ITERATIVE OPTIMIZATION FLIGHT MANAGEMENT BASED ON A MODEL

专利摘要:
A system, a computer readable medium, and a method including obtaining flight data for a specific aircraft for a prescribed flight; obtain measurements of current samples of at least one state or output of the specific aircraft; performing on the basis of flight data obtained, current or output measurements, and a mathematical model representing precisely a real operational performance of the specific aircraft and providing a forecast indication of a future performance of the specific aircraft, a control optimization to determine an optimal cost control entry for the prescribed flight; adjusting, in response to a consideration of the actual operational characteristics of the specific aircraft, the optimized control input; and transmitting the tuned optimized control input to the specific aircraft to operate the specific aircraft to minimize the direct operating cost for the prescribed flight.
公开号:FR3064739A1
申请号:FR1852788
申请日:2018-03-30
公开日:2018-10-05
发明作者:Eric Richard Westervelt；Mark Lawrence Darnell；Reza Ghaemi；David LAX
申请人:General Electric Co；
IPC主号:

专利说明:

® FRENCH REPUBLIC
NATIONAL INSTITUTE OF INDUSTRIAL PROPERTY © Publication number: 3,064,739 (to be used only for reproduction orders) (© National registration number: 18 52788
COURBEVOIE © Int Cl ⁸ : G 01 C21 / 20 (2017.01), G 01 C 23/00
A1 PATENT APPLICATION
©) Date of filing: 30.03.18. © Applicant (s): GENERAL ELECTRIC COMPANY— © Priority: 03.31.17 US 15476351. US. @ Inventor (s): WESTERVELT ERIC RICHARD, DAR- NELL MARK LAWRENCE, GHAEMI REZA and LAX (43 Date of public availability of the DAVID. request: 05.10.18 Bulletin 18/40. ©) List of documents cited in the report preliminary research: The latter was not established on the date of publication of the request. (© References to other national documents ® Holder (s): GENERAL ELECTRIC COMPANY. related: ©) Extension request (s): (© Agent (s): CASALONGA.
(□ 4 / FLIGHT MANAGEMENT BY ITERATIVE OPTIMIZATION BASED ON A MODEL.
FR 3,064,739 - A1 (3y) A system, computer readable medium, and a method including obtaining flight data for a specific aircraft for a prescribed flight; obtain measurements of current samples of at least one state or output of the specific aircraft; to carry out, as a function of the flight data obtained, current or output measurements, and of a mathematical model representing precisely an actual operational performance of the specific aircraft and providing a forecast indication of a future performance of the specific aircraft, a control optimization to determine an optimal control input from a cost point of view for the prescribed flight; to adjust, in response to a consideration of the actual operational characteristics of the specific aircraft, the optimized control input; and transmitting the optimized control input set to the specific aircraft to operate the specific aircraft to minimize the direct operating cost for the prescribed flight.
Flight specification 230 232

Flight management by iterative optimization based on a model
The present invention relates generally to flight management, more particularly, systems, devices and functional methods for flight management and applications thereof.
The cost of fuel usually accounts for a large part of operating expenses in commercial aviation. Therefore, functional efficiency and fuel economy are research avenues for improvements in aircraft design and use. The primary focus is on fuel economy technologies, aircraft and engine design, control design, and flight path planning and execution (called flight guidance).
Flight management systems, or FMS acronym, in English terms, on board an aircraft usually determine constant climb, cruise, and descent speeds and cruise altitudes in an effort to reduce or minimize the direct operating cost of DOC acronym in English terms, given the take-off weight and range and assuming a number of factors such as, for example, a constant push to climb and a slow push for the descent. These simplifying assumptions have traditionally been applied to implement practical systems, although such assumptions and simplifications lead to suboptimal performance and compromise fuel savings. In addition, conventional flight control systems are usually reactive to a current state or states of an aircraft. In some aspects, the aircraft control system may respond continuously to current or past aircraft conditions in an attempt to control the operation of the aircraft.
Also, there is a need for systems and methods that improve the optimization problem for flight that are not strictly reactive and without simplifying assumptions to obtain optimal guidance.
According to one embodiment, the object of the present invention is to obtain flight data for a specific aircraft for a prescribed flight; obtaining current sample measurements of at least one state or exit from the specific aircraft; the realization as a function of the flight data obtained, of current or output measurements, and of a mathematical model representing precisely an actual operational performance of the specific aircraft and providing a forecast indication of a future performance of the specific aircraft, d 'control optimization to determine an optimal control input from a cost point of view for the prescribed flight; the adjustment, in response to a consideration of the actual operational characteristics of the specific aircraft, of the optimized control input; and transmitting the optimized control input set to the specific aircraft to operate the specific aircraft to perform the prescribed flight to minimize the direct operating cost for the prescribed flight.
For example, successive sequential instants in time include a time from the initial obtaining of current sample measurements to the end of the prescribed flight.
The flight specification may include a mathematical model including specific tail performance and operational characteristics for the particular aircraft.
