AIRCRAFT CONTROL OPTIMIZED BY ITERATIVE OPTIMIZATION 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 including a mathematical model that accurately represents a performance of the specific aircraft and provides a forecast indication of a future performance of the aircraft specific in response to a current state or an entry of the specific aircraft; obtain measurements of current samples of at least one state or output of the specific aircraft; performing, based on the flight data and current measurements and outputs obtained, control optimization to generate optimized control commands to minimize the direct operating cost of the prescribed flight; transmitting the optimized control commands to the particular aircraft for use in operating the particular aircraft to perform the prescribed flight; and iteratively repeating the process operations at successive sequential instants in time for a period of at least a portion of the prescribed flight.
公开号:FR3064606A1
申请号:FR1852779
申请日:2018-03-30
公开日:2018-10-05
发明作者:Mark Lawrence Darnell；Reza Ghaemi；David LAX；Eric Richard Westervelt
申请人:General Electric Co；
IPC主号:

专利说明:

© Publication no .: 3,064,606 (to be used only for reproduction orders)
©) National registration number: 18 52779 ® FRENCH REPUBLIC
NATIONAL INSTITUTE OF INDUSTRIAL PROPERTY
COURBEVOIE © Int Cl ⁸ : B 64 D 45/00 (2017.01), B 64 D 43/00
A1 PATENT APPLICATION
©) Date of filing: 30.03.18. © Applicant (s): GENERAL ELECTRIC COMPANY— © Priority: 31.03.17 US 15476409. US. @ Inventor (s): DARNELL MARK LAWRENCE, GHAEMI REZA, LAX DAVID and WESTERVELT ERIC (43) Date of public availability of the RICHARD. 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.
FR 3 064 606 - A1 (04) OPTIMIZED AIRCRAFT CONTROL BY ITERATIVE OPTIMIZATION BASED ON A MODEL.
©) A system, computer readable medium, and method including obtaining flight data for a specific aircraft including a mathematical model which accurately represents a performance of the specific aircraft and provides a predictive indication of future performance of the aircraft. 'specific aircraft in response to a current state or input from the specific aircraft; 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 and current measurements and outputs obtained, a control optimization in order to generate optimized control commands to minimize the direct operating cost of the prescribed flight; transmit the optimized control commands to the particular aircraft so that it uses them to operate the particular aircraft to perform the prescribed flight; and repeating iteratively the operations of the method at successive sequential instants in time for a duration of at least part of the prescribed flight.
Flight specification

i
Aircraft control optimized 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).
A flight management system or “Flight Management Systems”, acronym FMS in English terms, on board an aircraft usually determines 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 while 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 result in suboptimal performance and compromise fuel savings. In addition, conventional flight control systems are usually reactive to the current state 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 control that are not strictly reactive and without simplifying assumptions to obtain optimal guidance.
According to one embodiment, the present invention relates to obtaining flight data including a flight specification and other flight-related data for an aircraft specific for a prescribed flight; obtaining sample measurements from at least one state or exit from the specific aircraft; carrying out, based on flight data and current or output measurements, a control optimization to generate optimized controls to minimize a direct operating cost of the prescribed flight; the guidance, in response to receipt of the optimized controls, of the particular aircraft according to the controls optimized to execute the prescribed flight; the iterative repetition, at successive sequential instants in time for a duration of at least part of the prescribed flight, of the operations of obtaining sample measurements, carrying out optimization of the control, and guiding the '' particular aircraft according to optimized controls.
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 mathematical model may include specific tail performance and operational characteristics for the specific aircraft.
The mathematical model can model at least the particular aircraft, engines of the particular aircraft, and atmospheric conditions for flight for a future period of time when the generated optimized specific route controls will be used to guide 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 specific aircraft.
For example, at least one state of the specific aircraft includes a plurality of states corresponding to a plurality of functions of the specific aircraft.
For example, at least one of the plurality of states is unknown based on the 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 states from current sample measurements.
For example, the current state or entry to the particular aircraft is set based on a current state or an exit from the particular aircraft.
According to another aspect, the invention relates to a system can implement, execute, or implement at least some of the characteristics of the methods presented here.
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.
For example, the mathematical model includes specific tail performance and operational characteristics for the specific aircraft.
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 generated optimized optimized route controls will be used to guide the aircraft specific.
For example, at least some of the flight data is obtained from a source separate and distinct from an on-board system of the specific aircraft.
For example, at least one state of the specific aircraft includes a plurality of states corresponding to a plurality of functions of the specific aircraft.
