JP2023135721A - Taking-off/landing control device - Google Patents

Abstract

To provide a taking-off/landing control device capable of performing stable control of a vertical taking-off/landing machine based on a highly precise prediction value of a wind speed and wind direction in the periphery of an object point in real-time.SOLUTION: A taking-off/landing control device 200 includes: previous weather feature quantity extraction sections 203, 204 for extracting a weather feature quantity from past weather and topographic data of a taking-off/landing place; a weather analysis section 206 for outputting a weather analysis value in taking-off/landing from weather forecasting data and the topographic data; a weather sensor data acquisition section 207 for acquiring observation values such as a wind speed and a wind direction from weather sensors in the periphery of the taking-off/landing place; a data assimilation section 208 for assimilating the weather analysis value of the taking-off/landing place with the wind speed, the wind direction or the like; and guidance control information generation sections 209-212 for acquiring machine body information of the vertical taking-off/landing machine and flight plan data, simulating a taking-off/landing place peripheral environment, generating posture control data of the vertical taking-off/landing machine based on the taking-off/landing place peripheral environment, and then outputting the posture control data to the vertical taking-off/landing machine.SELECTED DRAWING: Figure 2

Description

The present invention relates to a takeoff and landing control system that controls takeoff and landing of vertical takeoff and landing aircraft such as rotary wing aircraft and drones based on predictions.

During takeoff and landing of flying objects such as airplanes and rotary-wing aircraft, it is necessary to understand weather conditions such as wind speed and direction in order to control gas stably. Currently, various weather forecasts are made by meteorological agencies and private weather companies in various countries based on simulations and observation data, and this data is used for aircraft operations, takeoffs and landings.

Furthermore, detailed weather information is observed near airports using observation equipment such as dedicated radars, and based on this information decisions are made on whether to take off or land, and aircraft are controlled.

On the other hand, in recent years, vertical takeoff and landing aircraft such as rotary-wing aircraft and drones for passenger transportation and logistics have been attracting attention, and these aircraft require stable takeoff and landing when taking off and landing at locations other than airports that do not have advanced equipment. Realization of control is desired.

For this reason, it is necessary to understand local weather conditions such as wind speed and direction using methods different from conventional methods.

However, weather conditions such as wind speed and direction are difficult to predict using only simple sensors, and depending on the conditions, the observation accuracy of observation equipment may decrease or the observation range may be limited.

On the other hand, the observation data published by the Japan Meteorological Agency and other organizations has a spatial resolution of several tens of kilometers, making it difficult to grasp the detailed weather conditions around takeoff and landing sites.

To address such problems, techniques described in Patent Document 1 and Patent Document 2 are disclosed in the field of predicting wind speed and wind direction.

Patent Document 1 proposes a technique for predicting wind direction, wind speed, etc. by installing a plurality of atmospheric pressure sensors around a point such as an airport that is subject to weather prediction and grasping the gradient of atmospheric pressure. In particular, the aim is to understand changes in wind speed and direction that affect the safety of aircraft takeoff and landing, such as downbursts, by understanding weather disturbances from the gradient of atmospheric pressure.

Patent Document 2 proposes a technology that performs a simulation using numerical calculations based on observed values of wind speed and wind direction above the landing site and image data of structures photographed by the landing aircraft, and grasps the wind speed and wind direction near the landing site at the time of landing. ing. This technology makes it possible to predict wind speed and direction not only at the observation point but also around the landing site.

Japanese Patent Application Publication No. 2013-50417 JP 2020-45049 Publication

With the technology described in Patent Document 1, for example, it is possible to predict the approximate wind speed and direction in the area covered by those observation points from the atmospheric pressure observation results at multiple points several kilometers apart. On the other hand, it is difficult to predict wind speed and direction by observing atmospheric pressure alone, taking into account the effects of topography and structures.

For example, for airports located on flat land that are not affected by the surrounding topography or structures, it is sufficient to be able to predict global wind speed and direction, but vertical takeoff and landing aircraft such as rotary-wing aircraft and drones are When taking off or landing in an area with a certain degree of density, it is necessary to predict changes in wind speed and direction such as vortices and separation caused by the topography. There is a problem in that it is necessary to install many different types of sensors and expand the observation network.

In the technology described in Patent Document 2, boundary conditions and initial conditions for simulation are set based on observation points in the sky and the arrangement of structures extracted from image data, and then the conditions are adjusted to actual conditions through numerical analysis and calculations using a simple model. Wind speed and direction can be predicted in the near future.

However, in order to simulate the wind speed and direction for several minutes during takeoff and landing in real time, it is necessary to take measures such as reducing the number of calculation grids and using a simplified model, which reduces prediction accuracy and However, there is a problem in that it is difficult to predict the wind speed and direction required for stable control of the aircraft.