The mathematical model models for example at least the particular aircraft, the engines of the specific aircraft, and the atmospheric conditions for flight for a future period of time when the adjusted optimized control input will be used to guide the specific aircraft. .
For example, actual operational characteristics include aspects of a flight control function of the specific aircraft.
At least some of the flight data can be obtained from a source separate and distinct from an on-board system of the particular aircraft.
At least one state of the specific aircraft may include a plurality of states corresponding to a plurality of functions of the specific aircraft.
At least one of the plurality of states may be unknown based on current sample measurements and an estimate for the at least one unknown state is determined, at least in part, based on at least one of the plurality of 'states known from current sample measurements.
According to another embodiment, the invention relates to a system capable of implementing, executing, or implementing at least some of the characteristics of the methods described here. In yet another embodiment, the invention relates to a tangible medium can implement executable instructions which can be executed by a device or system activated by a processor to implement at least some aspects of the methods of the present invention.
For example, successive sequential instants in time include a time from the initial obtaining of current sample measurements to the end of the prescribed flight.
The flight specification may include a mathematical model including specific tail performance and operational characteristics for the specific aircraft.
The mathematical model can model at least the specific aircraft, engines of the specific aircraft, and atmospheric conditions for flight for a future period of time when the adjusted optimized control input will be used to guide the specific aircraft.
For example, actual operational characteristics include aspects of a flight control function of the specific aircraft.
At least some of the flight data can be obtained from a source separate and distinct from an on-board system of the particular aircraft.
At least one state of the specific aircraft may include a plurality of states corresponding to a plurality of functions of the specific aircraft.
At least one of the plurality of states may be unknown based on current sample measurements and an estimate for the at least one unknown state is determined, at least in part, based on at least one of the plurality of 'states known from current sample measurements.
According to another aspect, the invention relates to a computer-readable tangible medium having program instructions executable by a processor stored on it, the medium comprising:
program instructions for obtaining current sample measurements of at least one state or exit from the specific aircraft;
program instructions for carrying out, on the basis of the flight data obtained, current or output measurements, and a mathematical model representing precisely an actual operational performance of the specific aircraft and providing a predictive indication of a future performance of the aircraft. 'specific aircraft in response to a current state or an input from the specific aircraft, a control optimization to determine a control input optimized to minimize a direct operating cost of the specific aircraft for the prescribed flight;
program instructions for adjusting, in response to consideration of the actual operational characteristics of the specific aircraft, the optimized control input;
program instructions for transmitting the tuned optimized control input to the specific aircraft to thereby use it to operate the specific aircraft to perform the prescribed flight to minimize the direct operating cost for a first portion of the prescribed flight; and program instructions to repeat iteratively, at many successive sequential times in time for a remaining portion of the prescribed flight, the operations of obtaining the flight data, of obtaining the measurements of current or output samples, of carrying out control optimization, adjust the optimized control input, and transmit the adjusted optimized control input to the specific aircraft.
For example, successive sequential instants in time include a time from the initial obtaining of current sample measurements to the end of the prescribed flight.
Moments of time sequential in time may include time from the initial sample measurement until the end of the prescribed flight.
For example, the mathematical model models at least the particular aircraft, engines of the particular aircraft, and atmospheric conditions for flight for a future period of time when the adjusted optimized control input will be used to guide the aircraft specific.
Other objects, characteristics and advantages of the invention will appear on reading the following description, given solely by way of non-limiting example, and made with reference to the appended drawings in which:
Figure 1 is an illustrative representation of an example of a schematic diagram of an old flight control system;
Figure 2 is an illustrative representation of an example of a schematic diagram of a forecast flight management system structure, according to an embodiment of the present invention:
Figure 3 is an illustrative example of a flow diagram of a method, according to an embodiment of the present invention:
FIGS. 4A and 4B are illustrative graphs of certain aspects of an iterative method of a forecast flight management structure, according to an embodiment of the present invention: and
Figure 5 is an illustrative representation of a schematic diagram of a system or device which can support the methods according to the invention.
A Flight Management System, or FMS acronym, in conventional English terms, of an aircraft in service today generally determines aspects of a flight plan, including but not being limited to, the speeds and altitudes of climb, cruise, and descent, as well as a trajectory or a complete or partial flight path. At least some of the data used by the FMS to generate the commands and the corresponding flight path (or at least part of it) can be received from a ground-based source. For example, a completed basic flight plan for an aircraft may be received by the FMS and used to determine an "optimized" or, more specifically, fairly personalized flight path for a general type aircraft performing the flight. Other and / or additional data such as, for example, wind and temperature data and aircraft rating for the aircraft may also be received and used by the FMS to calculate the flight plan which may be used for guidance by the aircraft. For example, the flight plan calculated by the FMS can be determined using extended / general statistics and measurements for the aircraft, where the statistical data can represent an average for the aircraft which will travel the calculated flight path, and a number of assumptions regarding aircraft operating characteristics and other performance constraints such as assumed / nominal or averaged air traffic control limits and simplified motion equations can be used for flight plan calculation . In addition, imprecise estimates of aircraft weight and wind aloft can contribute to less than fully optimized flight path determinations. For example, a lookup table or other predetermined static values including averaged command data values (eg, "economical" command speeds and altitudes, etc.) can be referenced by the FMS (or other entity ) and used by the FMS on board the aircraft to build a four-dimensional trajectory (4-D including latitude, longitude, altitude, and time) called "optimized" for the aircraft using the "economic" control targets In which the calculated path can be used to guide the aircraft to the path constructed in a planned time structure.
