CN108984917A - Large aircraft flies control actuating system intelligent design and evaluation method - Google Patents
Large aircraft flies control actuating system intelligent design and evaluation method Download PDFInfo
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Abstract
Present disclose provides a kind of large aircrafts to fly control actuating system intelligent design and evaluation method comprising following steps: according to constraint condition, the configuration set for flying control actuating system is reduced by the artificial intelligence approach based on constraint satisfaction problemx；Undesirable configuration is rejected according to the security requirement of winged control actuating system；It establishes and flies control actuating system optimizing index appraisal procedure；According to the objective function that appraisal procedure constructs, multiple-objection optimization is carried out to winged control actuating system, Pareto optimization set is obtained, so that configuration set further reduces；And Analysis of Policy Making is carried out to Pareto optimization set, determine the target configuration for flying control actuating system.
Description
Technical field
This disclosure relates to which a kind of large aircraft flies control actuating system intelligent design and evaluation method.
Background technique
The highly reliable winged control actuating system of high-performance is that relationship flight safety, maneuvering performance and Control platform are mostly important
On-Board Subsystem is of great significance to the target of sustainable development of national airliner and large transport airplane.Fly control actuation system
The major function of system is to carry out the distribution of secondary energy sources power transmission to execute with actuation, and the flight of aircraft is completed by scheduled task
Control and manipulation.But up to the present, Chinese large-sized passenger plane flies control actuating system mainly by the states granddad such as PARKER, EATON
Department provides, and design wound is not illustrated at theory with key technology.Therefore, it is badly in need of independent development and meets large aircraft needs
Efficient highly reliable advanced winged control actuating system.The main problem for restricting the winged control actuating system development of China's aircraft at present is: mistake
It goes to have continued two generation machine hydraulic system technologies substantially, although three generations's machine achieves very ten-strike, rear supervention based on imitated
Exhibition lacks innovation, and basic theory and technical support are weak, lacks advanced system design philosophies and thought.
With the continuous promotion that airliner requires economy, safety, the feature of environmental protection and comfort, future aircraft will
Gradually develop to mostly electricity/complete electric direction, has system complicated so that flying control actuating system, number of components is huge, redundancy configuration group
The features such as closing explosion.It is also evolving in addition, flying control actuator, main actuator is in addition to hydraulic actuator at present
(Hydraulic Actuator, HA), there are also electric hydrostatic actuator (Electro-Hydrostatic Actuator, EHA) and
The hydraulic actuator (Electro-backup-Hydraulic Actuator, EBHA) of electricity backup.Multiple types actuator
Using the configuration for flying control actuating system and its relied on energy to entire aircraft produces tremendous influence.Such as A380 aileron,
Elevator, rudder, spoiler share 40 actuator, have HA, EHA, EBHA three types in each actuator of consideration, often
The source that a actuator can choose includes H1, H2, E1, E2, H1E1, H2E2, H1E2, H2E1 combination again, then flying in design
Machine actuating system be laid out when will face multiple shot array problem, it is possible to create layout quantity will be greater than 1040。
In addition, for large aircraft electrohydraulic dynamic actuating system from traditional hydraulic to electric hydaulic isomery and more
When electric direction changes, the variation of the configuration of new system necessarily causes the problems such as system evaluation.Result of study shows aircraft
The difference of actuation architecture, to weight, maturity, cost etc. reflection aircraft make kinety system canonical parameter have it is extremely important
Influence.Especially more power technology development, after isomery becomes selection, the complexity of system increases, and gives system index of correlation
It calculates and system evaluation brings difficulty.It carries out system evaluation and relevant parameter optimization is whether the design of check flight configuration is correct
Reasonable important measure.
The optimum configuration for flying control actuating system is to fly control actuating system on the basis of can ensure Flight Safety
The various indexs such as weight it is optimal.The method for solving this design problem at present is to be based on professional knowledge, test and trial and error, with
And iteration between different subjects, including aerodynamics, function hazard evaluation, processing quality, system architecture etc..However by
It is excessively huge in the quantity that design process is related to alternative, if it is considered that being unpractical with manual optimization.This
Earlier design phase is especially true, because frequent change needs to complete new iteration.Therefore, in order to assist fly control actuation system
System designer completes this task, needs the Automation Design to a certain degree.