The present invention was made in view of this background, and the purpose of the present invention is to combine observation values and simulations around takeoff and landing sites to provide highly accurate predictions of wind speed and wind direction around target points in real time. Another object of the present invention is to realize a takeoff and landing control system and a takeoff and landing control method that are capable of stably controlling a vertical takeoff and landing aircraft based on predicted values.

In order to achieve the above object, the present invention is configured as follows.

In the takeoff and landing control system, there is a preliminary weather feature extraction unit that performs advance weather analysis from past weather data and terrain data of the airfield and extracts weather features, and a weather feature extraction unit that performs advance weather analysis from past weather data and terrain data of the airfield, and extracts meteorological features from the weather forecast data and the terrain data. a weather analysis unit that analyzes the weather of a data assimilation unit that assimilates the meteorological analysis value of the airfield of the vertical takeoff and landing aircraft and the observed values such as the wind speed and the wind direction, based on the meteorological feature amount, and The aircraft information of the vertical take-off and landing aircraft and the flight plan data of the vertical take-off and landing aircraft are acquired, and the surroundings of the airfield are acquired based on the weather analysis values assimilated by the data assimilation unit, the aircraft information, and the flight plan data. a guidance control information generation unit that simulates an environment, generates control data necessary for attitude control of the vertical take-off and landing aircraft based on the simulated environment around the take-off and landing field, and outputs the control data to the vertical take-off and landing aircraft. .

In addition, in the takeoff and landing control method, preliminary weather analysis is performed from past weather data and topographic data of the airfield, extracting weather features, and analyzing the weather during takeoff and landing of vertical takeoff and landing aircraft from weather forecast data and the topographic data. Obtaining observed values such as wind speed and wind direction from weather sensors placed around the takeoff and landing field, and based on the extracted weather features, an analysis value of the weather at the takeoff and landing field of the vertical takeoff and landing aircraft; The observed values such as the wind speed and the wind direction are assimilated, aircraft information of the vertical take-off and landing aircraft around the airfield and flight plan data of the vertical take-off and landing aircraft are obtained, and the assimilated analysis value of the weather is obtained. , based on the aircraft information and the flight plan data, simulate the environment around the takeoff and landing field, and generate control data necessary for attitude control of the vertical takeoff and landing aircraft based on the simulated environment around the takeoff and landing field. and output to the vertical takeoff and landing aircraft.

According to the present invention, it is possible to realize a takeoff and landing control device and a takeoff and landing control method that are capable of highly accurate prediction of wind speed and wind direction around a target point in real time and stable control of a vertical takeoff and landing aircraft based on the predicted values.

It is a diagram showing an example of an airfield surrounded by structures. 1 is a diagram illustrating a configuration example of a takeoff and landing control system in Embodiment 1 of the present invention. FIG. 3 is a diagram showing an example of weather forecast values and local wind condition analysis. FIG. 3 is a diagram showing an example of the relationship between a flow field and a feature amount in fluid analysis. FIG. 3 is a functional block diagram of a data assimilation unit in Embodiment 1 of the present invention. It is a figure showing the example of composition of the takeoff and landing control system in Example 2 of the present invention. It is a figure showing the example of composition of the takeoff and landing control system in Example 3 of the present invention. It is a figure showing the example of composition of the takeoff and landing control system in Example 4 of the present invention.

Next, embodiments for carrying out the present invention will be described in detail with reference to the drawings as appropriate.

In addition, in each drawing, the same reference numerals are given to the same components, and the description thereof will be omitted.

(Example 1)
FIG. 1 is a diagram showing an example of an airfield 103 for a vertical takeoff and landing aircraft 101 surrounded by structures 102.

In FIG. 1, a vertical takeoff and landing aircraft 101 takes off and lands at an airfield 103 surrounded by structures 102. The structures 102 are buildings such as buildings, residences, stations and bridges, and objects that affect the wind speed and direction around the airfield 103, such as mountains and trees.

A weather sensor 104 is installed around the airfield 103 that can observe weather-related state quantities such as wind speed and direction. The weather sensor 104 may be a sensor that measures the wind speed and direction at the installation point, such as a three-cup anemometer, or a sensor that can measure the wind speed distribution in the altitude direction, such as a Doppler lidar.

The airfield 103 has a size of several meters to several tens of meters, and the surrounding weather sensors 104 are installed within a range of several meters to several kilometers around the airfield 103.

FIG. 2 is a diagram showing an example of the configuration of the takeoff and landing control system 200 according to the first embodiment of the present invention.

The takeoff and landing control system 200 uses the terrain data stored in the terrain data storage unit 201 and the past weather data stored in the past weather data storage unit 202 as input, and performs takeoff and landing using the advance weather analysis unit 203 as advance preparation for operation. Past weather conditions around the field 103 are analyzed by numerical simulation.