For example, at least one of the plurality of states is unknown based on the 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 states from current sample measurements.
For example, the current state or entry to the particular aircraft is adjusted based on a current state or an exit from the particular aircraft.
According to a second 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 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 a mathematical model that accurately represents operational performance in the real world of the specific aircraft and provides a predictive indication of future performance of the specific aircraft in response to a current state or an entrance to the specific aircraft; and other flight data including weather forecast and air traffic control information relating to the prescribed flight;
program instructions for obtaining current sample measurements of at least one state or exit from the specific aircraft;
program instructions for carrying out, as a function of the flight data and current or output measurements obtained, a control optimization to generate optimized control commands to minimize a direct operating cost of the prescribed flight, the optimized controls generated including, at the less, control surface controls, engine thrust controls, and combinations thereof;
program instructions for transmitting the optimized control commands to the particular aircraft for use in operating the particular aircraft to perform the prescribed flight; and program instructions to repeat iteratively, at successive sequential instants in time for a duration of at least part of the prescribed flight, the operations of obtaining the measurements of current samples or outputs, of carrying out the optimization of the control, and transmit the optimized control commands to the particular aircraft.
For example, successive sequential instants in time include a time from the initial obtaining of the sample measurements to the end of the prescribed flight.
For example, the mathematical model includes specific tail performance and operational characteristics for the specific aircraft.
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 generated optimized optimized route controls 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 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 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 that results from the speed and altitude control inputs. At least some of the data used by the FMS to generate the controls and the corresponding flight path (or aspects and parts thereof) 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" flight plan or, more specifically, a fairly personalized flight plan 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. In some aspects, 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 the operating characteristics of the aircraft and other performance constraints such as assumed / nominal or averaged air traffic control limits and simplified equations of motion can be used to calculate the vehicle trajectory resulting from the control inputs defined by the flight plan. 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 construct a four-dimensional trajectory (4D including latitude, longitude, altitude, and time) called “optimized” for the aircraft using “economic” control targets, where the calculated control can be used to guide the aircraft to the planned route in a given time frame.
In some aspects, however, the resulting flight plan calculated by the on-board FMS system (s) (or others) may not produce a truly optimized flight path that can be reliably and / or efficiently tracked by the flight control system to minimize the direct operating cost or acronym "Direct Operating Cost" of DOC acronym in Anglo-Saxon terms. For example, the extent and specificity of flight data (i.e., their level of adaptation to the flight plan, aircraft, weather and air traffic conditions, etc., specific) considered and even being able to be received, processed, stored, reported, and which can be acted on 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.
For example, a conventional flight management system can be generally considered to be reactive. The conventional flight management system can be considered reactive since it determines control commands to fly on a specific flight path based on past actions and perhaps some common actions of an aircraft, based on on past data events.
Referring to FIG. 1, an illustrative representation of an example of a system 100 for guidance and navigation of an aircraft including an old conventional control and direction function 105 is shown. A control and direction function 105 includes a vertical navigation module 110, or vertical navigation, of acronym VNAV in Anglo-Saxon terms, a flight guidance system 115, or flight guidance system, of acronym FGS in Anglo terms -saxons, and an automatic pilot module 120 called auto pilot in Anglo-Saxon terms which can cooperate together to form at least part of the control and steering function 105 of a particular aircraft.
The VNAV 110 works to calculate vertical speed commands, for example, 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 FMS vertical speed control command (s) to minimize deviation from the target path. The autopilot 120 further operates to generate elevator surface deflections in the form of surface deflection commands which are provided to the aircraft 130 to control the movement of the aircraft relative to the desired movement along the target path. . In addition, the control and steering function 105 can control the operation of the autothrottle, for example, to reach an established target speed by controlling the speed of the aircraft within safe operating margins. For example, if the speed in the air decreases below a threshold speed for the flight path of the FMS reference 125, then the autothrottle commands the autothrottle to regulate an increase in the speed in the air. If the speed in the air 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 automatically by the autopilot or an indication to notify a pilot to reduce the speed of the aircraft). The autothrottle can also operate, for example, to keep the aircraft engines at a fixed power setting as a function of the different phases of a flight (for example, takeoff, climb, cruise, descent, etc.).
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 environmental and operating parameters. Sensor data from the sensors can be provided, as an input, 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 commands.
In some aspects, some of the systems and method of the present invention provide greater computing capabilities compared to the conventional FMS 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 movements when controlling the aircraft according to the flight plan.
