91 results about "Flight model" patented technology

The invention discloses an avigation multi-spectral scanner geometric rough correction method under the conditions of no gesture information, which comprises the steps that: 1) the multi-spectral scanner data is carried out the coordinate conversion, the measured value in a WGS-84 ground coordinate system is converted to the value in a Gaussian plane Cartesian coordinate; 2) according to a ideal flight model, an one second mode is used for simulating a rolling angle; 3) a curve is fitted according to the height data in the vertical plane, then the flight pitching angle in each updated data point is calculated according to the cutting direction; 4) the central projection constitutive equation is used for obtaining the point coordinates; 5)according to the flight height, the scanning angel and the instantaneous scanning angel, the other points coordinates in the same scanning row are obtained by the scanning mode; 6) a direct method is used for producing a rough correction image. The invention improves the geographical accuracy of the avigation remote sensing, and is an innovation of the remote sensing technology under the conditions of no gesture information and improves the time effectiveness, so the avigation remote sensing technology can be better applied to the production and livelihood of the national economy.

A method of modelling a flight of an aircraft using at least one computer system is disclosed. In one embodiment, the method includes: sourcing flight details from at least one data source using at least one data acquisition system, the flight details representative of the activity of the aircraft within a flight information region, and compiling a flight model from the flight details using a processing system, the flight model indicating the activity of the aircraft over the duration of the flight in two or more FIRs or for an entire flight undertaken in a single FIR.

The invention discloses a method, a device and a system for navigating an unmanned aerial vehicle. The method comprises the following steps of obtaining a target area image collected by a binocular image collecting device which is arranged on the unmanned aerial vehicle; respectively extracting characteristic points of the target area image; detecting and matching the characteristic points, and performing three-dimensional reconstruction on the target area image according to the characteristic points, so as to obtain a three-dimensional model containing three-dimensional coordinate information of a target area; according to a preset flight route and the three-dimensional model, establishing a flight model containing the flight route information, so as to navigate the unmanned aerial vehicle according to the flight model. The method has the advantages that on the basis of the obtained target area image, the flight route of the unmanned aerial vehicle in the target area is determined by an image processing technique, the interference by instable factors is avoided, and the anti-interference property is higher; the stability in the navigation of the unmanned aerial vehicle is favorably improved.

The invention discloses a method for designing an aircraft controller with the nonlinearity, which is used for solving the technical problem that an existing robust control principle is lack of design steps, so that a flight controller is difficult to directly design. The invention adopts the technical scheme that a robust stable solvability condition of a system with an uncertain nonlinear term is given out; closed-loop expectation poles fed back by a state of a linear system are directly utilized to select; and according to the characteristic that real parts of all the closed-loop expectation poles are all negative numbers, a limiting condition inequality is given out to directly design a feedback matrix. Therefore, engineering technicians in the research field can directly design the flight controller for a flight model with the uncertain nonlinear term, which is obtained by a wind tunnel or flight test; and the technical problem that in the current research, only a robust stability inequality is given out so as not to directly design the flight controller is solved.

The invention relates to a modeling method for a flight/propulsion system/jet flow noise comprehensive real-time model. The modeling method comprises the following steps: establishing a jet flow noisereal-time prediction model; establishing a component-level model of the turbofan engine with the large bypass ratio; establishing a kinetic model and a kinematics model of the double-engine transporter; and synthesizing and correcting a flight/engine/jet noise model. The invention discloses a noise reduction method for an aircraft. According to a traditional method, a flight system, a propulsionsystem and noise calculation are generally carried out separately; the inter-system coupling relationship is difficult to fully consider; the problem that the noise condition in the whole flight process cannot be covered is solved. According to the method, the problems that the calculation amount is large, and the jet flow noise cannot be calculated in real time according to flight and engine states are solved, a jet flow noise real-time prediction model is established and combined with a flight model and an engine nonlinear model, and real-time simulation of the flight state, the engine performance and the jet flow noise is achieved.