The advance weather analysis unit 203 creates a calculation grid based on topographical data, creates initial conditions and boundary conditions for analysis based on past weather data, and calculates past weather conditions around the airfield in high resolution through numerical analysis. .

The topographical data stored in the topographical data storage unit 201 includes Geographical Survey Institute maps published by the Geospatial Information Authority of Japan in which altitudes are expressed numerically, topographical information measured independently, or topographical information of buildings such as buildings published by private companies. The data may include coordinates, size, etc.

The past weather data stored in the past weather data storage unit 202 includes past weather forecast values issued by meteorological organizations such as the Japan Meteorological Agency and the National Oceanic and Atmospheric Administration, and past weather observations observed at the target point using some kind of sensor such as AMeDAS. It may also be past weather data published independently by a private company using a weather analysis simulator or the like.

This simulation targets a range of several kilometers around the airfield 103, and is performed using a model that can take into account the effects of local topography and structures. This model may be one used for analyzing turbulence phenomena in the field of computational fluid analysis, or an analytical model in which the influence of physical phenomena such as clouds and solar radiation is added to the model.

Preliminary weather analysis requires as accurate an understanding of past weather conditions as possible, so the computational grid used for analysis must have sufficient resolution to understand the effects of building winds and mountain winds. It is also necessary to use models for physical phenomena that can reproduce fluid phenomena such as turbulence and separation that may occur within the analysis target range.

The preliminary weather analysis unit 203 creates a calculation grid based on topographical data, creates initial conditions and boundary conditions for analysis based on past weather data, and uses numerical analysis to obtain high resolution past weather conditions around the airfield 103. calculate.

The analysis results obtained by the preliminary weather analysis section 203 are decomposed by the feature amount extraction section 204 into characteristic state amounts of the weather situation at the target point. Techniques such as principal component analysis, orthonormal decomposition, and singular value decomposition are used for this decomposition. The feature extraction unit 204 calculates the meteorological principal component around the airfield 103 as a feature by principal component analysis based on past weather conditions.

As an example, if past wind direction and wind speed data obtained by the advance weather analysis unit 203 are expressed as a matrix Z, the singular value decomposition is expressed as Z=UΣV ^T , and Z is expressed as a feature space. can be projected to. At this time, the matrix U is a matrix that represents conversion to the feature space, and even if the conditions are not included in the preliminary analysis, the wind speed and direction data at the target point are converted to the feature space using this matrix U. is possible.

Next, when operating the take-off and landing control system 200, analysis by the weather analysis unit 206 is required based on the weather forecast data stored in the weather forecast data storage unit 205 first.

As an example, in the early morning on the day of operation of the takeoff and landing control system 200, LFM (local model), which is weather forecast data issued by the Japan Meteorological Agency, is examined, and this data is used as the initial condition and boundary condition, similar to the advance weather analysis unit 203. The topographical data stored in the topographical data storage unit 201 is also inputted, and the weather conditions are simulated by computational fluid analysis. Since the weather forecast data includes future forecast values, a weather analysis value at a future point in time around the airfield 103 can be obtained as an analysis result.

Thereafter, when the vertical takeoff and landing aircraft 101 takes off and lands, the weather observation values acquired by the weather sensor data acquisition unit 207 and the weather analysis values predicted by the weather analysis unit 206 are converted into a transformation matrix U obtained from the feature extraction unit 204. The data is assimilated by the data assimilation unit 208.

That is, the data assimilation unit 208 converts the analysis value output from the weather analysis unit 206 and the observed value acquired from the weather sensor data acquisition unit 207 into the same space as the weather feature quantity, and after data assimilation, By converting it again into the same space as the analysis value, weather prediction values with improved accuracy than weather forecast data are calculated.

The weather observation values acquired by the weather sensor data acquisition unit 207 are values at a specific point, such as the observed values of wind speed and wind direction data observed from the weather sensor 104, for example. However, by transformation using the transformation matrix U, the distribution of observed values in the feature space can be estimated. By correcting the analysis values obtained by the weather analysis unit 206 based on the observation value distribution in this feature space, highly accurate weather prediction values can be obtained at the time the observation values are obtained.

A more detailed explanation will be given later using FIG. 5.

The aircraft sensor data acquisition unit 209 acquires aircraft information such as the position and attitude of the direct take-off and landing aircraft 101. Further, the flight plan data acquisition unit 210 acquires the future flight route of the vertical takeoff and landing aircraft 101.

The weather forecast values obtained by the data assimilation unit 208 are combined with aircraft information such as the position and attitude of the vertical takeoff and landing aircraft 101 obtained from the aircraft sensor data acquisition unit 209 and the flight plan data acquisition unit 210. In combination with the future flight path of the vertical take-off and landing aircraft 101 obtained from the above, it is simulated how the vertical take-off and landing aircraft 101 should be guided and controlled in virtual space to ensure stable takeoff and landing.