Summary of the invention
In order to solve at least one above-mentioned technical problem, present disclose provides a kind of large aircrafts to fly control actuating system intelligence
Energy design and evaluation method comprising following steps: according to constraint condition, pass through the artificial intelligence based on constraint satisfaction problemx
Method reduces the configuration set for flying control actuating system；It is rejected according to the security requirement of winged control actuating system undesirable
Configuration；It establishes and flies control actuating system optimizing index appraisal procedure；According to the objective function that appraisal procedure constructs, to winged control actuation
System carries out multiple-objection optimization, Pareto optimization set is obtained, so that configuration set further reduces；And it is excellent to Pareto
Change set and carry out Analysis of Policy Making, determines the target configuration for flying control actuating system.
According at least one embodiment of the disclosure, constraint condition includes: user demand, air worthiness regulation, three axis independence
Controllable design criteria and each power source mean allocation.
In accordance with another embodiment of the present disclosure, the solution of constraint satisfaction problemx is backtracking method, and constraint is completely
The solution strategies of sufficient problem can be realized the disaggregation solution for meeting constraint.
According to the another embodiment of the disclosure, is not met and wanted according to the security requirement rejecting of winged control actuating system
The step of configuration asked includes: the function risk assessment and system-level function risk assessment of aircraft-level, determines safety
Target；Safety requirements is distributed to each subsystem using obstacle tree analysis process by Entry-level System safety evaluation；And system peace
Full assessment determines the probability of three axis failure events, and rejects the three undesirable configurations of axis failure probability.
According to the another embodiment of the disclosure, system security assessment further include: find out minimal cut using descending method
Collection, for the set of the smallest elementary event that three axis failure events occur；Non cross link is carried out to minimal cut set；And
According to the three axis failure probability of CALCULATION OF FAILURE PROBABILITY for the elementary event that Failure Mode Effective Analysis obtains.
According to the another embodiment of the disclosure, optimizing index includes weight, energy consumption, cost.
According to the another embodiment of the disclosure, the appraisal procedure of weight includes: for internal structure complexity, still
There is the component of mature series of products, the method for concluding estimation by data statistics and the principle of similitude obtains the growth rule of weight
Rule, using the weight of current version as with reference to acquisition weight；And it is less for part, and formed design specification
Component, using the computation method for hot based on design constraint in conjunction with empirical equation.
According to the another embodiment of the disclosure, multiple-objection optimization uses discrete multi-objective particle swarm optimization method.
According to the another embodiment of the disclosure, Analysis of Policy Making uses analytic hierarchy process (AHP).
According to the another embodiment of the disclosure, the target zone of analytic hierarchy process (AHP) is the target structure for flying control actuating system
Type, rule layer are weight, energy consumption, Cost Evaluation index, and solution layer is the configuration scheme in Pareto optimization set.
Detailed description of the invention
Attached drawing shows the illustrative embodiments of the disclosure, and it is bright together for explaining the principles of this disclosure,
Which includes these attached drawings to provide further understanding of the disclosure, and attached drawing is included in the description and constitutes
A part of this specification.
Fig. 1 is the winged control actuating system intelligent design of large aircraft and evaluation according at least one embodiment of the disclosure
The flow chart of method.
Fig. 2 is the winged control actuating system safety Design process of large aircraft according at least one embodiment of the disclosure
Figure.
Fig. 3 is the discrete multi-objective particle swarm algorithm flow chart according at least one embodiment of the disclosure.
Fig. 4 is the actuating system optimization structure chart based on analytic hierarchy process (AHP) according at least one embodiment of the disclosure.
Fig. 5 is the winged control actuating system decision based on analytic hierarchy process (AHP) point according at least one embodiment of the disclosure
Analysis method process.