The invention provides a method for pre-estimating flight path of a wind tunnel free flight test model, and the method comprises the steps: 1, obtaining an attack angle - mechanics coefficient table of a flight model; 2, setting the initial attack angle value theta0 of a free flight test, a transmission position, and an initial transmission speed, obtaining the mechanics coefficient at the initial attack angle value theta0 through linear interpolation, and enabling the initial attack angle value theta0 and the corresponding mechanics coefficient to serve as an initial transmission parameter D0; 3, calculating and obtaining pre-estimated flight path data through a Runge-Kutta method after flight at the transmission position; 4, repeatedly carrying out the steps 2 and 3 when the pre-estimated flight path data does not meet the testing requirements, obtaining a new pre-estimated flight path, and carrying out step 4 till the new pre-estimated flight path meets the testing requirements. The method pre-estimates the flight path of free flight of a model in a wind tunnel, enables the flight path to stay for longer tie in an observation region, and obtains more effective information during testing.

The invention discloses a planning system for a fly-around route of a civil aviation airplane in bad weather. The planning system comprises a data input module for acquiring weather data and scheduledflight data, a route calculation module for dynamically calculating the fly-around route according to data input by the data input module, and a route output module for displaying the fly-around route output by the route calculation module on a map; the scheduled flight data comprises scheduled flight plan route data, scheduled flight real-time position data, a flight speed of a scheduled flight,a flight direction of the scheduled flight and scheduled flight model data. According to the planning system and method for the fly-around route of the civil aviation airplane in the bad weather provided by the invention, the system can be changed in real time according to conditions to plan a new route in real time, so that the flight safety of the scheduled flight is improved; furthermore, thefly-around cost of the scheduled flight is reduced; the working amount of commanding the scheduled flight to fly around by a controller is reduced; meanwhile, the fly-around efficiency of the scheduled flight is improved.

The embodiment of the present invention proposes a dynamic pricing method combined with passenger information, including: a flight pricing model establishment step for establishing a flight pricing model based on flight OD information, reservation information, and flight sales information; flight pricing based on user information The model adjustment step is used to adjust the flight pricing model according to the user's user information and historical purchase records; the price determination step is to calculate the appropriate price in real time according to the constructed pricing model, and at the same time give feedback on the sales situation, calibrate the model, and use Calculated on the next price.

The present invention provides a flight model satellite test method and system of a minisatellite. The method comprises the steps of (S1) carrying out thermal modification on a flight model satellite, (S2) loading a satellite for the flight model satellite, (S3) carrying out vacuum testing on the flight model satellite, and (S4) carrying out multiple-layer heat insulation material coating finishing on the flight model satellite. According to the method and the system, the overall task targets of low cost, short cycle and large volume of the minisatellite are achieved, the flight model test verification of the minisatellite is simply and rapidly completed, and the development cost and development cycle of a flight model development phase thermal control satellite are reduced.

The invention discloses a controller design method for an aircraft lag model, which is used for solving the technical problem that an existing robust control principle is lack of design steps, so that a flight controller is difficult to directly design. The invention adopts the technical scheme that a robust stable solvability condition of a time lag system is given out; closed-loop expectation poles fed back by a state of a linear system are directly utilized to select; and according to the characteristic that real parts of all the closed-loop expectation poles are all negative numbers, a limiting condition inequality is given out to directly design a feedback matrix. Therefore, engineering technicians in the research field directly designs the flight controller for a flight model with a time lag uncertainty, which is obtained by a wind tunnel or flight test; and the technical problem that in the current research, only a robust stability inequality is given out so as not to directly design the flight controller is solved.