In other words, the environment simulation unit 211 calculates whether the vertical take-off and landing aircraft 101 will appear in the digital space (virtual space) based on the aircraft information and flight plan data of the vertical take-off and landing aircraft 101 under weather conditions such as wind and rain included in the weather forecast values. The system simulates the flight of the aircraft during takeoff and landing, and calculates the route and attitude the aircraft should take during takeoff and landing from the flight simulation results.

Based on this simulation result, information (control data) necessary for the vertical take-off and landing aircraft 101 is output from the guidance control information output unit 212, and the vertical take-off and landing aircraft 101 is guided and controlled.

That is, the vertical take-off and landing aircraft 101 flies according to a flight path in which changes in flight direction and speed of the vertical take-off and landing aircraft 101 are estimated due to wind speed and wind direction around the simulated airfield 103.

As an example, parameters such as the tilting angle of the vertical take-off and landing aircraft 101 and the landing route are output to the vertical take-off and landing aircraft 101 so that it can land stably with respect to the predicted future wind speed. The vertical takeoff and landing aircraft 101 receives this information and is able to take off and land stably in consideration of the surrounding weather conditions.

That is, the guidance control information output unit 212 transmits information on the route and attitude that the vertical takeoff and landing aircraft 101 should take during takeoff and landing to other vertical takeoff and landing aircraft 101 around the airfield 103 by communication means such as wireless communication.

FIG. 3 is a diagram showing an example of weather forecast values and local wind condition analysis. For example, the meteorological data 301 published by the Japan Meteorological Agency is called Grid Point Value (GPV), and it shows the values of meteorological variables such as wind speed and wind direction corresponding to each grid in a space divided into grids. is stored. Weather data 301 shows wind speed vectors 302 on grid points, and the shading changes depending on the size of the wind speed vectors 302.

When a portion 303 of the weather data 301 is enlarged, it becomes like the enlarged weather data 311. It can be seen from the wind speed vector 302 that the direction and magnitude of the wind is blowing with respect to the coastline 312. In the expanded range of meteorological data 311, winds are blowing northeast on the west side of coastline 312, and stronger winds are blowing southeast on the east side.

Weather analysis included in the takeoff and landing control system 200 is performed based on the above GPV data. For example, when the airfield 103 is included in the analysis range 314 in the expanded weather data 311, initial conditions and boundary conditions for the weather analysis are created from information on wind speed vectors included in the analysis range 314.

For example, in the analysis target area 321 around the airfield 103, the boundary condition 322 is created from the wind speed from the southeast indicated by the GPV of the analysis target range 314, making it possible to simulate the analysis target area 321 by computational fluid analysis. As a result of the simulation, for example, wind conditions 323 are obtained, and changes in wind direction and wind speed around the airfield 103 that are blocked by the structure 102 can be understood.

FIG. 4 is a diagram showing an example of the relationship between a flow field and its feature in fluid analysis, using an example of a simple flow field around a cylinder, regarding the meteorological feature extracted by the feature extraction unit 204. be.

In FIG. 4, when a flow 402 flows into a cylinder 403, a flow velocity distribution 401 is formed around the cylinder. The flow velocity behind the cylinder 403 slows down and a vortex is generated at the same time. By performing singular value decomposition using the flow velocity change at this time as a matrix Z and plotting the transformation matrix U, a principal component 410 is obtained. The principal components can be obtained according to the magnitude of energy, and a principal component 411 with large energy and a principal component 412 with small energy are obtained.

The principal component 411 with large energy represents a major change in the flow velocity distribution 401, and the change in the principal component 411 is related to the arrangement of vortices behind the cylinder 403. The principal component 412 with low energy also represents a change in the flow velocity distribution 401, but it represents a small structural change included in the change in the vortex, and the change is more pronounced in the flow velocity distribution 401 than the principal component 411 with higher energy. The degree of influence is small. The feature extraction unit 204 three-dimensionally obtains such a principal component 411 in the analysis target area 321 around the airfield 103.

FIG. 5 is a functional block diagram of the data assimilation unit 208 in the first embodiment.

In FIG. 5, the data processing unit 208 includes a reduced-dimensional state quantity calculation unit 01, an assimilation amount analysis unit 502, and an assimilation calculation unit 503. The data assimilation unit 208 first receives weather forecast values from the weather analysis unit 206 . This weather forecast value is projected onto the feature space by the dimension reduction state quantity calculation unit 501 using the transformation matrix U derived by the feature quantity extraction unit 204 in the preliminary analysis, and is reduced in dimension.