Specific embodiment
The disclosure is described in further detail with embodiment with reference to the accompanying drawing.It is understood that this place
The specific embodiment of description is only used for explaining related content, rather than the restriction to the disclosure.It also should be noted that
For ease of description, part relevant to the disclosure is illustrated only in attached drawing.
It should be noted that in the absence of conflict, the feature in embodiment and embodiment in the disclosure can
To be combined with each other.The disclosure is described in detail below with reference to the accompanying drawings and in conjunction with embodiment.
The highly reliable winged control actuating system of high-performance is that relationship flight safety, maneuvering performance and Control platform are mostly important
On-Board Subsystem, however Chinese large-sized aircraft technology ground zero at present fly control actuating system design shortage system wound into theoretical base
Plinth.Therefore the design method for flying to control actuating system is studied to have a very important significance.The disclosure flies control for design aircraft and makees
Two hang-ups are assessed in the multiple shot array and various dimensions that dynamic system layout faces, and propose a kind of large aircraft based on artificial intelligence
Fly the design of control actuating system and evaluation method, design and provide fundamental basis for actuating system, as shown in Figure 1 comprising following step
It is rapid:
S1: it according to constraint condition, is reduced by the artificial intelligence approach based on constraint satisfaction problemx and flies control actuating system
Configuration set；
S2: undesirable configuration is rejected according to the security requirement of winged control actuating system；
S3: it establishes and flies control actuating system optimizing index appraisal procedure；
S4: the objective function constructed according to appraisal procedure carries out multiple-objection optimization to winged control actuating system, it is tired to obtain pa
Optimization set is held in the palm, so that configuration set further reduces；
S5: Analysis of Policy Making is carried out to Pareto optimization set, determines the target configuration for flying control actuating system.
With reference to the accompanying drawing, the specific embodiment of each step is described in detail.
Step S1: it according to constraint condition, is reduced by the artificial intelligence approach based on constraint satisfaction problemx and flies control actuation system
The configuration set of system.
The quantity summation that the redundancy master of large aircraft flies control actuator configuration combination can reach 1040If to all structures
Type is all analyzed and evaluated, and the time of consumption will be unacceptable, so the quasi- searching method by artificial intelligence, that is, pass through
The design combination for being unsatisfactory for requiring is rejected in the constraint to be abided by of design.In accordance with another embodiment of the present disclosure, it constrains
Set is other than comprising user demand, it is also contemplated that air worthiness regulation, the individually controllable design criteria of three axis, each power source are uniform
Distribution etc..The constraint set can be divided into strong constraint and weak constraint.Strong constraint is that good, such as left and right sides is integrated in program
The layout of spoiler be it is identical, i.e., bilateral symmetry.Weak constraint is can be according to constraint list of the user demand on interface
The middle constraint chosen, for example, on aileron actuator layout whether include all power sources.
After setting constraint set, artificial intelligence approach can be applied, that is, is used for reference constraint satisfaction problemx (CSP)
The configuration for not meeting constraint is deleted, is substantially reduced configuration set by description and method for solving.However, traditional constraint satisfaction is asked
The algorithm of topic is merely able to find the solution for meeting design constraint.According to disclosure another embodiment, asked for this
Topic, the disclosure have studied follow-on constraint satisfaction problemx solution strategies, propose and make suitable for large aircraft electrohydraulic dynamic
The security constraint intelligence configuration inference method of dynamic system design, the disaggregation that this method may be implemented to meet constraint solve.
Binding character can meet problem, and there are many solutions, and according to the another embodiment of the disclosure, the disclosure is used
Method be backtracking method, basic ideas are every time any selection one variables and its arbitrary value, carry out variable assignments and continue to solve
Certainly problem.Meanwhile whether demand binding character problem checks assignment that is, between the constraint relationship all variables that assignment is completed
Meet constraint condition.If not being able to satisfy the constraint condition under assignment condition, other assignment are selected to be attempted, such as nothing
Method obtains the value for meeting existing assignment condition, then is recalled, replace with the assignment of a variable.If meeting condition, continue to taste
Try the codomain selection of next variable.And so on, the assignment of all variables in problem can be met until completing entire binding character,
And meeting all restrictive conditions, this binding character, which can be obtained, can meet the solution of problem.
