CN106959609A - Based on the most credible method of estimation of aircraft accident sequence of events for mixing PREDICTIVE CONTROL - Google Patents

Based on the most credible method of estimation of aircraft accident sequence of events for mixing PREDICTIVE CONTROL Download PDF

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Publication number
CN106959609A
CN106959609A CN201710201385.1A CN201710201385A CN106959609A CN 106959609 A CN106959609 A CN 106959609A CN 201710201385 A CN201710201385 A CN 201710201385A CN 106959609 A CN106959609 A CN 106959609A
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China
Prior art keywords
state
sequence
estimation
moment
events
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CN201710201385.1A
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Inventor
高振兴
王浩锋
吴东苏
孔祥骏
顾宏斌
俞力玲
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Nanjing University of Aeronautics and Astronautics
China Academy of Civil Aviation Science and Technology
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Nanjing University of Aeronautics and Astronautics
China Academy of Civil Aviation Science and Technology
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    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B13/00—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
    • G05B13/02—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
    • G05B13/04—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators
    • G05B13/042—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators in which a parameter or coefficient is automatically adjusted to optimise the performance

Abstract

The invention discloses based on the most credible method of estimation of aircraft accident sequence of events for mixing PREDICTIVE CONTROL, belong to the technical field of flight visual simulation and flight safety.The present invention assign aircraft virtual condition as system anticipated output, handle input and interference are regarded as system input, simultaneously system model is used as using flying simulation model, the Model Predictive Control problem that a control system is converted into the problem of manipulation event and external interference is inferred in crash analysis, so that the model predictive control method during application control is theoretical realizes the most credible estimation of sequence of events in aircraft accident.