In other words, the data assimilation unit 208 converts the analysis value output from the weather analysis unit 206 and the observed value acquired from the weather sensor data acquisition unit 207 into the same space as the feature quantity, performs data assimilation, and then performs analysis. By converting it again into the same space as the value, a weather prediction value with improved accuracy than the weather forecast data is calculated.

Next, the observed values acquired by the weather sensor data acquisition unit 207 are also projected onto the feature space by the assimilation amount analysis unit 502 using the transformation matrix U derived by the feature extraction unit 204 in the preliminary analysis.

At this time, since the observed values are values at discrete points, when multiplying by the transformation matrix U, it is difficult to determine which grid of the calculation grid used by the weather analysis unit 206 the discrete points are. It becomes necessary.

Observed values and analysis values in the feature space are data assimilated in an assimilation calculation unit 503. For data assimilation, a method such as a three-dimensional variational method or a Kalman filter may be used, or a simpler method such as an interpolation method may be used.

For example, when an interpolation method is used, the difference between the predicted weather value and the observed value is calculated in the feature space. This difference is multiplied by the inverse matrix of the transformation matrix U to restore the original value in physical space. This restored value is multiplied by an arbitrary weighting coefficient W, and then added to the weather forecast value as a correction amount. As a result of this assimilation calculation, a highly accurate weather prediction value 504 is obtained.

As described above, according to the first embodiment of the present invention, predictions are made based on the topography data of the prediction target point stored in the topography data storage unit 201 and the past weather data stored in the past weather data storage unit 202. The feature amount of the weather situation is grasped by the preliminary weather analysis unit 203.

The weather analysis unit 206 analyzes the weather conditions around the target point based on the weather forecast data issued by a meteorological organization such as the Japan Meteorological Agency, which is stored in the weather data storage unit 205. Observed values from the weather sensor 104 around the takeoff and landing target point are acquired from the weather sensor data acquisition unit 207, and the meteorological analysis values and observed values are converted into a feature space based on the feature quantities grasped in advance, and combined by data assimilation.

Then, the environmental simulation unit 211 predicts weather conditions such as wind speed and direction with high precision, and stably controls the vertical takeoff and landing aircraft 101 based on the prediction results, thereby predicting the wind speed and direction around the target point in real time. It is possible to realize a takeoff and landing control device 200 and a takeoff and landing control method that are capable of highly accurate prediction and stable control of the vertical takeoff and landing aircraft 101 based on predicted values.

(Example 2)
Next, Example 2 of the present invention will be described.

FIG. 6 is a diagram illustrating a configuration example of a takeoff and landing control system 200 according to the second embodiment. Descriptions of parts similar to those in Example 1 will be omitted.

In the takeoff and landing control system 200 of the second embodiment, the observed values acquired by the weather sensor data acquisition section 207 are input to the observed value correction section 601. The observed value correction unit 601 removes errors included in the observed values acquired by the weather sensor data acquisition unit 207, removes the errors, and outputs the corrected observed values to the data assimilation unit 208. Errors at this time may be due to noise caused by the weather sensor 104 etc. during observation, errors due to improper installation, or errors due to the sensor not being able to output properly due to aging etc. This is an error.

In order to determine these errors from among the observed values acquired by the weather sensor data acquisition unit 207, it is necessary to combine the weather forecast values made highly accurate by the data assimilation unit 208 and the observation by the observed value correction unit 601 before assimilation. The assimilation result learning unit 602 learns the amount of correction based on the value.

Based on this learning result, if the amount of correction by the observed value correction unit 601 changes significantly (changes by more than a certain amount) with respect to normal data assimilation (past average data assimilation), it is treated as an error. After the observed value correction unit 601 corrects the observed value, the data assimilation unit 208 performs data assimilation again using the corrected observed value.

The assimilation result learning unit 602 determines the error based on, for example, an error threshold. The assimilation result learning unit 602 holds a predetermined error threshold, and when the correction amount in the data assimilation unit 208 exceeds the error threshold, outputs the difference from the threshold to the observed value correction unit 601, The observed value is corrected by the observed value correcting unit 601 according to the difference from the threshold value, and is assimilated again by the data assimilating unit 208.

The data assimilated by the data assimilation unit 208 is output to the environment simulation unit 211 via the assimilation result learning unit 602.

However, the assimilation result learning unit 602 only needs to learn the assimilation result from the output from the data assimilation unit 208 and output the difference from the threshold to the observed value correction unit 601, and the data assimilated by the data assimilation unit 208 is It is also possible to output to the environment simulation unit 211 without going through the assimilation result learning unit 602.

Other configurations and operations are the same as in the first embodiment.