By the artificial intelligence search based on constraint satisfaction problemx, configuration quantity be can be greatly reduced, for example,
A380 aileron is all to be configured as 4^6=4096 kind, and constraint satisfaction problemx is only 16 kinds remaining after solving.In addition, by based on about
After the artificial intelligence approach that beam meets problem solves, the layout scenarios of A380 can be by configuration quantity from 1040It is down to 108。
Step S2: undesirable configuration is rejected according to the security requirement of winged control actuating system.
Higher and higher to large aircraft security requirement now, the function of flying airborne equipment and the system integration is more and more,
System architecture becomes increasingly complex, and can aircraft continue safe flight as urgent need consideration after analysis system leads to the problem of failure.
Electrohydraulic dynamic actuating system is as one of civil aircraft critical system, and whether system function is complete reliable, and whether system performance is steady
It is fixed, it is directly related to the safety of entire aircraft flight, is the object of aiMonhiness authority's high spot reviews.Therefore, electrohydraulic dynamic is made
Dynamic system, which carries out safety analysis, just becomes one ring of key of civil aircraft safety Design.
According to the another embodiment of the disclosure, the step further include: the function risk assessment (FHA) of aircraft-level
With system-level function risk assessment, security objectives are determined；Entry-level System safety evaluation (PSSA), using obstacle tree
Safety requirements is distributed to each subsystem by analytic approach；And system security assessment (SSA), determine the probability of three axis failure events,
And reject the three undesirable configurations of axis failure probability.
Fig. 2 is the winged control actuating system safety evaluation process that the disclosure uses comprising the determination part of safety requirements
(left branch of " V " shape shape) and verification portion (right branch of " V " shape shape) for supporting research & development in flight.At the beginning of research & development in flight,
It just needs to carry out the function risk assessment an of aircraft-level, system-level function harm then is carried out to each subsystem again
Property assessment.The purpose of function risk assessment (FHA) is that identification aircraft and system function and its function combine relevant failure
State determines the influence grade of each failure state and carries out the prime reason of grade separation, and establishes phase according to grade is influenced
The security objectives answered.For example, the target call any influence safe flight of aircraft safety design and the failure of safe landing are lost
Efficiency should all be no more than 10-9/ Fh (pilot time).Function HAZAN (FHA) is carried out to winged control actuating system, it is determined that
Then all disabler failures that system may occur endanger influence degree by failure of removal and carry out to these failure of removal
Classification.The disclosure carries out system-level function HAZAN to main flight control system mainly for three axis control functions of aircraft,
Determine which failure state rolling control function, pitch control function, yaw control function have respectively.
According to function risk assessment (FHA), its various failure state and shadow are determined for three axis control function of aircraft
Ring grade.Then Entry-level System safety evaluation (PSSA) is carried out, constructs failure by top layer event of these failure states respectively
It sets (fault tree analysis, FTA), further analyzes which unit failure in main flight control system will lead to top layer mistake
Effect state occurs, to be required to determine all parts failure state one by one according to the quantitative probabilities to top layer failure state
Maximum allowable probability.Entry-level System safety evaluation (PSSA) is the process to iterate in entire design activity, if
Meter change will lead to the system requirements obtained and change (and variation of fault tree)；Conversely, passing through Entry-level System safety
The potential safety problem of assessment discovery also results in change in design.After the modification that iterates, the design side of aircraft is obtained
Case.
Then, into test phase, respectively by component-level test, system level testing and final aircraft-level test.?
Component-level test phase is mainly verified by failure tree analysis (FTA) and Failure Mode Effective Analysis.In system security assessment
(SSA) stage calculates the failure probability of each failure event by non cross link method, and undesirable configuration will be removed.