The invention provides a low-speed aircraft aerodynamic parameter vehicle-mounted testing method and system. The low-speed aircraft aerodynamic parameter vehicle-mounted testing system comprises a carrier (1), a force measuring bench unit (2), a data collection unit (3), a control unit (4) and a measuring and controlling unit (5), wherein the force measuring bench unit (2), the data collection unit (3), the control unit (4) and the measuring and controlling unit (5) are mounted on the carrier (1); the measuring and controlling unit (5) transmits a current testing flying parameter to the control unit (4); the control unit (4) transmits a corresponding control instruction to the force measuring bench unit (2) according to the received flying parameter; an aircraft or a flying model is mounted on the force measuring bench unit (2); under the control of the control unit (4), the force measuring bench unit (2) adjusts a flying attitude of the aircraft or the flying model; the data collection unit (3) collects wind pressure of the head part of the aircraft or the flying model and transmits the wind pressure to the measuring and controlling unit (5); the measuring and controlling unit transmits an instruction according to the wind pressure to control the carrier to adjust a running speed so that the wind speed of the head part reaches a preset wind speed; and the data collection unit(3) is informed to collect aerodynamic parameters of the aircraft or the flying model and transmit the aerodynamic parameters to be measuring and controlling unit (5) to be stored.

The invention discloses an adaptive flying path prediction method of an aircraft automatic near-field collision avoidance system. The method comprises following steps of A, collecting flying state andposition information data from a flight management system, and taking the collected information as state input of step B; B, resolving the state input according to a maneuver avoidance basic controllaw so as to obtain basic output; C, delivering compensation output for unmodeled dynamic uncertainty of an aircraft model and external interference approximation by using an interference observer based on a functional neural network, assisting controlling by using an RC link with robustness gain adaptively regulated so as to obtain compensation output; and D, using a sum of outputs of step B andC as input of a flight model, and resolving state and position information of step i. The method establishes a more complete state equation, improves flying path prediction accuracy, lowers Auto-GCASfalse alarm rate, makes Auto-GCAS more effective, and combines with the flight management system, flight control system and other avionics systems, thereby effectively guaranteeing flight security ofaircrafts.

The invention discloses a man-machine work efficiency evaluation and optimization design method, and belongs to the field of overall design of helicopters. The method comprises the following steps: step 1, constructing a digital model machine according to overall model number requirements and man-machine work efficiency design requirements; step 2, regulating a man-machine work efficiency index system according to the overall model number requirements and the man-machine work efficiency design requirements; step 3, manufacturing a physical engineering model machine according to the constructed digital model machine; step 4, regulating a man-machine work efficiency design and evaluation outline according to the man-machine work efficiency index system; step 5, performing man-machine work efficiency evaluation on then experimental physical engineering model machine onsite according to the man-machine work efficiency design and evaluation outline, and optimizing the designed digital model machine; and step 6, producing a test flight model machine according to the optimized model machine technical scheme, and performing multiple times of evaluation and gradual optimization on the optimized model machine. By adoption of the man-machine work efficiency evaluation and optimization design method disclosed by the invention, the efficiency, the scientificity and the accuracy of man-machine work efficiency design and evaluation in a research process can be improved, and the corresponding cost and resource wastes are reduced.

The invention provides a longitudinal flight model cluster man-machine closed-loop composite root locus multi-stage PID robust controller design method. According to the method, a model cluster composed of amplitude-frequency properties and phase-frequency properties within a whole envelope is directly determined and obtained through a sweep-frequency flight test under the condition that different heights and Mach numbers are given; according to military standard requirements for amplitude-frequency margins and phase margins within a flight envelope, closed-loop pole distribution limiting indicators under a corresponding root locus description are given, and the stage number and parameter values of a multi-stage PID robust controller are determined by additionally arranging a multi-stage PID controller according to the closed-loop pole distribution limiting indicators and a model identification method in system identification within the whole envelope of a flying machine; a low-altitude flight controller is designed by starting from the concept of closed-loop pole distribution limiting under the root locus description, wherein the low-altitude flight controller accords with the whole flight envelop and is free of pilot induced oscillation, low in overshoot and stable.