In some aspects, however, the resulting flight plan calculated by the in-flight / on-board (or other) FMS system (s) may not produce a truly optimized flight path that can be reliably and / or efficiently accomplished for minimize a direct operating cost or "Direct Operating Cost" of DOC acronym in Anglo-Saxon terms, expected. For example, the extent and specificity of flight data (i.e., its level of customization to flight plan, aircraft, time and air traffic conditions, etc., specific) considered and even which can be received, processed, stored, reported, and which can be acted upon by flight management systems (and others) of the aircraft can be limited by the processing power, the memory, and the connectivity capacities of these systems and / or the fidelity of the input data supplied to the FMS.
According to one embodiment, a conventional flight management system can generally be considered to be reactive. That is to say that in certain modes a conventional flight management system can be considered to be reactive since it determines control commands to fly on a specific flight path as a function of past actions and perhaps some common actions. of an aircraft, building on past data events (i.e. looking back).
Referring to Figure 1, an illustrative representation of an example of a system 100 for guidance and navigation of an aircraft including an old conventional control system 105 is shown. The controller 105 includes a vertical navigation module 110 or vertical navigation, acronym VNAV in Anglo-Saxon terms, a flight guidance system 115 or flight guidance system, acronym FGS in Anglo-Saxon terms, and a module autopilot 120 which can cooperate together to form at least part of an on-board control and steering function 105 of a particular aircraft.
The VNAV 110 works to calculate vertical speed commands as a function of altitude deviations from a target path and the FGS 115 performs autopilot and autothrottle functions and generates yaw commands, for example, as a function of the vertical speed control (s) for the control and steering functions. The autopilot 120 further operates to generate lift surface deflections in the form of surface deflection commands which are supplied to aircraft 130 to control the dynamics of the aircraft. In addition, the 105 control and steering function controls the autothrottle to produce thrust. For example, if the air speed decreases below a threshold speed for the flight path of the FMS reference 125, then commands are sent to the autothrottle to regulate an increase in air speed. If the air speed increases above a threshold speed, then the control and steering function 105 can generate a command or indication for a speed reduction (for example, a command executed ίο automatically by the autopilot or an indication to notify a pilot to reduce the speed of the aircraft).
The control and steering function 105 can operate to control the operation of the aircraft 130 on which the system 100 is installed. There may be one or more sensors that are used to measure certain properties of the aircraft and / or the parameters and / or outputs of the aircraft's environment and operation. Sensor data from the sensors can be provided to the control and steering function 105 for feedback control of the aircraft.
According to one embodiment, the present invention includes applying a forecast element aspect to a flight management system or controller to determine optimized aircraft control and navigation commands.
In some examples, some of the systems and methods of the present invention provide greater computational capabilities in comparison to a conventional control and steering function and other aircraft flight controllers. Also, in certain embodiments, a method and a system can use mathematical models of an aircraft, of its engines, and of the future atmospheric conditions to which the aircraft will be subjected when using the control commands generated by the method and system for effectively compensating for unwanted transient performance introduced by the aircraft, its engines, and / or the atmosphere during the execution of the flight plan.
LA Figure 2 is a schematic explanatory diagram of a system 200, according to an exemplary embodiment presented here. In the example of FIG. 2, the system 200 includes a flight management computer or acronym FMC in English terms having a forecast aspect which replaces the control and direction function 105 in FIG. 1. In certain embodiments , the FMC 210 is not limited or constrained to replicate the functionalities of the control and steering function 105 or of other flight and other flight management systems and controllers. In certain aspects of the present invention, the FMC 205 may include additional, fewer, or alternative features in comparison to a conventional aircraft controller or control and steering function. In certain aspects, the FMC 205 can execute all aspects of planning an optimal mission to the execution of this mission on a cell by directly specifying aerodynamic objectives (for example thrust, deflection of control surfaces, etc. .). In this way, the FMC 205 can be an increase and / or an improvement on the previous system (for example, the control and steering function 105 of FIG. 1). In one aspect, the FMC 205 is remote from the control and steering function 105 since the output (s) of FMC 205 from the FMC 205 are fundamentally different from the outputs of, for example, the control and steering function 105.
The FMC 205 includes a model forecast controller which is used to generate control histories and corresponding state trajectories that minimize the direct operating costs (DOC) of a particular aircraft. In some embodiments, a DOC may be but is not limited to a fuel cost to execute a prescribed flight plan or at least parts of it.