According to the another embodiment of the disclosure, system security assessment is further comprising the steps of: finding out minimal cut using descending method
Collection, for the set of the smallest elementary event that three axis failure events occur；Non cross link is carried out to minimal cut set；And
According to the three axis failure probability of CALCULATION OF FAILURE PROBABILITY for the elementary event that Failure Mode Effective Analysis obtains.
System security assessment (SSA) is a kind of analysis method from bottom to top.System security assessment is with Entry-level System safety
Property assessment failure tree analysis (FTA) based on, since bottom failure event, with Failure Mode Effective Analysis (Failure
Mode and Effects Analysis, FMEA) failure probability of bottom event that provides is according to top layer failure state
Failure probability carries out quantitative analysis.
In order to carry out the analysis of qualitative, quantitative to fault tree, minimal cut set is first found out using descending method, that is, the smallest
So that the set for the elementary event that top event occurs.Non cross link is carried out to minimal cut set later, finally obtains failure probability.
Step S3: it establishes and flies control actuating system optimizing index appraisal procedure.
In order to realize the comparison of aircraft configuration, need to evaluate and optimize the performance of configuration.
According to the another embodiment of the disclosure, optimizing index mainly include fly the control weight of actuating system, energy consumption,
Cost.It is weight assessment that wherein difficulty is biggish.
The method for defining weight assessment is, in the case where certain design needs, for different configurations, obtains power actuation
The weight of all parts of system, and the total weight of the weight to other systems generation.
Weight is to influence the important evaluation index and determinant of large aircraft power and actuating system configuration.Large size flies
Mechanomotive force and the difficult point of actuating system weight assessment include that its component is various；The weight of component estimates that difficulty, many and design need
Non-linear growth of hoping for success relationship；Serious with the coupling of other systems, the variation of system can have an impact the weight of other systems.
For this purpose, being directed to all relevant components, different weight assessment algorithms is had studied, specific weight computational algorithm is very big.This
Partial algorithm has passed through the inspection of part finished product, and Numerical value error can be applied to initial stage between 10%-20%
Design phase.
According to the another embodiment of the disclosure, the characteristics of for power and actuating system component, two kinds of weight are proposed
The method of assessment: it is complicated for this kind of internal structure of hydraulic pump, but have the component of mature series of products, pass through data statistics
The method for concluding estimation with the principle of similitude, obtains the increasing law of weight, is weighed using the weight of current version as reference
Amount；And it is less for the parts such as fluid pressure line, hydraulic cylinder, and the component of design specification is formed, using based on setting
Computation method for hot of the meter constraint in conjunction with empirical equation.
Corresponding algorithm is also all developed for energy consumption and cost to be assessed.
Step S4: the objective function constructed according to the appraisal procedure carries out multiple-objection optimization to winged control actuating system,
Pareto optimization set is obtained, so that the configuration set further reduces.
The extensive intelligent optimization that building optimizes for seaworthiness safety, power to weight ratio, the multidisciplinary of energy consumption, multiple target configuration
Method, distributed for research, dissimilar redundancy electrohydraulic dynamic actuating system new system design theory have important guidance
Meaning.So-called configuration optimization is on the basis of meeting the constraint conditions such as seaworthiness safety, flight quality, and optimization energy source drives
The actuator combination of dynamic control surface is allowed to meet the requirement such as safety, economy, comfort.
The disclosure greatly reduces the order of magnitude of configuration by artificial intelligence approach, is searching out inside the combination come, is having
Although a large amount of combination also meets primary demand, from performance perspective be consider be it is unexcellent, need to assess to configuration
On the basis of, configuration is further searched for by Multipurpose Optimal Method.On the one hand because electrohydraulic dynamic actuating system is deposited
In multiple evaluation indexes, and there are contradiction between each index, and unit also disunity；Another aspect combination evaluation problem be from
Dissipate optimization.Considered based on the above two o'clock, according to the another embodiment of the disclosure, selects discrete multi-objective particle swarm optimization
Method (DMOPSO) further searches for configuration, obtains Pareto (Pareto) optimization set, realizes configuration quantity
Further degrade.
