CN114510070A - Automatic near-ground collision avoidance optimal control method for aircraft - Google Patents
Automatic near-ground collision avoidance optimal control method for aircraft Download PDFInfo
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Abstract
The invention discloses an automatic near-ground collision avoidance optimal control method for an aircraft, which comprises the following steps of A, acquiring aircraft state data; b, acquiring terrain elevation data; step C, establishing a nonlinear kinematics/dynamics model function; step D, establishing a flight constraint function; step E, establishing an optimal control cost functional and carrying out optimization calculation on weight parameters in the cost functional by using an intelligent optimization algorithm so as to obtain an optimal control strategy; and step F, controlling the aircraft to fly by the flight control system of the aircraft according to the optimal control strategy. The invention has the beneficial effects that: the method can comprehensively consider the state characteristics and performance constraints of the aircraft, and the optimal control method of the automatic near-ground collision avoidance system can improve the accuracy and effectiveness of the automatic near-ground collision avoidance maneuver, reduce the false alarm rate, improve the flight safety of the aircraft, and fully exert the mission efficiency of the aircraft.
Description
Technical Field
The invention relates to the technical field of aviation control, in particular to an optimal control method for automatic near-ground collision avoidance of an aircraft, which comprises specific products such as an automatic near-ground collision avoidance system, an automatic air collision avoidance system, a near-ground warning system, a terrain perception and warning system and the like.
Background
An Auto Ground Collision Avoidance System (Auto-GCAS) improves the Flight safety of an aircraft and reduces a controllable Flight impact accident (CFIT). The core of the method is that based on the dynamic characteristics of the aircraft, the flight trajectory of the aircraft is calculated and predicted in real time according to the current state information of the aircraft; utilizing airborne digital terrain data and according to the flight track of the aircraft, and solving a predicted land collision area in real time through a terrain scanning algorithm; calculating through a ground collision evaluation algorithm, and comparing the flight track with a predicted ground collision area; when the ground collision assessment threshold is met, immediately sending a ground collision prevention request to a flight control system; triggering the maneuver of leveling and pulling up the aircraft to ensure the flight safety without the override of the driver; meanwhile, ground collision avoidance warning information is sent to the cockpit display and control system. The method can reduce the CFIT incidence under the extreme conditions of high overload consciousness loss or lost direction of pilots and the like, and is mainly applied to aircrafts for high-speed flight, large-motor low-altitude combat tasks.
Auto-GCAS belongs to a new technology at home, has been researched for many years abroad, is applied to partial models of fighters, and plays an important role in flight safety. Lockheed Martin airlines, usa, are major research and development manufacturers of automated near-earth collision avoidance system equipment worldwide. Recent data indicate that the army 03 months in 2019 completed all tests of the on-line Auto GCAS for the F-35 fighter. Up to now, the American fighters F-16, F-22 and F-35 have been or have reached a fitted state.
The performances of climbing performance, minimum turning radius and the like of aircrafts of different models are obviously different, and the performance difference directly influences the design of an evasive maneuvering track of an automatic near-ground collision avoidance system and the generation of an evasive maneuvering command. If a certain safety threshold value is added to the automatic collision avoidance algorithm, the aircraft can be relatively easily ensured to avoid the terrain. However, in order to ensure that the Auto GCAS achieves a low false alarm rate and a low false alarm rate, exert the maximum combat efficiency of the aircraft, and make good use of the maneuvering performance of the aircraft, it is necessary to optimally control the avoidance maneuver of the Auto GCAS.
Disclosure of Invention
The invention discloses an automatic near-ground collision avoidance optimal control method for an aircraft, which is used for calculating an optimal and timely effective Auto GCAS avoidance maneuvering track by combining climbing capacity, overload constraint, minimum turning radius and other performances of the aircraft through an optimal control method.
