Backstepping & Frenet-Serret theory | |
CN106844887B (en) | Dynamics modeling method and device for rotor unmanned aerial vehicle | |
CN107368091A (en) | A kind of stabilized flight control method of more rotor unmanned aircrafts based on finite time neurodynamics | |
CN112394739B (en) | Active-deformation active-disturbance-rejection flight control method for four-rotor aircraft | |
CN107957730A (en) | A kind of unmanned vehicle stabilized flight control method | |
CN104950901A (en) | Nonlinear robust control method with finite-time convergence capacity for unmanned helicopter attitude error | |
CN104210655A (en) | Double-rotor-wing unmanned plane | |
CN112578805B (en) | Attitude control method of rotor craft | |
CN107065901A (en) | A kind of rotor wing unmanned aerial vehicle attitude control method, device and unmanned plane | |
CN112558621A (en) | Decoupling control-based flying mechanical arm system | |
CN109703768B (en) | Soft air refueling docking method based on attitude/trajectory composite control | |
CN109828602B (en) | Track loop nonlinear model transformation method based on observation compensation technology | |
WO2022048543A1 (en) | Flight control method, unmanned aerial vehicle, and storage medium | |
CN105488295A (en) | Unmanned aerial vehicle modeling system taking wind field disturbances into consideration | |
CN112744227B (en) | Multi-mode land-air amphibious vehicle take-off and landing control method and device and computer storage medium | |
CN110414110B (en) | Airplane stress simulation method used in flight stall state | |
CN110254703B (en) | Tilting double-rotor wing automatic hovering T-shaped unmanned aerial vehicle system | |
CN110723309A (en) | Method for measuring rotational inertia of quad-rotor unmanned aerial vehicle | |
CN105488296A (en) | Unmanned aerial vehicle modeling method covering wind field disturbance term | |
Panda et al. | Flap‐Lag‐Torsion Stability in Forward Flight | |
CN109308074A (en) | A kind of compensation method and system of drone center of unmanned aerial vehicle offset | |
CN117008626A (en) | Accurate route tracking guiding control method of unpowered parachute-wing unmanned aerial vehicle in wind field | |
CN111008488B (en) | Propeller unmanned aerial vehicle launching process reaction torque modeling method |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
PB01 | Publication | ||
PB01 | Publication | ||
SE01 | Entry into force of request for substantive examination | ||
SE01 | Entry into force of request for substantive examination | ||
WD01 | Invention patent application deemed withdrawn after publication |
Application publication date: 20170419 |
|
WD01 | Invention patent application deemed withdrawn after publication |