In some embodiments, while the system 200 may include at least one or more of the functionalities provided by the components of a control and direction function
105 100 shown in Figure 1 (for example, VNAV, 110, FGS 110 and autopilot 120), the FMC 205 of FIG. 2 does not necessarily include the same type of components or analogous devices that perform identical functions. In some embodiments, the FMC 205 may include technologies, mechanisms, protocols, inputs, and considerations, including but not limited to different types and sources of data, calculation techniques, and mechanisms (e.g., hardware, software, devices, systems and components, etc.), including those that are not known and those that may become known in the future. As such, the FMC 205 is not required to be built on or interfaced with an older system such as, for example, system 100. In addition, system 200 may include functionality, including precision, efficiency and processing power, not provided by a conventional FMS like the type shown in Figure 1.
In some modes, the FMC 205 uses a control methodology in which a common control action is obtained by solving an optimization problem in a series of successive moments in time. In some embodiments, the methodology uses predictive control by model (MPC) to predict future performance of the aircraft and adjust a current control input action (s) to further control the aircraft to operate in an optimized manner.
Referring again to FIG. 2, FMC 205 receives as input a flight specification and other flight data. In some embodiments, the flight specification may include constraints on the aircraft, a departure location / airport of a prescribed flight for a particular aircraft, a destination location / airport for the prescribed flight, performance limits transient for the particular aircraft (i.e., specific tail values, not assumptions and / or averaged or static values, etc.), and other data, including any data that may be included in a flight plan. Other flight data received as input by the FMC 205 may include, in some embodiments, weather forecasts, air traffic control data including, but not limited to, information regarding the execution of the flight plan prescribed of the particular aircraft, and additional relevant data. FMC 205 processes input data (eg flight specification and other flight data) to generate control and trajectory histories to minimize a DOC, in which these commands 230 are used by a control system to control operational aspects of aircraft 227 in the performance of a prescribed flight. Control commands 230 may include, for example, control surface controls to control aircraft surface deflections, engine thrust settings, and other commands to control operation of the aircraft, where the flight control system is represented by VNAV 215, FGS 220, and autopilot 225.
The optimized control command (s) generated by the FMC 205 can be used directly by the flight control system 210 to control an aircraft trajectory. Measurements 235 indicative of a current state or exit from the aircraft are obtained from aircraft 227, where the current state of the aircraft or exit from it is a response to current control commands. The current state of the aircraft can be determined and calculated based on one or more sensor outputs, observations, or derivations of measurable and / or observed behaviors from the particular aircraft. Measurements and / or outputs 235 from aircraft 227 are also replenished in FMC 205.
In response to receipt of measurements and / or outputs 235 indicative of the current state of the aircraft, the FMC 205 uses this information to determine reference commands optimized to minimize a direct operating cost (DOC) to comply with one or more desired transient performance limits of the particular aircraft for the prescribed flight. In consideration of the actual operational characteristics (for example, faults, anomalies, etc.) of the flight control system 210, these optimized reference commands 230 generated (for example, control surface commands to control surface deflections of the aircraft, engine thrust settings, and other commands to control operation of the aircraft) may be updated, adjusted, formed, and / or changed periodically in a continuous effort to control the operation of the aircraft. aircraft in an optimized way.
In some aspects presented here, the system 200 understands how the system will respond (i.e., react) to a reference control signal (230) and determines control commands 232 which are optimized to control the aircraft 227 so that 'it operates as desired (ie, minimizing DOC) given the operational realities of the flight control system 210. In some aspects, the FMC 205 can operate to modify or adjust a reference signal ( that is, a control input) to influence the actual processing characteristics of the flight control system 210. In some embodiments, the system 200 regulates the reference commands 230 generated by the FMC 205 to control the aircraft 227 to fly on optimized trajectories to minimize DOC.
FIG. 3 is an illustrative flowchart of an exemplary embodiment of a method 300. The method 300 can be executed by a system, a device, and combinations thereof, including a flight management controller fully on board an aircraft or distributed over computer systems and networks including a combination of on-board, satellite, and ground systems. In some examples, a system or device comprising a processor can execute program instructions from, for example, an application or an “app” implemented as a tangible medium for carrying out the operations of the method 300. In certain embodiments, at least part of the method 300 can be implemented by software components deployed as software as a service.
In operation 305, flight data for a prescribed flight is obtained. The flight data obtained can come either from an on-board system of a particular aircraft to perform the prescribed flight or from external computer equipment such as a ground system and a satellite system. In certain aspects presented here, external computer equipment refers to a device, system, and component comprising a central unit (i.e., a processor) which is separate and distinct from a flight control system and / or flight management of an aircraft. In some embodiments, computing processing power, processing speed, data access bandwidth capacity, data processing capabilities, interconnectivity capabilities with other systems, and combinations of external computer equipment presented here may be superior to such functionalities of flight control and flight management systems on board an aircraft (that is to say, native). External computer equipment presented here may include technical functionality to interface and communicate with other systems, including but not limited to, other external computer equipment, flight control and flight management systems on board an aircraft , and other types of systems via communication links (eg uplink, downlink) using different communication protocols and techniques.