Description

Based on the most credible method of estimation of aircraft accident sequence of events for mixing PREDICTIVE CONTROL
Technical field
The invention discloses based on the most credible method of estimation of aircraft accident sequence of events for mixing PREDICTIVE CONTROL, and in particular to A kind of method of the optimal estimating non-normal hours sequence in crash analysis, belongs to the technology of flight visual simulation and flight safety Field.
Background technology
For the aviation accident analysis of causes, it can often find that accident phenomenon is possible to much conflicting occur or seen Like unrelated failure, many senior pilots and machinist think that such case can not possibly occur.But accident investigator Conventional wisdom is that：Two or more incoherent system, parts, while or it is small probability to break down in succession in a short time Event.All accident phenomenons are all to have a fundamental cause, then occur a series of sequence of events, and last event is exactly Accident.Previous event is the cause of latter event, and latter event is the consequence of previous event.This just as many meters of Buddhist nun's dominoes, If one card is taken out in centre, the board of back would not fall, and accident would not occur.This analytic approach is generally also event chain point Analysis method.During application affairs link analysis method, some events relevant with cause of accident is first found out from many events, is sent out according to event Raw event sequence and causality, are analyzed ring by ring, list event chain, then event is analyzed one by one.Generally this It is required for crash analysis personnel manually to carry out logic analysis, takes time and effort very much, also easily analyze error result.
For specific aircraft accident, it is desirable to utilize practical flight casualty data and the flight dynamics model set up, The estimation most probable sequence of events that accidents happened occurs during Fast simulation, is real-time Simulation instead of artificial estimation sequence of events There is provided and instruct.The aircraft accident of current commercialization reproduces emulation and analysis software, is all by the FDR numbers in accident aircraft black box According to carrying out the playback of driving cabin instrument and vision simulation environment, and CVR voice recordings that temporal registration crosses are added to aircraft accident Whole process is reproduced, but does not estimate the function of abnormal event sequence automatically.
In fact the flight model for being used for aircraft accident analysis is typically a hybrid system, and hybrid system is continuous system With the combination of discrete system, include continuous system as kinetic model, also the discrete system including discrete event control system System.For such a system, it is necessary to estimate wherein be most likely to occur sequence of events so that whole hybrid system Simulation data data and practical flight casualty data between error it is minimum.Because the input of these events has scope limitation, And dynamic on-line optimization discrete series is needed, so needing the hybrid system prediction algorithm of advanced design, estimate that accidents happened and send out Most believable abnormal event sequence information when raw, is that air-accident investigation and the analysis of causes provide effective instrument.
The content of the invention
The goal of the invention of the present invention is that there is provided based on the flight for mixing PREDICTIVE CONTROL for above-mentioned background technology not enough Method of estimation that accident event sequence is most credible, the abnormal event sequence of high confidence level is provided for aircraft accident causal investigation, will Sequence of events estimation automation, reduces the workload of analysis personnel, solves people's work point in existing aircraft accident causal investigation The technical problem that analysis accident event chain workload is big, easily malfunction.
The present invention is adopted the following technical scheme that for achieving the above object：
(1) it is typical with some because aircraft accident includes the switching of aircraft dynamics model and a variety of state of flights The feature of hybrid system, sequential logic system, discrete event system as described in the system with multi-tool switching, finite state machine System etc., so aircraft accident is described using MLD models, wherein setting up aircraft dynamics model using the differential equation, together When introduce auxiliary logic variable and be used for describing the switching between different flight state and different flight state；
(2) the constraint value condition to each state variable in flying simulation model carries out the analysis of system, explicit to consider Saturation, the span of state of flight and the handover event set of such as actuator of constraint present in system, input constraint master If the limitation of the amplitude and speed of handle input amount, such as throttle, pedal, the effective breadth of control stick and manipulation rate limitation. State constraint mainly includes the limitation of each state variable in model, the amplitude and rate limitation of such as each rudder face.And design a model Quadratic performance index used in PREDICTIVE CONTROL；
(3) predictive control strategy of the hybrid system based on quadratic performance index is used, passes through line solver MIXED INTEGER Quadratic programming, obtains current optimal control sequence and state estimation, after optimal control sequence is obtained, takes first element conduct The controlled quentity controlled variable at current time, that is, the time during aircraft accident or the estimation of controlled quentity controlled variable, pass through the emulation of a period of time Operation, it is possible to estimate accidents happened generating process stage special event sequence；
(4) the abnormal event sequence estimated, passes through corresponding time point special event in FDR data and CVR data Comparison, confirms final most credible abnormal event sequence.
The present invention uses above-mentioned technical proposal, has the advantages that：Hybrid System Theory and mould are used by comprehensive The event such as handle input and interference, is regarded as system input, aircraft virtual condition is exported as system by type Prediction and Control Technology, The estimation of abnormal event is converted into a constrained hybrid system rolling optimization problem, crash analysis stream can be simplified Journey, sequence of events is estimated to automate, reduces the workload of analysis personnel, helps to find in time important in aircraft accident Time point and anomalous event.
Brief description of the drawings
Fig. 1 is a kind of structural representation of the present invention.
Fig. 2 is the aircraft accident hybrid model schematic diagram under sequence of events driving of the present invention.
Embodiment
The technical scheme to invention is described in detail below in conjunction with the accompanying drawings.
In the implementation process for carrying out the most credible estimation of aircraft accident sequence of events, mainly there are several main steps, wrap Include aircraft accident modeling, the determination of state of flight span and time series, quadratic model object function determine, roll online it is excellent Change and solve MINLP model, most certainty sequence verification, whole flow process is as shown in Figure 1.Specific implementation steps are such as Under.
Basic idea is that the state space of the aircraft by the situation of breaking down or change of configuration carries out subspace segmentation.Each Subsystem in subspace can be by traditional Differential Equation Modeling.Then closed with simple or compound propositional logic System's description is per sub-spaces, and the true and false of proposition uses 0,1 to represent, pass through propositional logic and the equivalence relation of MIXED INTEGER inequality Propositional logic is transformed into MIXED INTEGER linear inequality.Simultaneously logic is introduced in system linearity discrete state equations to become Amount and auxiliary variable, and consider the linear mixed-integer inequality that the primal constraints and propositional logic conversion of system are introduced, The continuous part and logical gate of system and the interaction between them are described, thus by failure feelings under unified framework The discrete event of condition and the continuous process of flight are unified, and such as Fig. 2 is exactly the individual aircraft accident under discrete event control system Hybrid model.
The equation of normal condition aircraft can be expressed as：
X (t+1)=A0x(t)+B0u(t) (1)
Wherein：
X=[Δ u Δ w Δ q Δs θ]T (4)
U=[δe δT]T (5)
When breaking down or during change of configuration, the stability parameter of aircraft is changed, the parameter matrix of equation can be with It is expressed as：
So, the form that total state space equation can be expressed as：
Wherein, q (t) represent break down or change of configuration discrete event.The then state equation under MLD frameworks and mixing Integer inequality can be expressed as：
X (t+1)=Ax (t)+B1u(t)+B2δ(t)+B3z(t) (9)
E2δ(t)+E3z(t)≤E1u(t)+E4x(t)+E5 (10)
Wherein,
B2=0 (13)
B3=[B31 B32 B33 B34 B35] (19)
Then by aircraft accident sequence of events most Creditability Problems, it is converted into a hybrid system based on mixed integer programming Model Predictive Control rolling optimization problem.
For such a mked logical dynamic system of aircraft accident model, balance is given to (xε,uε).And it is current to set t Moment, x (t) is current state variable, is obtained by direct measurement or by state, observer is obtained.As t=0, x (t) For the original state of system, definition
Consider following Optimal Control Problem：
Wherein, Q1=Q1>0, Q2=Q2>=0, Q3=Q3>=0, Q4=Q4>0, Q5=Q5>=0,The optimal control sequence at the following k moment that expression is tried to achieve in t, and x (k | t)=x (t+k,x(t),Represent the model based on system, t in state x (t) andUnder effect, etching system shape during to t+k The prediction of state.Similar definable δ (k | t), z (k | t), y (k | t).Each inequality expresses system input, output and state Span constraint.
Above mentioned problem ultimately forms a MIQP problem.Moment t is located at, optimal control sequence is tried to achieve According to the principle of roll stablized loop, first element interaction of optimal control sequence is taken in system,
Cast out the other elements of control sequenceAt the t+1 moment, according to the status information x measured (t+1) said process, is repeated, just can roll and obtain optimal control input and state handover event is estimated, that is, flight thing Therefore the most credible estimation of middle sequence of events.
Finally, the abnormal event sequence estimated can be passed through FDR data and CVR numbers by air-accident investigation personnel The multiple-authentication of corresponding time point event compares in, confirms final most credible abnormal event sequence, searches out really Cause of accident.