The invention discloses an unmanned aerial vehicle dunking and rebounding self-evolution intelligent system and control method. The unmanned aerial vehicle intelligent system comprises a four-rotor unmanned aerial vehicle, three cameras, a flight controller, an airborne central processor, a ground data processing base station and a basketball shooting device. The control method comprises a controlmethod of a double-under-stability system and a control method for self-evolutionary learning of the unmanned aerial vehicle. According to the control method of the double-under-stability system, estimated interference is added to an unmanned aerial vehicle under-stability flight model, an interference compensator is designed for approximation in order to compensate the counter-acting force of the estimated interference on the unmanned aerial vehicle, so that unstable factors caused by the estimated interference to the unmanned aerial vehicle can be eliminated, the closed-loop performance ofthe whole double-under-stability system can be enhanced, and the self-repairing of the flying state of the unmanned aerial vehicle can be realized. The control method for self-evolutionary learning ofthe unmanned aerial vehicle is a control method obtained by combining a mechanism model and a data model, wherein the mechanism model is used for establishing rules for a flight track of a basketball, and the data model is used for carrying out learning training through a certain number of samples.

The invention provides a design method for a longitudinal flight model cluster flutter-restraining composite root-locus compensation robust controller. According to the design method, a model cluster composed of amplitude-frequency characteristics and phase-frequency characteristics in a whole envelope is determined directly through frequency sweep flight tests with different heights and different Mach numbers given; a closed-loop pole distribution limiting index described by a corresponding root locus is given according to military standard requirements for amplitude-frequency margin and phase margin, a multi-stage tandem lag-lead compensating controller is additionally arranged, and therefore the number of stages and parameter values of a multi-stage tandem lag-lead compensation robust controller are determined through a model identification method in a closed-loop pole distribution limiting index and system identification process in the whole envelope of an air vehicle; a low-altitude flight robust controller which is capable of restraining flutter, small in overshoot and steady and accords with a whole flight envelope is designed from the conception of closed-loop pole distribution limiting described by a root locus.

The invention provides a design method of a longitudinal flight model cluster composite root-locus multi-level PID (proportion integration differentiation) controller. The design method includes: directly determining and acquiring a model cluster constituted according to amplitude-frequency and phase-frequency characteristics within the full envelop through sweep flight tests on set conditions of different heights and different Mach numbers; according to military standard requirements on amplitude-frequency margin and phase margin, providing the closed-loop pole distribution limit index corresponding to root-locus description, determining number of levels and parameter values of the multi-level PID controller by a model identification method applied to system identification according to requirements of the closed-loop pole distribution limit index within the full envelope of an aircraft after adding the multi-level PID controller; designing the small-overshoot stable low-altitude flight controller capable of meeting requirement of the flight full envelop from the concept of root-locus description based closed-loop pole distribution limit.

The invention relates to an ultra-high speed flight model front light and shadow imaging device. A time sequence controller of the imaging device is used for triggering the light emitting of a light source and the starting of all the cameras according to the time sequence, and all the cameras are started synchronously. Pulse laser beams generated by the light source are coupled and output throughoptical fibers, are collimated by a first collimating lens and then irradiated to a flight model in a test area. The collimated light beams passing through the flight model are converged through a second collimating lens, and a shadow camera is arranged at the position of 1 cm to 10 cm away from the focal point of the second collimating lens. The imaging main axis of the first front light camera and the imaging main axis of the second front light camera are arranged in a mirror symmetry mode, and the first and second front light cameras are used for imaging the illumination surface of the flight model. The device is used for simultaneously obtaining the front light image and the shadow image of a flight model.

The invention discloses an unmanned aerial vehicle obstacle avoidance method based on deep reinforcement learning, and the method comprises the following steps: 1), building an unmanned aerial vehicle obstacle avoidance flight model in a three-dimensional space, and randomly generating the number and position of obstacles, and the starting point of an unmanned aerial vehicle; (2) establishing an environment model based on a Markov process framework, (3) selecting actions based on states and strategies, enabling the unmanned aerial vehicle to interact with the environment to generate a new state after taking the actions, calculating an obtained reward, forming quaternions by the states, the actions, the reward and the actions at the next moment, and storing the quaternions in a sample space through an improved method for sample sampling training; 4) performing network updating on a sample obtained by sampling the environment model by adopting an improved DDQN algorithm, and assigning a state-action pair of the sample; and 5) selecting an optimal action according to the assignment of each action in the state in the sample, and further obtaining an optimal strategy. The invention provides the reinforcement learning obstacle avoidance method adopting the segmentation sampling pool, and the training efficiency of the generation strategy is improved.