Flight data may include details of at least one of the particular aircraft and parameters of the prescribed flight. For example, the flight data may include details relating to the particular aircraft and may include characteristics specific to the particular aircraft. Examples may include specific tail characteristics of the aircraft, including, for example, specific performance and operational values for the particular aircraft such as thrust, drag, etc. which can be based on actual (ie past) historical performance, maintenance, and other types of data. Flight data including details of the prescribed flight parameters and may include a completed (basic) flight plan, nominal aircraft characteristics for the particular aircraft (as opposed to actual characteristics for the "particular" aircraft specific), and actual weather or environmental factors at the time the prescribed flight will be performed (as opposed to average weather conditions).
In some embodiments, at least some of the specific details of the flight data for the particular aircraft may include a data model, where the data model includes specific tail characteristics (i.e., performance data and specific to the specific aircraft). The data model for the particular aircraft may include characteristics and parameters, including its values, that are specific to the particular aircraft. In part, the specific details may be based on a history of previous flights made by the particular aircraft.
In some embodiments, the extent (i.e., level of detail and understanding) of the specific tail characteristics for the particular aircraft included in the flight data of operation 305 may be sufficient to such an extent. such that a mathematical database model (or other data structure) representing the aircraft actually corresponds closely to the operational performance in real life of the particular aircraft. Given a high level of correspondence between the data model and the operational performance of the particular aircraft, such an accurate data model is here called "digital double" of the particular aircraft. The digital double includes an updated and accurate account of key features / aspects of the particular aircraft. The extent and precision of a data model for the particular aircraft in certain embodiments presented here greatly contributes to the ability for the method 300 to generate specific optimized path controls and an optimized path. In some examples, the performance of an optimization performed by the method 300 is improved and increased to obtain a lower DOC due, at least in part, to the use of a digital double in certain embodiments.
In some embodiments, data may be collected (i.e., observed, recorded, and retained) for a specific aircraft over time. The detailed data collected (for example, data including but not limited to thrust, drag, and other parameters) can be used to construct an accurate database mathematical model for the particular aircraft. In some aspects, a mathematical model for a particular aircraft presented here can be updated repeatedly, at least periodically, when the particular aircraft is used. The time intervals for the update can be triggered or called in response to a change in the aircraft specific characteristic data, significant maintenance changes, etc. In such use cases, the updated mathematical model can be used to perform a revised control optimization to generate an updated control entry (s) from the cost perspective.
During operation 310, measurements of current samples or taken out of the aircraft are obtained. Current and / or output measurements are the result of the aircraft's response to certain reference or initial input control command (s). Current measurements and / or outputs can be obtained directly from sensors and other aircraft devices or systems and, in some examples, derived from other measurements or outputs.
Continuing during operation 315, the FMC of certain embodiments presented here is used to perform control optimization to determine an optimal control input from a cost perspective for the prescribed flight to minimize a DOC of the prescribed flight for the aircraft. The optimized control input is generated based on, at least in part, flight data obtained during operation 305, current measurements and / or outputs received during operation 310, and a mathematical model representing specifically actual operational performance of the specific aircraft and providing a predictive indication of future performance of the specific aircraft. The mathematical model accurately represents operational performance in the real world of the specific aircraft, including operational performance of the aircraft and the engines configured with it. In some aspects, the mathematical model can also accurately represent a performance of the control and steering function of the specific aircraft.
During operation 320, the optimized control input signal determined during operation 315 can be adjusted, modified, or otherwise formed to take into account the dynamics of the specific aircraft, including operational aspects of its control and direction function. In certain embodiments, the flight management controller of the specific aircraft (for example, the FMC 205 in the example of FIG. 2) or another system having such functionality can know malfunctions, anomalies and other real-world characteristics of the aircraft (for example, as represented by a mathematical database model) and consider these aspects to adjust the optimized control input.
During operation 325, the adjusted optimized control input formed during operation 320 is transmitted to the system or to the control and direction function of the aircraft (for example, 210 in FIG. 2) and their subsystems (for example, VNAV 215, FGS 220, autopilot 225, etc.), which in turn use the tuned optimized control input (s) to control the movement of the aircraft to perform the prescribed flight optimally, minimizing DOC as desired.
Operation 330 includes iteratively repeating operations 305 to 325 for a series of successive instants in time until the prescribed flight is performed by the aircraft. In some examples, the method 300 can be carried out repeatedly for a period of time corresponding to an entire extent of a prescribed flight plan. In some scenarios, however, process 305 to 325 operations can be performed during only a particular part of a prescribed flight, such as one or more of an ascent, cruise, and descent part of a prescribed flight.