Particle swarm optimization algorithm imagination has flock of birds specified place of search of food and uncertain food in some region,
But know how far of the every bird from food.In order to find food as early as possible, every bird tends to live through at oneself from food
The nearest position of object is nearby found, and close to that nearest apart from food at present bird, so utilizes experience and group
Experience finds food.If flock of birds foraging behavior, which is abstracted into algorithm, carrys out solving optimization problem, the region scanned for
Be exactly the value range of optimization problem, the bird in flock of birds is abstracted into particle, without volume and quality, but have position x,
Speed v and adaptive value f (x).Up to the present optimum position that first particle is searched for is Pbest, entire population searches
Optimal location be Gbest.Particle can carry out speed and position according to following more new formula in t moment algorithm operational process
It updates:
Vi(t+1)=Vi(t)+c1*r1*(Pbest-Xi(t))+c2*r2*(Gbest-Xi(t))
Xi(t+1)=Xi(t)+Vi(t+1)
Wherein c1And c2Referred to as Studying factors, r1And r2It is random number, value range is between 0 to 1.From above-mentioned update
Formula, which can be seen that, to be come, and the speed of each particle updates item and contains the velocity component of three aspects.
First part is known as inertia portion, describes the velocity magnitude at particle current time for the subsequent time particle
The influence of speed；Second part is known as itself study part, describes the influence that particle is remembered by itself, is particle
To the summary at passing all moment, find last time particle to be reached the personal best particle point nearest from target.
Accordingly it is also possible to c1It is defined as " autognosis part ".Part III is known as team learning part, describes and comprehensively considers
The experience of entire population is remembered in iterative process before group's particle, has reflected society's cooperation memory between entire group,
The information sharing effect between each particle is embodied, by comparison, finds the desired positions that entire group's particle reached.
Accordingly it is also possible to c2It is defined as " group cognition part ".
Adaptive value f (x) represents target function value.The disclosure as described above chooses weight fW(x), energy consumption fP(x), cost
fCIt (x) is objective function.It is mutually restricted between each target by decision variable, it must be with it to the optimization of one of target
His target is cost, while the unit of each target is also inconsistent, therefore, it is difficult to objectively evaluate the superiority-inferiority of multiple target solution.It is more
The solution of objective optimisation problems is not unique, and there are an optimal solution set, it is optimal to be known as Pareto for element in set
Solution.Each solution corresponds to an object vector in multi-objective optimization question, and so-called Pareto optimal solution is exactly to be not present in this way
Solution so that its corresponding object vector be less than the corresponding object vector of Pareto optimal solution.Member in Pareto optimal solution set
Element is incomparable each other for all targets.
Aircraft Steering Engine multiple target minimization problem can be described as:
In formulaFor area of feasible solution, E=f (x) | x ∈ RnIt is target solution vector space.
As shown in figure 4, the actuating system configuration discrete optimization process based on discrete multi-objective particle swarm optimization method can retouch
It states as follows:
(1) population is initialized, the maximum number of iterations that discrete multi-objective particle swarm optimization method is arranged is 100, setting
Population is 600, and the capacity in setting Pareto disaggregation library is 300；
(2) speed and initial position (parameter value to be optimized) for initializing particle, bring particle rapidity, position into building
Objective function, i.e. weight fW(x), energy consumption fP(x), cost fC(x) in, the fitness function value of each particle is acquired；
(3) individual extreme value is initialized；
(4) it according to Pareto dominance relation, selects non-dominant particle, puts it into non-dominant concentration, i.e., it is external to concentrate；
(5) it is concentrated from outside and chooses global optimum；
(6) according to improved multi-objective particle swarm algorithm more new formula, processing is updated to particle rapidity and position；
(7) speed after update and position are brought into objective function, fitness value after update is obtained, according to Pareto branch
It with relationship, is compared with the particle for being stored in non-dominant collection, is stored in non-dominant value, deleted by predominant value；
(8) non-dominant concentration particle is stored in external set, if the population of deposit is greater than the maximum of external set
Number is stored, using crowding distance method, extra relatively inferior solution is deleted, retains more excellent solution；
(9) particle is concentrated to carry out descending processing outside；
(10) judge whether to have reached the number of iterations, step (5) are rotated back into if not, continue to update iteration；If reaching
Maximum number of iterations, then export it is external concentrate particle, as the Noninferior Solution Set of objective function.