FIG. 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 205 having improved functionality or flight management computer, acronym eFMC in English terms which interfaces and communicates with a particular aircraft 210. The eFMC 205 includes additional functionalities, improved or increased compared to an aircraft flight management system (FMS) or conventional controller such as, for example, the control and steering function 105 in FIG. 1 (although not limited to this). The eFMC 205 may include a model predictive controller which is used to control a flight path of a particular aircraft and a closed-loop performance of the particular aircraft. Some embodiments presented here include aspects of predicting future performance of a particular aircraft and determining a current or current control input for the aircraft which can be used for guidance and control of the aircraft. In certain embodiments, the commands or control inputs determined by certain embodiments presented here can be optimized to minimize a direct operating cost (DOC) such as, but not limited to, the fuel cost for a prescribed flight plan or at least parts of it.
In some embodiments, the system 205 can replace functionality provided by the components of the FMS 100 shown in FIG. 1. In some aspects, an eFMC here "replaces" a system such as, for example, the control and steering function 105 in FIG. 1 by determining and transmitting control signals to aircraft 210 to directly and effectively monitor aircraft performance ’in a desired manner.
In some aspects, the eFMC may not be limited or restricted to determine the control commands it can transmit to an aircraft in a manner identical or even similar to, for example, a control and steering function 105. In some embodiments, factors, considerations, mechanisms, algorithms, and method for determining control commands (e.g., aircraft speed, aircraft attitude, etc.) of an eFMC presented here may be different from those used by an FMS.
In some aspects, the eFMC 205 uses a control methodology in which a common control action is obtained by solving an optimization problem in a series of successive sampling instants over time. In some embodiments, the methodology uses predictive control by model (MPC) to predict future performance of the aircraft and set a current control input action (s) to further control the aircraft to operate in an optimized manner.
Referring again to Figure 2, the eFMC 205 receives as input a flight specification and other flight related 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. Other flight data received as input by the eFMC 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 flight of the particular aircraft, and additional relevant data. The eFMC 205 processes the input data (for example, the flight specification and other flight data) to generate a control command (s) based on a forecast aspect (i.e., the knowledge) of the operation of the aircraft system. The control commands thus generated are sent to the particular aircraft 210 to control aspects of the performance of the aircraft. Control commands may include, for example, control surface commands to directly control aircraft surface deflections, engine thrust settings, and other commands to control operation of the aircraft. For example, the eFMC can adjust the signal (s) transmitted to control the aircraft to obtain, for example, a desired performance (for example, a minimized direct operating cost, where the signals are based (at least in part) on measurements and / or exits from aircraft 210.
The control command (s) generated by the eFMC 205 is (are) used by the aircraft 210 to control the trajectory of the aircraft. Measurements 215 indicative of a current state of the aircraft or exits therefrom are obtained from the aircraft 210, where the current state of the aircraft or the exit thereof is a response to commands received from the eFMC 205. The current state or an exit from the aircraft can be determined and calculated based on one or more sensor outputs, observations, or derivations of measurable and / or observed behaviors of the particular aircraft. In addition, measures 215 are fed back into eFMC 205.
In response to receipt of outputs or measurements indicative of the current state of the aircraft, the eFMC 205 uses this information to determine optimized control commands that can minimize direct operating cost to comply with one or more desired transient performance limits of the particular aircraft for the prescribed flight. Optimized control commands generated (for example, control surface commands to control aircraft surface deflections, engine thrust settings, and other commands to control operation of the aircraft) are provided to aircraft 210 in an effort to control the aircraft in an optimized manner.
From a certain point of view, the eFMC, in its capacity to replace a conventional flight management system or another similar element (for example, the control and steering function 105 of Figure 1), can provide a system, process and / or mechanism that is more technically efficient, elegant, and sophisticated than an FMS and similar systems, including their many components, (sub) systems and modules.
In some aspects presented here, the system 200 understands how the system (e.g., aircraft 210) will respond to a reference control signal and determines control commands which are optimized to control the aircraft to operate from the desired way (i.e., minimize DOC). The system 200 regulates or sets the control commands generated by the eFMC 205 to obtain the desired output from the system (ie, the operation of the aircraft to obtain the DOC).