In some embodiments, the optimization performed by a method presented here, as but not limited to method 300, may include a predictive model control (MPC) method where a current control action (for example, a control input ) is obtained or determined by solving an online optimization problem at each sampling instant over time. In part, the MPC uses dynamic constraint optimization at each sampled time instant and the controller adapts to the current state of the system (for example, the aircraft) to reject disturbances and anomalies, to influence multi interactions - variables of system components and subsystems, and to optimize system performance under real operating conditions. The optimization problem can be formed as an optimal open loop control problem with a finite horizon where a current state of the system is used as an initial state and a sequence of control actions in the finite horizon is the solution to the problem. optimization.
MPC's methodology uses an aircraft model. The model provides a mechanism for the MPC process to make predictions for the future and consider the effects of changes in current input (for example, control commands 230 in Figure 2) on the evolution of future system performance (for example, aircraft 227). In some embodiments, techniques and methods other than MPC can be used to predict and optimize other operation of an aircraft.
In some embodiments, data may be collected (i.e., observed, recorded, and retained) for a specific aircraft over time. Detailed collected data (for example, past data indicative of and / or including but not limited to thrust, drag, and other parameters) can be used to construct an accurate data model for the particular aircraft. In some aspects, a data model for a particular aircraft presented here may be updated repeatedly when the particular aircraft is in use. The time intervals for the update may be triggered or called in response to a change in the aircraft specific characteristic data. The updated data model can be used to perform a revised control optimization to generate updated optimized route specific controls for the prescribed flight.
In some embodiments, the data model can accurately and fully express the actual stresses on the aircraft during the prescribed flight, including parameters directly related to the airframe, aircraft engines, fuel weight, stresses in airspace including the prescribed flight, weather conditions experienced during the flight, air traffic control alarms, etc. In certain aspects, the data model presented here, in addition to accurately and sufficiently representing the aircraft at a level of certainty to generate optimized controls, can also be favorable to optimization and computer efficient in such a way that the problem of optimal control can be resolved in real time to be achievable.
Still looking at some of the Aspects of the MPC in the context of the present invention, a first control action (for example, a reference control command (s)) is applied to the system and at a next sampling instant the optimization problem is posed and solved again with the finite horizon shifted by a sampling time. Since the control commands entered into the system are the result of a finite horizon optimization problem, relevant and real operational constraints of the system can be targeted and dealt with explicitly by the MPC by expressing these constraints in terms of variables decision and adding them to the optimization problem in such a way that they are taken into account in the optimization solution.
In some aspects, an MPC method presented here can be summarized as including (1) detecting measured or exited states of the subject system (i.e., an aircraft), (2) estimating states of the system which are necessary for the optimization problem but not directly measured or detected, where the estimates can be derived, calculated, or otherwise determined by one or more of the non-limiting methods presented here (for example, using a Kalman filter, etc. .); (3) to solve the problem of optimal constrained control over a finite horizon (for example, minimizing the DOC for a particular aircraft performing a prescribed flight); (4) apply the first sample of optimal control to the system; (5) repeating steps (1) - (4) again at each next time instant.
FIGS. 4A and 4B illustrate some aspects of the predictive and feedback correction aspects of the MBM process presented here. FIG. 4A includes a graph 405 in which an optimal control profile 415 is calculated for the entire forecast horizon 420 at time k (402). The calculated control profile ensures that the planned output 410 at time k satisfies the performance objectives and the system constraints. Only the first sample of the input is implemented up to time step k + 1. FIG. 4B includes graph 430 having an optimal control profile 440 which is calculated for the entire forecast horizon 445 at time k + 1 (432). At time k + 1, a new series of optimal control (s) 440 are calculated to take into account the non-correspondence to the model and disturbances. The planned output 435 satisfies the performance objectives and the system constraints.
FIG. 5 is a schematic explanatory diagram of the device 500 according to an example of certain embodiments. The device 500 can include a computer device and can execute program instructions to perform any of the functions described here. The device 500 may include a server implementation, a dedicated processor device, and other systems, including systems deployed in the aircraft and systems deployed in, for example, external computer equipment or facility, in certain modes of achievement. The device 500 can include other elements not shown according to certain embodiments.
The device 500 includes a processor 505 operatively coupled to the communication device 515 for communicating with other systems, a data storage device 530, one or more input devices 510 for receiving inputs from other systems and entities, one or more output devices 520 and a memory 525. The communication device 515 can facilitate communication with other systems and components, such as other external computer equipment, an air traffic control network, and an aircraft. The 510 input device (s) may include, for example, a keyboard, mouse or other pointing device, a microphone, a button or switch, an infrared (IR) port, a docking station, and / or a touch screen. The input device (s) 510 can be used, for example, to enter information into device 500. The output device (s) 520 can be understood, for example, a display (for example, a display screen) a speaker, and / or a printer.
Data storage device 530 can include any suitable data storage device, including combinations of magnetic storage devices (e.g., magnetic tape, hard drives and flash memory), semiconductor storage devices , optical storage devices, read only memory (ROM) devices, random access memory (RAM), SCM memory or any other fast access memory. The data storage device 530 can store flight data plans, a control command optimized by certain embodiments presented here, etc.