Claims (5)

1. based on the most credible method of estimation of aircraft accident sequence of events for mixing PREDICTIVE CONTROL, it is characterised in that including following step Suddenly：
A, using Hybrid System Theory aircraft accident is modeled；
B, the span by setting state of flight and handover event set are determined for the secondary of Model Predictive Control Type object function；
C, asked using predictive control strategy line solver MINLP model of the hybrid system based on quadratic performance index Inscribe to obtain current optimal control sequence and state estimation；
Corresponding time point thing in D, the abnormal event sequence obtained for state estimation, comparison FDR data and CVR data Part is to confirm most credible abnormal event sequence.
2. according to claim 1 based on the most credible method of estimation of aircraft accident sequence of events for mixing PREDICTIVE CONTROL, it is special Levy and be, step A specific method is：The flight dynamics model set up using the differential equation under various states is simultaneously flown description The propositional logic of machine state space is converted to MIXED INTEGER inequality, is set up using discrete event method between various states mutually The switching model of conversion, it is considered to system primal constraints and MIXED INTEGER inequality, describes hybrid system company under same framework Continuous part and logical gate and interaction between them are to determine the MLD models of aircraft accident.
3. according to claim 2 based on the most credible method of estimation of aircraft accident sequence of events for mixing PREDICTIVE CONTROL, it is special Levy and be, the aircraft accident MLD models that step A is set up are：x(t)、u (t), δ (t), z (t) are respectively the state variable of t, input control variable, first state handover event, the switching of the second state Event, x (t+1) is the state variable at t+1 moment, A, B1、B2、B3、E1、E2、E3、E4、E5For parameter matrix.
4. according to claim 3 based on the most credible method of estimation of aircraft accident sequence of events for mixing PREDICTIVE CONTROL, it is special Levy and be, MINLP model problem is described as described in step C：
min { u 0 T - 1 } J ( u 0 T - 1 , x ( t ) ) = Σ k = 0 T - 1 | | ( u ( k ) - u e ) | | Q 1 2 + | | ( δ ( k | t ) - δ ϵ ) | | Q 2 2 + | | ( z ( k | t ) - z ϵ ) | | Q 3 2 + | | ( x ( k | t ) - x ϵ ) | | Q 4 2 + | | ( y ( k | t ) - y ϵ ) | | Q 5 2 ,
s . t . x ( T | t ) = x ϵ , x ( k + 1 | t ) = A x ( k | t ) + B 1 u ( k ) + B 2 δ ( k | t ) + B 3 z ( k | t ) , y ( k | t ) = C x ( k | t ) + D 1 u ( k ) + D 2 δ ( k | t ) + D 3 z ( k | t ) , E 2 δ ( k | t ) + E 3 z ( k | t ) ≤ E 1 u ( k ) + E 4 x ( k | t ) + E 5 , u min ≤ u ( k ) ≤ u max , k = 0 , ... , T - 1 x min ≤ x ( k | t ) ≤ u max , k = 0 , ... , T - 1 y min ≤ y ( k | t ) ≤ y max , k = 0 , ... , T - 1 ,
Wherein,For the optimal control sequence at the following T-1 moment tried to achieve in t, u (k) controls for the input at k moment Variable, ueIt is that input of the hybrid system under given poised state controls variable, δ (k | t) is for hybrid system in t and not Come the prediction that t+k moment first states handover event occurs under T-1 moment optimal control sequence effect, δεFor first state The expectation that handover event occurs, and z (k | t) make for hybrid system in t and following T-1 moment optimal control sequence With the lower prediction that t+k moment the second state handover event occurs, zεThe expectation that second state handover event occurs, x (k | T) for hybrid system in the case where t and following T-1 moment optimal control sequence are acted on to the pre- of t+k moment state variables Survey, xεFor state variable of the hybrid system under given poised state, y (k | t) is hybrid system in t and future T-1 The prediction of etching system virtual condition, y when under individual moment optimal control sequence effect to t+kεFor xεIt is that hybrid system is balanced given System virtual condition under state, Q1>0, Q2>=0, Q3>=0, Q4>0, Q5≥0。
5. according to claim 4 based on the most credible method of estimation of aircraft accident sequence of events for mixing PREDICTIVE CONTROL, it is special Levy and be, step C specific method is：First member of current time optimal control sequence is taken according to roll stablized loop principle Element acts on system solution MINLP model problem, again and again, takes in each moment optimal control sequence One element interaction rolls in system and solves optimal control sequence and the estimation of state handover event.
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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN108460509A (en) * 2017-12-20 2018-08-28 中国人民解放军海军大连舰艇学院 Fleet air defense scheduling of resource optimal control method and system under a kind of dynamic environment