The invention provides an optimal control method of an automatic near-ground collision avoidance system of an aircraft, which comprises the following steps,
step A: acquiring state information data such as the current flight position and flight attitude of the aircraft from flight management systems such as an inertial navigation system and an atmospheric data system of the aircraft;
and B: extracting topographic data in a certain range around the current position of the airplane as the center from a topographic database;
and C: establishing a nonlinear kinematics/dynamics model function of the aircraft according to various parameters of the aircraft;
step D: establishing a flight constraint function of the aircraft according to the kinematic/dynamic characteristics of the aircraft and the evasion maneuver requirements of the automatic near-ground collision avoidance system;
step E: on the basis of the aircraft state data and the terrain data acquired in the step A and the step B, a cost functional of optimal control of the aircraft automatic near-ground collision avoidance system is established by adopting a nonlinear kinematics/dynamics model function and a flight constraint function;
step F: selecting an intelligent optimization algorithm to carry out optimization solution on the weight parameters in the cost functional in the step E to obtain final optimal control;
step G: and D, substituting the optimal coefficient matrix obtained by calculation in the step F into the step E, resolving to obtain an optimal result, returning the optimal result to the flight control system of the aircraft, and operating the aircraft to fly according to an optimal control law so as to realize optimal control of the automatic near-ground collision avoidance system.
Further, the state information data of the current position, flight attitude and the like of the aircraft in the step A comprise longitude, latitude, track inclination and the like provided by positioning systems such as inertial navigation equipment, a GPS/Beidou system and the like, and air pressure altitude, vacuum speed and the like provided by an air data computer;
further, the terrain database of step B is an international universal terrain database (Jeppesen, SRTM, etc.), and includes elevation data of terrain and corresponding latitude and longitude information. And B, calculating a latitude and longitude variation range of a certain range around the aircraft according to the latitude and longitude of the current position of the aircraft acquired in the step A, reading corresponding terrain elevation data from a terrain database according to the latitude and longitude variation range obtained by calculation, generating the terrain elevation data of a determined range by processing modes of cutting, splicing and the like of the elevation data, and setting the range to be 5km multiplied by 5km for subsequent steps.
Further, the nonlinear kinematics/dynamics model function of the aircraft in step C is different according to different aircraft and different requirements of system performance, computational performance, etc., and the established model function is also different, which may be adaptively changed according to specific aircraft.
Furthermore, the flight motion model of the general aircraft in step C mainly includes two types, namely a six-degree-of-freedom model and a three-degree-of-freedom model, wherein the six-degree-of-freedom model can better reflect the change of the attitude of the aircraft compared with the three-degree-of-freedom model, and the method described herein focuses more on the track control change of the aircraft, so that a simplified three-degree-of-freedom particle model is taken as an example for explanation. The details are further described in the detailed description.
Considering the instantaneity of the automatic near-ground collision avoidance maneuver of the aircraft, the three-degree-of-freedom model function is established based on the following three-point assumption:
a) the aircraft keeps the current airspeed unchanged;
b) the aircraft is not influenced by external uncertain factors such as wind speed and the like;
c) the aircraft is only used as a particle model and does not consider the change of the attitude motion of the aircraft.
The kinematic equation set is as follows:
the system of kinetic equations is shown below:
wherein x, y and z in the equation set are the representation of the position information of the aircraft in a geographic coordinate system, gamma is a track inclination angle, and V istIs the flight vacuum speed, chi is the track azimuth, mu is the track roll angle, NzIs normally overloaded.
Furthermore, the establishment of the maneuver avoiding flight constraint function of the automatic near-ground collision avoidance system in the step D mainly includes the aspects of the predicted time constraint of the flight track prediction function module, the distance constraint of the minimum ground clearance of the aircraft of the terrain scanning function module, the performance constraint of the normal overload of the aircraft of the automatic maneuver avoidance function module, the performance constraint of the roll angle and the roll angular rate in the maneuvering process of the aircraft, and the like according to the functional characteristics of the automatic near-ground collision avoidance system. The details are further described in the detailed description.
Further, the cost functional of the optimal control of the automatic near-earth collision avoidance system of the aircraft in the step E is established, in order to meet the most appropriate maneuvering response planning, the optimal control law u based on the allowable control domain A is planned by solving the minimized cost functional*(t), therefore, the cost functional is established as follows:
further, the optimal control law u in the cost functional of step E*(t) in the present invention mainly includes track roll angle control mu (t) and normal overload control Nz(t)。
Further, the weight parameters in the optimization step E of step F may be selected from different intelligent optimization algorithms, including but not limited to neural networks, particle swarm optimization, biomimetic algorithms, legacy algorithms, and the like.
And further, the optimal control result of the step G is crosslinked with the automatic flight control system of the aircraft only when the automatic near-ground collision avoidance system near-ground collision avoidance evaluation function module sends out an alarm signal, the optimal control law is sent to the flight control system, the aircraft is controlled to execute automatic maneuver evasion, and the automatic near-ground collision avoidance optimal control of the aircraft is realized.