FIG. 3 is an illustrative flow diagram 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 (eg , eFMC 205 in FIG. 2) fully on-board an aircraft or distributed over computer systems and networks including a combination of on-board and ground systems. In some examples, a system or device having a processor can execute program instructions from, for example, an application or "app" implemented as a tangible medium for performing the operations of the method 300. In some embodiments, at least part of the method 300 can be implemented by software components deployed as software as a service or a platform 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 execute the prescribed flight or from external computer equipment. In certain aspects presented here, external computer equipment refers to a device, system, and component having a central processing 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 these external computer equipment presented here may be greater than and / or an alternative to such functionalities of flight control and flight management systems on board an aircraft (ie, 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 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 data model (or other data structure) representing the aircraft actually corresponds closely to the real-life operational performance 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 duplicate may include an updated and accurate account of key characteristics / 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 optimized specific path controls and an optimized trajectory based on forecast aspects of performance of the particular aircraft. 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 and to a prospective or forecast performance for the particular aircraft.
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 data model for the particular aircraft. In some aspects, a data model for a particular aircraft presented here can be updated repeatedly, at least periodically, when the particular aircraft is in use. The time intervals for the update can be triggered or called up in response to a change in aircraft specific characteristic data, significant maintenance changes, etc. In some use cases, the updated data model can be used to perform a revised control optimization to generate updated updated specific route controls.
During operation 310, measurements of aircraft samples are obtained. Current measurements are the result of the aircraft's response to certain reference or initial input command (s) and may be indicative of at least one specific aircraft condition. In some embodiments, at least one output of the specific aircraft is obtained during operation 310. The output obtained during operation 310 can provide an overview of how the particular aircraft responds to an input signal reference or initial.
Continuing during Operation 315, the FMC functionally described here is used to perform control optimization to generate specific path controls optimized to minimize a DOC of the flight prescribed for the aircraft. The optimized control commands are generated based, at least in part, on the flight data obtained during operation 305 and the current measurements or outputs received during operation 310.
During operation 320, the optimized control commands are supplied to the aircraft and thus used to guide the aircraft according to the specific path controls optimized so that the prescribed flight can be performed in an optimal manner, minimizing DOC as desired.
Operation 325 includes iterative repetition of operations 305 to 320 for a series of successive moments in time until the prescribed flight is executed 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 certain scenarios, however, the operations of the process 305 to 320 can be carried out 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 method of predictive model control (MPC) where a current control action is obtained or determined by solving a problem online optimization 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.
The MPC methodology uses a precise model of the aircraft. The model provides a mechanism for the MPC process to make predictions for the future and consider the effects of current input changes (for example, control commands) on future performance performance of the system. 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 (ie, observed, recorded, and retained) for a specific aircraft over time (eg, operation 310 of FIG. 3). The detailed data collected (for example, data 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 specific data model reflecting a particular aircraft presented here can 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 check optimization to generate updated optimized route specific checks 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.
Looking again at some of the Aspects of the MPC in the context of the present invention, a first control action (for example, reference control commands) is applied to the system and at a next sampling instant the problem of optimization is rested and resolved again with the finite horizon shifted by a sampling instant. 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 methods without limitation 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 an illustrative schematic 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, the 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, microphone, button or switch, infrared (IR) port, docking station , and / or a touch screen. One (s) 510 input device (s) can be used, for example, to enter information into the device 500. One (s) 520 output device (s) can (include), for example, a display (for example, a display screen) a speaker, and / or a printer.
The data storage device 530 can include any suitable permanent 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), 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 Parties
Number Description
100 SYSTEM
105 CONTROL AND MANAGEMENT FUNCTION
110 VERTICAL NAVIGATION MODULE
115 FLIGHT GUIDANCE SYSTEM
120 AUTOMATIC PILOT
122 COST INDEX
125 FMS FLIGHT ROUTE
130 AIRCRAFT
200 SYSTEM
205 IMPROVED FLIGHT MANAGEMENT COMPUTER (eFMC)
210 AIRCRAFT
215 MEASURES
300 PROCESS
305 PROCESS OPERATION
10 PROCESS OPERATION
15 PROCESS OPERATION
320 PROCESS OPERATION
325 PROCESS OPERATION
400 GRAPHIC
402 TIME k
410 PLANNED EXIT
415 OPTIMAL CONTROL PROFILE
420 FORECAST HORIZON
430 DEVIATION MODEL PARAMETERS
AERODYNAMIC
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 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 a mathematical model that accurately represents operational performance in the real world of the specific aircraft and provides a predictive indication of future performance of the specific aircraft in response to a current state or input specific aircraft; 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; 105 the realization, by a processor of computer equipment of the specific aircraft and as a function of the flight data and current measurements or outputs obtained, a control optimization to generate control commands optimized to minimize a direct operating cost of the prescribed flight, the optimized controls generated including, at a minimum, control surface controls, engine thrust controls, and combinations thereof;
transmitting the optimized control commands to the particular aircraft so that it uses them to operate the particular aircraft to perform the prescribed flight; and iterative repetition, at successive sequential instants in time for a duration of at least part of the prescribed flight, the operations of obtaining measurements of samples or outputs, of carrying out optimization of the control, and of transmitting the control commands optimized for the particular 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 mathematical model includes specific tail performance and operational characteristics for the specific aircraft.