Optimization engine 535, aircraft data modeler 540, and application 545 may include program instructions executed by processor 505 to cause device 500 to perform any one or more of the methods presented herein, including but not limited to aspects shown in FIG. 3. The embodiments are not limited to the execution of these processes by a single device.
Data 550 (either cached or an entire database) can be stored in volatile memory such as memory 525. The data storage device 530 can also store data and other program code to provide additional functionality and / or which are necessary for the operation of the device 500, such as device drivers, operating system files, etc. The data 550 may include aircraft-related performance data which can be used for future modeling of aircraft data for optimization purposes.
List of games
Number Description
100 SYSTEM
105 CONTROL AND STEERING FUNCTION 110 VERTICAL NAVIGATION MODULE
115 FLIGHT GUIDANCE SYSTEM
120 AUTOMATIC PILOT
125 FMS FLIGHT ROUTE
130 AIRCRAFT
200 SYSTEM
205 FLIGHT MANAGEMENT COMPUTER (FMC)
210 FLIGHT MANAGEMENT SYSTEM
215 VERTICAL NAVIGATION MODULE
220 FLIGHT GUIDANCE SYSTEM
225 AUTOMATIC PILOT
227 AIRCRAFT
230 REFERENCE CONTROL SIGNAL
232 CONTROL SIGNAL
235 MEASUREMENTS AND OUTPUTS
300 ORGANIZATION CHART
305 PROCESS OPERATION
10 PROCESS OPERATION
15 PROCESS OPERATION
320 PROCESS OPERATION
325 PROCESS OPERATION
330 PROCESS OPERATION
405 GRAPHIC
402 TIME k
410 PLANNED EXIT
OPTIMAL CONTROL PROFILE
FORECAST HORIZON
GRAPHIC
TIME k + 1
PLANNED EXIT
OPTIMAL CONTROLS
FORECAST HORIZON
SYSTEM
PROCESSOR
INPUT DEVICE (S)
COMMUNICATION DEVICE MEMORY OUTPUT DEVICE (S)
STORAGE FACILITY
OPTIMIZATION ENGINE
AIRCRAFT DATA MODELER
APPLICATION
DATA

权利要求:
Claims (20)
[1" id="c-fr-0001]
1. A method implemented by a processor of a computer system to optimize an aircraft guidance to minimize a direct operating cost of a prescribed flight, the method comprising:
obtaining flight data including a flight specification and other flight data for a prescribed flight, the flight specification including at least flight constraints, a departure location, a destination location, and limits transient performance; and other flight data including weather forecast and air traffic control information relating to the prescribed flight;
obtaining current sample measurements from at least one state or exit from the specific aircraft;
the production, by a processor of computer equipment of the specific aircraft and as a function of the flight data obtained, current or output measurements, and of a mathematical model representing precisely an actual operational performance of the specific aircraft and providing a predictive indication of future performance of the specific aircraft in response to a current state or input of the specific aircraft, control optimization to determine a control input optimized to minimize direct operating cost of the aircraft specific for the prescribed flight;
the adjustment, in response to a consideration of the actual operational characteristics of the specific aircraft, the optimized control input;
the transmission of the optimized control input set to the specific aircraft so as to use it to operate the specific aircraft to execute the prescribed flight to minimize the direct operating cost for a first part of the prescribed flight; and the iterative repetition, at numerous successive sequential instants in time for a remaining part of the prescribed flight, the operations of obtaining the flight data, of obtaining measurements of current or output samples, of optimizing the control, adjust the optimized control input, and transmit the adjusted optimized control input to the specific aircraft.
[2" id="c-fr-0002]
2. Method according to claim 1, in which the successive sequential instants in time include a time from the initial obtaining of the measurements of current samples until the end of the prescribed flight.
[3" id="c-fr-0003]
The method of claim 1, wherein the flight specification comprises a mathematical model including specific tail performance and operational characteristics for the particular aircraft.
[4" id="c-fr-0004]
The method of claim 3, wherein the mathematical model models at least the particular aircraft, engines of the specific aircraft, and atmospheric conditions for flight for a future period of time when the optimized control input set. will be used to guide the specific aircraft.
[5" id="c-fr-0005]
The method of claim 1, wherein the actual operational characteristics include aspects of a flight control function of the specific aircraft.
[6" id="c-fr-0006]
6. The method of claim 1, wherein at least some of the flight data is obtained from a source separate and distinct from an on-board system of the particular aircraft.
[7" id="c-fr-0007]
7. The method of claim 1, wherein the at least one state of the specific aircraft includes a plurality of states corresponding to a plurality of functions of the specific aircraft.
[8" id="c-fr-0008]
The method of claim 7, wherein at least one of the plurality of states is unknown based on current sample measurements and an estimate for the at least one unknown state is determined, at least in part, based on at least one of the plurality of states known from current sample measurements.