The optimal control method for automatic near-ground collision avoidance of the aircraft can guarantee the timely effectiveness of the automatic near-ground collision avoidance, reduce the false alarm rate and the false alarm rate, give full play to the task efficiency of the aircraft, and comprehensively guarantee the flight safety of the aircraft by combining with airborne systems such as a flight management system, a flight control system and the like under the condition of considering the performance constraint and the maneuvering constraint of the aircraft.
Drawings
The invention will be further explained with reference to the drawings.
FIG. 1 illustrates a motorized avoidance path schematic of an automatic near-horizon collision avoidance optimization control in accordance with an embodiment of the present invention.
FIG. 2 illustrates a schematic architectural diagram of an automatic near-ground collision avoidance optimization control in accordance with an embodiment of the present invention.
Detailed Description
The technical solution of the present invention is described below by using preferred embodiments, but the following embodiments do not limit the scope of the present invention.
The optimal control method for the automatic near-ground collision avoidance of the aircraft is built in the aircraft in a software mode and is provided with any device with data acquisition, processing, output and storage functions, such as near-ground warning equipment, a flight control system, a flight management system, a comprehensive environment monitoring system, a health management system and other avionics or flight control equipment. In addition, the automatic near-ground collision avoidance optimal control method of the aircraft is suitable for any aircraft with the near-ground collision avoidance requirement.
FIG. 1 is a schematic diagram of a motorized avoidance path for automated near-horizon collision avoidance optimization control formed in accordance with one embodiment of the present invention. A maneuvering avoidance path (c) in the attached figure 1 is an automatic ground-approaching anti-collision optimal control avoidance path of the aircraft according to the method; although the maneuvering evasion path I has the near-earth anti-collision effectiveness, the maneuvering evasion path I is easily judged as a false alarm by a pilot; and the maneuvering evasion path triggers maneuvering at the collision critical time, so that false alarm is reduced, and safety and effectiveness cannot be guaranteed.
Referring to fig. 2, the flight management system such as inertial navigation system and atmospheric data system of the aircraft collects the current flight position and flight attitude of the aircraft, including the current position information x, y, z, track inclination angle γ, flight vacuum velocity VtTrack azimuth χ;
referring to fig. 2, terrain elevation data within a certain range (5km × 5km) around the current position of the aircraft is extracted from a terrain database;
referring to FIG. 2, a non-linear kinematics/dynamics model function of an aircraft is established based on various parameters of the aircraft
Wherein the state variable X is [ X, y, z, gamma, chi ]]TControl input u ═ Nz, μ]TThe specific relational expression is as follows:
referring to fig. 2, a flight constraint function of the aircraft is established according to the kinematics/dynamics of the aircraft and the avoidance maneuver requirements of the automatic ground proximity collision avoidance system, and mainly includes a predicted time constraint of a flight path prediction function module, a distance constraint of the minimum ground clearance of the aircraft of a terrain scanning function module, a performance constraint of the aircraft of an automatic maneuver avoidance function module on normal overload, and performance constraints of a roll angle and a roll angle rate in the aircraft roll maneuver process, and the like, which are specifically shown as follows.
Constraint function μ (t) for roll angle control:
μmin≤μ(t)≤μmax
constraint function of normal overload nz (t):
1g≤Nz(t)≤c·Nzmax
wherein c represents a weight coefficient, the value is changed according to the flight characteristics of the aircraft and the bearing capacity of the pilot, the value range is (0,1), and NzmaxMaximum overload designed for aircraft.
Referring to the attached figure 2, based on the aircraft state data and the terrain data acquired in the step A and the step B, establishing a cost functional J for optimal control of the aircraft automatic near-ground collision avoidance system by adopting an aircraft model function and a flight constraint function:
where R is a weight coefficient matrix for flight control, which can be expressed as
Referring to the attached figure 2, an intelligent optimization algorithm is selected to optimize and solve the coefficients of the weight coefficient matrix R in the cost functional in the step E, and final optimal control is obtained;
referring to the attached figure 2, substituting the optimal coefficient matrix obtained by calculation in the step F into the step E, calculating to obtain an optimal result, and returning the optimal result to a flight control system of the aircraft.
Referring to fig. 2, the aircraft is controlled to fly according to the optimal control law according to the control instruction of the flight control system, so as to realize the optimal control of the automatic near-ground collision avoidance system.