Step S5: Analysis of Policy Making is carried out to Pareto optimization set, determines the target configuration for flying control actuating system.
When optimum results there are multiple feasible solutions, how in these feasible target solutions, a best optimization knot is found
Fruit is the critical issue for further increasing electrohydraulic dynamic actuating system configuration optimization design.After obtaining Pareto optimization set,
It needs to carry out comprehensive assessment to the configuration in set, thus selection target configuration.Multi-objective decision algorithm is integrated in software,
The weight for each target that can be provided according to expert is realized the comprehensive assessment to scheme, is ranked up to all configurations, supports
The selection of configuration.
According to the another embodiment of the disclosure, Analysis of Policy Making uses analytic hierarchy process (AHP).
Analytic hierarchy process (AHP) (Analytic Hierarchy Process, AHP) leads to complicated decision system stratification
The importance of layer-by-layer more a variety of relation factors is crossed, provides quantitative foundation for analysis, decision.This method basic principle is root
According to the property and general objective to be achieved of problem, it is broken down into different compositing factors, according to the membership between factor
With influence each other, by a multi-level simulation tool structural model being formed after different levels aggregation combination, utilize the experience pair of people
Decision scheme superiority and inferiority is ranked up, and determines the relatively important weighted value of each layer of whole factors, and then propose optimal case.
According to the another embodiment of the disclosure, as shown in figure 5, actuating system target will be obtained in analytic hierarchy process (AHP)
The target of configuration is set as target zone, using evaluation indexes such as weight, energy consumption, costs as rule layer, by Pareto optimization collection
Each configuration scheme in conjunction is as solution layer.Finally by analytic hierarchy process (AHP) calculating and the judgement of integrated decision-making person, really with this
It is set for dynamic aims of systems configuration.
Electrohydraulic dynamic actuating system Analysis of Policy Making process based on analytic hierarchy process (AHP) is as shown in Figure 5.Firstly, establishing electro-hydraulic
Power actuating system optimizes AHP Model；The judgment matrix A compared two-by-two is constructed, whether test and judge matrix is one
Cause property matrix, if it is not, then adjustment judgment matrix A, and judgement is re-started, until judgment matrix A is judged as consistency square
Battle array；Finally calculate weight w.In conjunction with present example, the detailed step for calculating weight w is as follows:
1) Judgement Matricies.
Judgment matrix A is determined according to the relationship between each index of rule layer
In formula, aijFor the opposite significance level with target of index i and index j, value range is 1~9, the bigger table of numerical value
Show that relative importance is higher.Different degree scale meaning table is as shown in table 1.
1 importance scale meaning table of table
By the significance level of 3 factors more than statisticalling analyze, judgment matrix is established according to table 1:
2) consistency check of judgment matrix.
The calculation method of coincident indicator CI is as follows:
In formula, CI is the coincident indicator of judgment matrix；RI is the Aver-age Random Consistency Index of judgment matrix, tool
Body value is referring to table 2；CR is the random consistency ratio of judgment matrix；λmaxFor characteristic root of a matrix maximum value；N is judgment matrix
Order.
The value of 2 Aver-age Random Consistency Index RI of table
By can be calculated, λmax=3.08,Therefore, should
Judgment matrix has satisfied consistency.If being unsatisfactory for consistency check, return step 1), reconfigure judgment matrix.
3) it is calculated by comparison element by judgment matrix for the relative weighting of the criterion.