The invention provides a semi-physical simulation system and method for unmanned aerial vehicle attacking moving target diving flight, and belongs to the field of unmanned aerial vehicle semi-physical simulation systems, and the system comprises a main control computer which is used for setting the initial positions and motion parameters of a simulation rack, a radiation source and an unmanned aerial vehicle reconnaissance load; motion information of the unmanned aerial vehicle and the radiation source is displayed in real time; the analog simulation computer is used for setting a vector signal source and unmanned aerial vehicle reconnaissance load signal parameters; motion of the unmanned aerial vehicle and the radiation source under the set condition is simulated and analyzed, and scaling mapping is carried out; the simulation rack is used for driving the unmanned aerial vehicle reconnaissance load and the radiation source to simulate according to the set position, attitude and motion state; real-time radiation source position, unmanned aerial vehicle reconnaissance load position and attitude information are transmitted to the analog simulation computer; and the unmanned aerial vehicle reconnaissance load is used for transmitting reconnaissance load sensor data to the analog simulation computer. The flight model of the unmanned aerial vehicle in the target diving attack stage is realized, and the method has reference and practicability.

The external form structure of flying vehicle ralates to the fields of space, aviation, flight model and toy technology, and its technical scheme is as follows: the bottom portion of the self-body is made into the form of the dish, its top portion also is made into the form of the dish whose centre portion of outward projected, after said two dishes are combined, a form whose centre is thick and perphery is thin. Said flying vehicle can be suitable for lifting and falling on the water and ground. Its external form is simple, and aerodynamic resistance is small.

The invention provides a design method of a longitudinal flight model cluster flutter-suppression composite root-locus multi-level PID (proportion integration differentiation) robust controller. The design method includes: directly determining and acquiring a model cluster which is constituted according to amplitude-frequency and phase-frequency characteristics within the full envelop through sweep flight tests on set conditions of different heights and different Mach numbers; according to military standard requirements on amplitude-frequency margin and phase margin, providing the closed-loop pole distribution limit index corresponding to root-locus description, determining number of levels and parameter values of the multi-level PID robust controller by a model identification method applied to system identification according to requirements of the closed-loop pole distribution limit index within the full envelope of an aircraft after adding the multi-level PID controller; designing the small-overshoot stable low-altitude flight controller capable of suppressing flutter and meeting requirement of the flight full envelop from the concept of root-locus description based closed-loop pole distribution limit.

The invention discloses an unmanned aerial vehicle control method and system, a terminal and an unmanned aerial vehicle. The method comprises the following steps that: a terminal receives an unmannedaerial vehicle flight track sent by a user and sends a control signal to the unmanned aerial vehicle through the network based on the unmanned aerial vehicle flight track so as to control the action of the unmanned aerial vehicle, wherein the unmanned aerial vehicle flight track is obtained by accelerator data, a flight model, and a flight attitude in a preset manner; and the terminal is connectedto the network by means of WIFI. According to the invention, since the terminal l is connected to the network by means of WIFI, the controllable distance of the unmanned aerial vehicle is increased.The terminal receives the unmanned aerial vehicle flight track sent by the user and sends the signal to the e unmanned aerial vehicle via the network based on the unmanned aerial vehicle flight trackso as to control the action of the unmanned aerial vehicle, so that the unmanned aerial vehicle can fly directly based on the flight track preset by the user. The operation is simple. The method is suitable for various groups; the flight distance of the unmanned aerial vehicle is long; and the flight track is controllable.