It should be noted that the above description is based on specific embodiments of the invention, and although the invention has been described in detail with reference to preferred embodiments, it will be understood by those skilled in the art that modifications and equivalent substitutions can be made to the technical solution of the present invention without departing from the spirit and scope of the technical solution of the present invention.
Claims (9)
1. An optimal control method for automatic near-ground collision avoidance of an aircraft is characterized by comprising the following steps,
step A, acquiring aircraft state data related to the current state of the aircraft in a flight management system of the aircraft;
b, acquiring terrain elevation data of the aircraft, which are related to the current position of the aircraft, in a terrain database of the aircraft;
step C, establishing a nonlinear kinematics/dynamics model function about the aircraft;
step D, establishing a flight constraint function related to the aircraft;
step E, based on the aircraft state data and the terrain elevation data, adopting the nonlinear kinematics/dynamics model function and the flight constraint function to establish a cost functional about optimal control of an automatic near-ground collision avoidance system of the aircraft, and performing optimization solution on weight parameters in the cost functional by using an intelligent optimization algorithm to obtain an optimal control strategy; and the number of the first and second groups,
and F, controlling the aircraft to fly by the flight control system of the aircraft according to the optimal control strategy.
2. The method according to claim 1, wherein in step a, the aircraft state data comprises a position of the aircraft, a track pitch angle of the aircraft, an air pressure altitude of the aircraft, and a flight vacuum speed of the aircraft.
3. The method for optimally controlling automatic ground collision avoidance of an aircraft according to claim 1, wherein in the step B, the terrain elevation data relates to an area within a certain range centered on the current position of the aircraft; further, the range is 5km × 5 km.
4. The method as claimed in claim 1, wherein in step C, the nonlinear kinematics/dynamics model function is a six-degree-of-freedom model or a three-degree-of-freedom model.
5. The optimal control method for automatic near-earth collision avoidance of the aircraft according to claim 4, wherein the step C takes the instantaneity of the automatic near-earth collision avoidance maneuver of the aircraft into consideration, and when a three-degree-of-freedom model function is established, the three-point assumptions are as follows:
a) the aircraft keeps the current airspeed unchanged;
b) the aircraft is not influenced by external uncertain factors such as wind speed and the like;
c) the aircraft is only used as a particle model and does not consider the change of the attitude motion of the aircraft.
The kinematic equation set is as follows:
the system of kinetic equations is shown below:
wherein x, y and z in the equation set are the representation of the position information of the aircraft in a geographic coordinate system, gamma is a track inclination angle, and V istIs the flight vacuum speed, chi is the track azimuth, mu is the track roll angle, NzIs normally overloaded.
6. The method as claimed in claim 1, wherein in step D, the flight constraint function is established according to a predicted time constraint of a flight path prediction function module, a distance constraint of a minimum ground clearance of an aircraft of a terrain scanning function module, a performance constraint of a normal overload of the aircraft of an automatic maneuver avoidance function module, and a performance constraint of a roll angle and a roll rate during a roll maneuver of the aircraft.
7. The method according to claim 1, wherein in step E, the optimal control law u based on allowable control domain a is planned by solving the minimized cost functional*(t), therefore, the cost functional is established as follows:
the optimal control law u in the cost functional of step E*(t) in the present invention mainly includes track roll angle control mu (t) and normal overload control Nz(t)。
8. The aircraft automatic ground collision avoidance optimal control method according to claim 1 or 7, wherein in the step E, the intelligent optimization algorithm is a neural network, a particle swarm algorithm, a bionic algorithm or a legacy algorithm.
9. The method as claimed in claim 1, wherein in step F, the optimal control strategy is cross-linked with the flight control system of the aircraft in automatic flight only when the automatic near-ground collision avoidance system near-ground collision avoidance evaluation function module sends out an alarm signal.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117991819A (en) * | 2024-04-07 | 2024-05-07 | 中国人民解放军陆军指挥学院 | Unmanned aerial vehicle flight control method |
| CN117991819B (en) * | 2024-04-07 | 2024-06-04 | 中国人民解放军陆军指挥学院 | Unmanned aerial vehicle flight control method |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN117991819A (en) * | 2024-04-07 | 2024-05-07 | 中国人民解放军陆军指挥学院 | Unmanned aerial vehicle flight control method |
| CN117991819B (en) * | 2024-04-07 | 2024-06-04 | 中国人民解放军陆军指挥学院 | Unmanned aerial vehicle flight control method |
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