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR101016611B1 (en) * 2010-12-14 2011-02-24 이화여자대학교 산학협력단 Aerial pressurizing smart-wear system for preparing against collision accident by mobile
CN102636992A (en) * 2012-04-19 2012-08-15 南京理工大学常熟研究院有限公司 Modeling based on piecewise-linear system of hybrid system theory and control method
CN102722624A (en) * 2012-06-08 2012-10-10 上海交通大学 Method for developing flying scenes for airworthiness certification and design evaluation of airplane
CN102722598A (en) * 2012-04-24 2012-10-10 南京航空航天大学 Incompatible failure safety analysis system and method for air plane motor
CN104238363A (en) * 2014-09-23 2014-12-24 江南大学 Transient state performance control method of multi-mode hybrid system

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR101016611B1 (en) * 2010-12-14 2011-02-24 이화여자대학교 산학협력단 Aerial pressurizing smart-wear system for preparing against collision accident by mobile
CN102636992A (en) * 2012-04-19 2012-08-15 南京理工大学常熟研究院有限公司 Modeling based on piecewise-linear system of hybrid system theory and control method
CN102722598A (en) * 2012-04-24 2012-10-10 南京航空航天大学 Incompatible failure safety analysis system and method for air plane motor
CN102722624A (en) * 2012-06-08 2012-10-10 上海交通大学 Method for developing flying scenes for airworthiness certification and design evaluation of airplane
CN104238363A (en) * 2014-09-23 2014-12-24 江南大学 Transient state performance control method of multi-mode hybrid system

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
张鹏: "基于混合逻辑动态的混杂系统建模及其模型预测控制", 《中国优秀硕士学位论文全文数据库 信息科技》 *
邵正: "基于飞行模拟环境的飞行事故事件序列估计方法研究", 《中国优秀硕士学位论文全文数据库 工程科技Ⅱ辑》 *

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN108460509A (en) * 2017-12-20 2018-08-28 中国人民解放军海军大连舰艇学院 Fleet air defense scheduling of resource optimal control method and system under a kind of dynamic environment

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