[9" id="c-fr-0009]
9. System comprising:
a memory (525) storing program instructions executable by a processor; and a processor (505) for executing the program instructions executable by a processor for:
obtaining flight data including a flight specification and other flight data for a specific aircraft for a prescribed flight, the flight specification including at least flight constraints, a departure location, a destination location, and transient performance limits; and other flight data including weather forecast and air traffic control information relating to the prescribed flight;
obtain current sample measurements of at least one state or exit from the specific aircraft;
perform, based on the flight data obtained, current or output measurements, and a mathematical model representing precisely an actual operational performance of the specific aircraft and providing a predictive indication of a future performance of the specific aircraft in response at a current state or an input of the specific aircraft, a control optimization to determine an optimized control input to minimize a direct operating cost of the specific aircraft for the prescribed flight;
adjust, in response to a consideration of the actual operational characteristics of the specific aircraft, the optimized control input;
transmits the tuned optimized control input to the specific aircraft to thereby use it to operate the specific aircraft to execute the prescribed flight to minimize the direct operating cost for a first part of the prescribed flight; and repeat iteratively, at successive sequential instants in time for a remaining part of the prescribed flight, the operations of obtaining the flight data, of obtaining the measurements of current or output samples, of carrying out the optimization of the control, to adjust the optimized control input, and to transmit the optimized control input set to the specific aircraft.
[10" id="c-fr-0010]
10. System according to embodiment 9, in which the successive sequential instants in time include a time from the initial obtaining of the measurements of current samples until the end of the prescribed flight.
[11" id="c-fr-0011]
11. The system of claim 9, wherein the flight specification comprises a mathematical model including specific tail performance and operational characteristics for the specific aircraft.
[12" id="c-fr-0012]
The system of claim 11, wherein the mathematical model models at least the specific aircraft, engines of the specific aircraft, and atmospheric conditions for flight for a future period of time when the optimized control input set. will be used to guide the specific aircraft.
[13" id="c-fr-0013]
The system of claim 9, wherein the actual operational characteristics include aspects of a flight control function of the specific aircraft.
[14" id="c-fr-0014]
14. The system of claim 9, wherein at least some of the flight data is obtained from a source separate and distinct from an on-board system of the particular aircraft.
[15" id="c-fr-0015]
15. The system of claim 9, wherein the at least one state of the specific aircraft includes a plurality of states corresponding to a plurality of functions of the specific aircraft.
[16" id="c-fr-0016]
The system of claim 15, wherein at least one of the plurality of states is unknown based on current sample measurements and an estimate for the at least one unknown state is determined, at least in part, based on at least one of the plurality of states known from current sample measurements.
[17" id="c-fr-0017]
17. Computer-readable tangible medium having program instructions executable by a processor stored thereon, the medium comprising:
program instructions for obtaining current sample measurements of at least one state or exit from the specific aircraft;
program instructions for carrying out, on the basis of the flight data obtained, current or output measurements, and a mathematical model representing precisely an actual operational performance of the specific aircraft and providing a predictive indication of a future performance of the aircraft. 'specific aircraft in response to a current state or an input from the specific aircraft, a control optimization to determine a control input optimized to minimize a direct operating cost of the specific aircraft for the prescribed flight;
program instructions for adjusting, in response to consideration of the actual operational characteristics of the specific aircraft, the optimized control input;
program instructions for transmitting the tuned optimized control input to the specific aircraft to thereby use it to operate the specific aircraft to perform the prescribed flight to minimize the direct operating cost for a first portion of the prescribed flight; and program instructions to repeat iteratively, at many successive sequential times in time for a remaining portion of the prescribed flight, the operations of obtaining the flight data, of obtaining the measurements of current or output samples, of carrying out control optimization, adjust the optimized control input, and transmit the adjusted optimized control input to the specific aircraft.
[18" id="c-fr-0018]
18. Support according to claim 17, in which the successive sequential instants in time include a time from the initial obtaining of the measurements of current samples until the end of the prescribed flight.
[19" id="c-fr-0019]
19. Support according to claim 17, in which the instants of sequential time in time include a time from the initial obtaining of the sample measurements until the end of the prescribed flight.
[20" id="c-fr-0020]
20. Support according to claim 19, in which the mathematical model models at least the particular aircraft, engines of the particular aircraft, and atmospheric conditions for the flight for a future period of time when the optimized control input is set. will be used to guide the specific aircraft.
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法律状态:
2019-02-19| PLFP| Fee payment|Year of fee payment: 2 |

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2020-02-20| PLFP| Fee payment|Year of fee payment: 3 |

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2020-08-07| PLSC| Publication of the preliminary search report|Effective date: 20200807 |

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2021-02-18| PLFP| Fee payment|Year of fee payment: 4 |

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2022-02-21| PLFP| Fee payment|Year of fee payment: 5 |

优先权:

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申请号 | 申请日 | 专利标题

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US15476351|2017-03-31|

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US15/476,351|US10832581B2|2017-03-31|2017-03-31|Flight management via model-based iterative optimization|

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