According to the second embodiment of the present invention, in addition to being able to obtain the same effects as the first embodiment, it is also possible to appropriately correct errors included in the weather data acquisition unit 207, and to raise the vertical takeoff and landing aircraft 101 to a higher altitude. It is possible to realize a takeoff and landing control device 200 and a takeoff and landing control method that can guide the user to the takeoff and landing field 103 with precision.

(Example 3)
Next, Example 3 of the present invention will be described.

FIG. 7 is a diagram illustrating a configuration example of a takeoff and landing control system 200 according to the third embodiment. Descriptions of parts similar to those in Example 1 will be omitted.

In the takeoff and landing control system 200 according to the third embodiment, sensor data of a plurality of aircraft is inputted to the environment simulation unit 211 by a multi-aircraft sensor data acquisition unit 701. Further, flight plan data for each aircraft is acquired from the multiple flight plan data acquisition unit 702.

The environment simulation unit 211 executes the same simulation as in the first embodiment, but obtains simulation results in a situation where a plurality of vertical takeoff and landing aircraft 101 take off and land at the airfield 103 at the same time. Based on this result, the multi-aircraft route optimization unit 703 calculates optimal route information for takeoff and landing for each vertical takeoff and landing aircraft 101.

For example, when a certain vertical takeoff and landing aircraft 101 lands preferentially, another vertical takeoff and landing aircraft 101 needs to wait above the airfield 103. Alternatively, if strong winds are expected around the takeoff and landing field 103, a takeoff and landing route in which vertical takeoff and landing aircraft 101 are spaced apart is required, and a route for this purpose is calculated by the multi-aircraft route optimization unit 703.

Based on the calculated route, the guidance control information output unit 212 tilts the body of the vertical take-off and landing aircraft 101 so that each of the plurality of vertical take-off and landing aircraft 101 can land stably as in the first embodiment. Parameters (data) such as angle and landing route are output.

Other configurations and operations are the same as in the first embodiment.

According to the third embodiment of the present invention, in addition to being able to obtain the same effects as in the first embodiment, even in a situation where a plurality of vertical take-off and landing aircraft 101 take off and land at the airfield 103 at the same time, the vertical take-off and landing aircraft 101 It is possible to calculate optimal route information for the vertical takeoff and landing aircraft 101, and to realize a takeoff and landing control system 200 and a takeoff and landing control method capable of more stable control of the vertical takeoff and landing aircraft 101.

Note that an example in which the third embodiment and the second embodiment described above are combined is also included in the embodiments of the present invention.

(Example 4)
Next, Example 4 of the present invention will be described.

FIG. 8 is a diagram showing a configuration example of a takeoff and landing control system 200 according to the fourth embodiment. Descriptions of parts similar to those in Example 1 will be omitted.

In the takeoff and landing control system 200 of the fourth embodiment, the weather sudden change information estimating unit 801 estimates (predicts) a sudden change in weather from data on observed values such as wind speed and wind direction acquired by the weather sensor data acquisition unit 207, and estimates (predicts) a sudden change in the weather. The estimation result is output to the guidance control information output section 212. The guidance control information output unit 212 changes the control information (control data) to be output (transmitted) to the vertical takeoff and landing aircraft 101 based on the sudden weather change estimation result.

For example, if a gust of wind occurs that changes the wind speed by several m/s or more within a few minutes, the data assimilation unit 208 and the environment simulation unit 211 may not be able to complete the simulation in time.

Therefore, such sudden changes are estimated using different methods, and depending on the results, processing such as interrupting takeoff and landing of the vertical takeoff and landing aircraft 101 to the airfield 103 is performed.

As for the above-mentioned different methods, for example, a learning method such as machine learning is used. For example, by learning conditions that cause gusts around the airfield 103 from past weather prediction results and weather observation values, sudden changes in wind speed such as gusts can be learned based on data from the weather sensor data acquisition unit 207. can be predicted in real time.

Other configurations and operations are the same as in the first embodiment.

According to the fourth embodiment of the present invention, in addition to being able to obtain the same effects as in the first embodiment, the takeoff and landing control system 200 and the takeoff and landing control system are capable of stably controlling the vertical takeoff and landing aircraft 101 even when the weather suddenly changes. method can be realized.

Note that examples in which the above-mentioned Example 4 is combined with Example 2 or Example 3 are also included in the examples of the present invention. Further, examples in which Example 2, Example 3, and Example 4 are combined are also included in the examples of the present invention.

The advance weather analysis section 203 and feature amount extraction section 204 described above can be combined into one advance weather feature amount extraction section.

Furthermore, the aircraft sensor data acquisition section 209, the flight plan data acquisition section 210, the environment simulation section 211, and the guidance control information output section 212 can be combined into one guidance and control information generation section.