[4" id="c-fr-0004]
4. The method of claim 1, wherein 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 optimized specific path controls generated will be used to guide the specific aircraft.
[5" id="c-fr-0005]
5. Method according to claim 1, in which at least some of the flight data are obtained from a separate and distinct source from an on-board system of the specific aircraft.
[6" id="c-fr-0006]
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.
[7" id="c-fr-0007]
The method of claim 6, wherein at least one of the plurality of states is unknown based on the 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 from the current sample measurements.
[8" id="c-fr-0008]
8. The method of claim 1, wherein the current state or the entry to the particular aircraft is set according to a current state or an output of the particular aircraft.
[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 a mathematical model that accurately represents operational performance in the real world of the specific aircraft and provides a predictive indication of future performance of the specific aircraft in response to a current state or input of the 'specific aircraft; 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, as a function of the flight data and current or output measurements obtained, a control optimization to generate optimized control commands to minimize a direct operating cost of the prescribed flight, the optimized controls generated including, at least, control commands control surface, engine thrust controls, and combinations thereof;
transmit the optimized control commands to the particular aircraft so that it uses them to operate the particular aircraft to perform the prescribed flight; and repeat iteratively, at successive sequential instants in time for a duration of at least part of the prescribed flight, the operations of obtaining the measurements of current or output samples, of carrying out the optimization of the control, and of transmitting the control commands optimized for the particular 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. System according to embodiment 9, in which the mathematical model includes a specific tail performance and operational characteristics for the specific aircraft.
[12" id="c-fr-0012]
12. System according to embodiment 9, 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 specific path controls generated will be used to guide the specific aircraft.
[13" id="c-fr-0013]
13. System according to embodiment 9, in which at least some of the flight data are obtained from a source separate and distinct from an on-board system of the specific aircraft.
[14" id="c-fr-0014]
14. System according to embodiment 9, in which the at least one state of the specific aircraft includes a plurality of states corresponding to a plurality of functions of the specific aircraft.
[15" id="c-fr-0015]
15. System according to embodiment 14, in which at least one of the plurality of states is unknown as a function of the sample measurements and an estimate for the at least one unknown state is determined, at least in part, as a function of at least one of the plurality of states from the current sample measurements.
[16" id="c-fr-0016]
16. System according to embodiment 9, in which the current state or the entry to the particular aircraft is adjusted as a function of a current state or an exit from the particular aircraft.
[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 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 a mathematical model that accurately represents operational performance in the real world of the specific aircraft and provides a predictive indication of future performance of the specific aircraft in response to a current state or an entrance to the specific aircraft; and other flight data including weather forecast and air traffic control information relating to the prescribed flight;
program instructions for obtaining current sample measurements of at least one state or exit from the specific aircraft;
program instructions for carrying out, as a function of the flight data and current or output measurements obtained, a control optimization to generate optimized control commands to minimize a direct operating cost of the prescribed flight, the optimized controls generated including, at the less, control surface controls, engine thrust controls, and combinations thereof;
program instructions for transmitting the optimized control commands to the particular aircraft for use in operating the particular aircraft to perform the prescribed flight; and program instructions to repeat iteratively, at successive sequential instants in time for a duration of at least part of the prescribed flight, the operations of obtaining the measurements of current samples or outputs, of carrying out the optimization of the control, and transmit the optimized control commands to the particular 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 sample measurements until the end of the prescribed flight.
[19" id="c-fr-0019]
19. Support according to claim 17, in which the mathematical model includes a specific tail performance and operational characteristics for the specific aircraft.
[20" id="c-fr-0020]
20. Support according to claim 17, 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 specific path controls generated will be used to guide the specific aircraft.
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优先权:

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申请号 | 申请日 | 专利标题

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US15/476,409|US20180286253A1|2017-03-31|2017-03-31|Optimized aircraft control via model-based iterative optimization|

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US15476409|2017-03-31|

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