The continued product of the every row element of judgment matrix A is calculated,I=1,2 ..., n, then
Seek MiN times root,I=1,2 ..., n, by can be calculated
Parameter
It willBy formulaIt is normalized, obtained normalized vector W is the weight of each factor
Coefficient, then
W=[0.066 0.149 0.785]T
It will be understood by those of skill in the art that above embodiment is used for the purpose of clearly demonstrating the disclosure, and simultaneously
Non- be defined to the scope of the present disclosure.For those skilled in the art, may be used also on the basis of disclosed above
To make other variations or modification, and these variations or modification are still in the scope of the present disclosure.
Claims (10)
1. a kind of large aircraft flies control actuating system intelligent design and evaluation method, which is characterized in that the large aircraft flies control
Actuating system intelligent design includes: with evaluation method
According to constraint condition, the configuration collection for flying control actuating system is reduced by the artificial intelligence approach based on constraint satisfaction problemx
It closes；
Undesirable configuration is rejected according to the security requirement of the winged control actuating system；
Establish the winged control actuating system optimizing index appraisal procedure；
According to the objective function that the appraisal procedure constructs, multiple-objection optimization is carried out to the winged control actuating system, it is tired to obtain pa
Optimization set is held in the palm, so that the configuration set further reduces；And
Analysis of Policy Making is carried out to the Pareto optimization set, determines the target configuration of the winged control actuating system.
2. large aircraft according to claim 1 flies control actuating system intelligent design and evaluation method, which is characterized in that institute
Stating constraint condition includes: user demand, air worthiness regulation, the individually controllable design criteria of three axis and each power source mean allocation.
3. large aircraft according to claim 1 flies control actuating system intelligent design and evaluation method, which is characterized in that institute
It states the solution of constraint satisfaction problemx and can be realized satisfaction about for the solution strategies of backtracking method and the constraint satisfaction problemx
The disaggregation of beam solves.
4. large aircraft according to claim 1 flies control actuating system intelligent design and evaluation method, which is characterized in that institute
Stating the step of rejecting undesirable configuration according to the security requirement of the winged control actuating system includes:
The function risk assessment of aircraft-level and system-level function risk assessment, determine security objectives；
Safety requirements is distributed to each subsystem using obstacle tree analysis process by Entry-level System safety evaluation；And
System security assessment determines the probability of three axis failure events, and rejects the three undesirable configurations of axis failure probability.
5. large aircraft according to claim 4 flies control actuating system intelligent design and evaluation method, which is characterized in that institute
State system security assessment further include:
Minimal cut set is found out using descending method, the minimal cut set makes the basic of the three axis failure event generation to be the smallest
The set of event；
Non cross link is carried out to the minimal cut set；And
According to three axis failure probabilities described in the CALCULATION OF FAILURE PROBABILITY of the elementary event of Failure Mode Effective Analysis acquisition.
6. large aircraft according to claim 1 flies control actuating system intelligent design and evaluation method, which is characterized in that institute
Stating optimizing index includes weight, energy consumption, cost.
7. large aircraft according to claim 6 flies control actuating system intelligent design and evaluation method, which is characterized in that institute
The appraisal procedure for stating weight includes:
For internal structure complexity, but there is the component of mature series of products, is concluded and estimated by data statistics and the principle of similitude
Method, obtain the increasing law of weight, using the weight of current version as with reference to obtain weight；And
It is less for part, and formed the component of design specification, using based on design constraint in conjunction with empirical equation
Computation method for hot.
8. large aircraft according to claim 1 flies control actuating system intelligent design and evaluation method, which is characterized in that institute
Multiple-objection optimization is stated using discrete multi-objective particle swarm optimization method.
9. large aircraft according to claim 1 flies control actuating system intelligent design and evaluation method, which is characterized in that institute
The Analysis of Policy Making is stated using analytic hierarchy process (AHP).
10. large aircraft according to claim 9 flies control actuating system intelligent design and evaluation method, which is characterized in that
The target zone of the analytic hierarchy process (AHP) is the target configuration of the winged control actuating system, and rule layer is weight, energy consumption, Cost Evaluation
Index, solution layer are the configuration scheme in the Pareto optimization set.
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