Therefore, the present invention includes advance weather feature extraction units (203, 204) that perform advance weather analysis from past weather data and terrain data of the airfield 103 and extract weather features, and A weather analysis unit 206 that analyzes the weather during takeoff and landing of the vertical takeoff and landing aircraft 101 and outputs the weather analysis values, and a weather sensor that acquires observed values such as wind speed and wind direction from the weather sensors 104 placed around the airfield 103. a data acquisition unit 207; a data assimilation unit 208 that assimilates the meteorological analysis values of the airfield 103 of the vertical takeoff and landing aircraft 101 and observed values such as wind speed and wind direction based on the extracted meteorological features; The environment around the airfield 103 is acquired based on the weather analysis values, aircraft information, and flight plan data assimilated by the data assimilation unit 208. and a guidance control information generation unit (209, 210, 211, 212) that generates and outputs data necessary for attitude control of the vertical takeoff and landing aircraft 101 based on the simulated environment around the airfield 103. Examples include takeoff and landing control systems.

101... Vertical takeoff and landing aircraft, 102... Structure, 103... Takeoff and landing field, 104... Weather sensor, 200... Takeoff and landing control system, 201... Terrain data memory, 202... Past Weather data memory, 203... Advance weather analysis section, 204... Feature amount extraction section, 205... Weather forecast data, 206... Weather analysis section, 207... Weather sensor data acquisition section, 208. ...Data assimilation section, 209...Aircraft sensor data acquisition section, 210...Flight plan data acquisition section, 211...Environment simulation section, 212...Guidance control information acquisition section, 301...Meteorological data , 302... Wind speed vector, 303... Part of meteorological data 301, 311... Area to be analyzed, 312... Coastline, 314... Range to be analyzed, 321... Area to be analyzed, 501... . . . Low-dimensional state quantity calculation section, 502 . . . Assimilation amount analysis section, 503 . . . Assimilation calculation section, 504 . . . Assimilation result learning unit, 701...Multiple aircraft sensor data acquisition unit, 702...Multiple flight plan data acquisition unit, 703...Multiple aircraft route optimization unit, 801...Sudden weather change information estimation unit

Claims (15)

a preliminary weather feature extraction unit that performs preliminary weather analysis from past weather data and topographical data of the airfield and extracts weather features;
a weather analysis unit that analyzes the weather at the time of takeoff and landing of the vertical takeoff and landing aircraft from the weather forecast data and the terrain data, and outputs the analysis value of the weather;
a weather sensor data acquisition unit that acquires observed values such as wind speed and wind direction from weather sensors placed around the airfield;
a data assimilation unit that assimilates the meteorological analysis value of the airfield of the vertical takeoff and landing aircraft and the observed values such as the wind speed and the wind direction, based on the extracted meteorological feature amount;
Acquire aircraft information of the vertical take-off and landing aircraft around the airfield and flight plan data of the vertical take-off and landing aircraft, and based on the meteorological analysis value assimilated by the data assimilation unit, the aircraft information, and the flight plan data. Guidance control information that simulates an environment around the takeoff and landing field, generates control data necessary for attitude control of the vertical takeoff and landing aircraft based on the simulated environment around the takeoff and landing field, and outputs the control data to the vertical takeoff and landing aircraft. A generation section,
A takeoff and landing control device characterized by comprising: The takeoff and landing control device according to claim 1,
The prior weather feature extraction unit includes:
a preliminary weather analysis unit that performs a preliminary weather analysis based on past weather data and terrain data regarding takeoff and landing of vertical takeoff and landing aircraft at the airfield;
a feature extraction unit that extracts the weather feature from the weather analysis result of the preliminary weather analysis unit;
Equipped with
The guidance control information generation unit includes:
an aircraft sensor data acquisition unit that acquires the aircraft information of the vertical takeoff and landing aircraft around the airfield;
a flight plan data acquisition unit that acquires the flight plan data of the vertical takeoff and landing aircraft;
an environment simulation unit that simulates the environment around the airfield based on the assimilated weather analysis values, the aircraft information, and the flight plan data;
a guidance control information output unit that outputs the control data necessary for the attitude control of the vertical takeoff and landing aircraft based on the environment around the takeoff and landing field simulated by the environment simulation unit;
A takeoff and landing control device characterized by comprising: The takeoff and landing control device according to claim 2,
The preliminary weather analysis section creates a calculation grid based on the topographical data, creates initial conditions and boundary conditions for analysis based on the past weather data, and calculates past weather conditions around the airfield by numerical analysis. A takeoff and landing control system that is characterized by high-resolution calculations. The takeoff and landing control device according to claim 2,
The take-off and landing control device is characterized in that the feature extracting unit calculates a meteorological principal component around the takeoff and landing field as the meteorological feature by principal component analysis based on past weather conditions. The takeoff and landing control device according to claim 2,
The data assimilation unit converts the analysis value output from the weather analysis unit and the observed value acquired from the weather sensor data acquisition unit into the same space as the weather feature amount, and after data assimilation. . A takeoff and landing control system, characterized in that the weather analysis value is calculated with improved accuracy than the weather forecast data by converting it again into the same space as the analysis value. The takeoff and landing control device according to claim 2,
The environment simulation unit is configured to calculate the timing of take-off and landing of the vertical take-off and landing aircraft in digital space based on the aircraft information and the flight plan data of the vertical take-off and landing aircraft under weather conditions such as wind and rain included in the weather analysis values. A takeoff and landing control system characterized by simulating a flight and calculating a route and an attitude that the vertical takeoff and landing aircraft should take during takeoff and landing based on the results of the flight simulation. The takeoff and landing control device according to claim 2,
The take-off and landing control system is characterized in that the guidance control information output unit outputs information on the route and attitude that the vertical take-off and landing aircraft should take during takeoff and landing to other vertical take-off and landing aircraft around the airfield. The takeoff and landing control device according to claim 2,
an observed value correction unit that removes and corrects errors included in the observed values acquired by the weather sensor data acquisition unit, and outputs the results to the data assimilation unit;
The weather prediction value assimilated by the data assimilation unit and the correction amount by the observed value correction unit before assimilation are learned, and based on the learning result, if the correction amount by the observed value exceeds a predetermined error threshold, correction is performed. an assimilation result learning unit that outputs the amount to the observed value correction unit;
A takeoff and landing control device characterized by comprising: The takeoff and landing control device according to claim 2,
a plurality of aircraft sensor data acquisition units that acquire the aircraft information of the plurality of vertical takeoff and landing aircraft;
a plurality of flight plan data acquisition units that acquire the flight plan data of the plurality of vertical takeoff and landing aircraft;
a multi-aircraft route optimization unit that optimizes the flight path of the plurality of vertical takeoff and landing aircraft based on the environment around the airfield simulated by the environment simulation unit;
The guidance control information output unit is configured to control the attitude of the plurality of vertical take-off and landing aircraft based on the flight path optimized by the multi-aircraft path optimization unit for the plurality of vertical take-off and landing aircraft. A takeoff and landing control device, characterized in that it outputs the necessary control data. The takeoff and landing control device according to claim 2,
further comprising a sudden weather change information estimating unit that estimates a sudden change in the weather from the observed value acquired by the weather sensor data acquisition unit and outputs the sudden weather change estimation result to the guidance control information output unit,
The takeoff and landing control device is characterized in that the guidance control information output unit changes the control data to be output to the vertical takeoff and landing aircraft based on the sudden weather change estimation result. Perform preliminary weather analysis from past weather data and topographical data of the airfield, extract weather features,
Analyzing the weather during takeoff and landing of vertical takeoff and landing aircraft from weather forecast data and the terrain data,
Obtaining observed values such as wind speed and wind direction from weather sensors placed around the airfield,
Assimilating the meteorological analysis value of the airfield of the vertical takeoff and landing aircraft and the observed values such as the wind speed and the wind direction based on the extracted meteorological feature amount,
Obtain aircraft information of the vertical take-off and landing aircraft and flight plan data of the vertical take-off and landing aircraft around the airfield, and based on the assimilated weather analysis values, aircraft information, and flight plan data, simulating a surrounding environment, generating control data necessary for attitude control of the vertical takeoff and landing aircraft based on the simulated surrounding environment of the takeoff and landing field, and outputting the control data to the vertical takeoff and landing aircraft;
A takeoff and landing control method characterized by: The takeoff and landing control method according to claim 11,
correcting by removing the error included in the observed value,
A takeoff and landing control method, characterized in that the meteorological analysis value and the observed value corrected for the error are assimilated. The takeoff and landing control method according to claim 11,
acquiring the aircraft information of the plurality of vertical takeoff and landing aircraft;
acquiring the flight plan data of the plurality of vertical takeoff and landing aircraft;
optimizing the flight path of the plurality of vertical takeoff and landing aircraft based on the simulated environment around the airfield;
A takeoff and landing control method, characterized in that the control data necessary for the attitude control of the plurality of vertical takeoff and landing aircraft is output based on the optimized flight path. The takeoff and landing control method according to claim 11,
Estimating a sudden change in the weather from the obtained observed values,
A takeoff and landing control method, characterized in that the control data output to the vertical takeoff and landing aircraft is changed based on the estimated sudden change in the weather. The takeoff and landing control method according to claim 11,
A takeoff and landing control method, characterized in that the vertical takeoff and landing aircraft flies in accordance with a flight path in which changes in flight direction and speed of the vertical takeoff and landing aircraft are estimated due to the simulated wind speed and direction around the airfield.

Images