CN107480335A - A kind of hypersonic vehicle Iterative Design method - Google Patents
A kind of hypersonic vehicle Iterative Design method Download PDFInfo
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Abstract
The invention discloses a kind of hypersonic vehicle Iterative Design method, comprise the following steps：Hypersonic aircraft parameterized model is built by geometric design method；The crucial model parameter of hypersonic aircraft is extracted by sensitivity method, reduced parameter model, obtains hypersonic aircraft towards the agent model of Iterative Design；The model parameter of hypersonic aircraft is optimized using dove colony optimization algorithm, obtains the poised state of different flying condition drags；The desired performance indications of hypersonic aircraft are determined, the poised state of model is iterated, obtain that aircraft is optimal designs a model.The present invention is under the flying condition of complexity, according to expected performance index, optimal model parameter is obtained using dove colony optimization algorithm, it is quickly obtained the optimal model parameters for meeting expected performance index, and it can cover to all flight envelopes, the model optimization instrument provided for hypersonic aircraft design.
Description
Technical field
The present invention relates to vehicle technology field, especially a kind of hypersonic vehicle Iterative Design method.
Background technology
Hypersonic aircraft has great military and civilian valency because of the flight characteristics of its big Mach number and High aititude
Value.The multi-disciplinary cutting edge technology of the hypersonic flight system integration, between subject interaction it is complicated, it is necessary to by comprehensive Design come
Obtain optimal dummy vehicle.
But traditional hypersonic aircraft modeling process is often based upon wind-tunnel and test data, workload is huge and takes
With costliness；In addition, time-consuming for data acquisition, be unfavorable for the Optimized Iterative design of model, and control action be difficult and other
Population parameter is merged.The present invention proposes a kind of hypersonic vehicle Iterative Design method, using parametrization
Modeling method builds hypersonic aircraft towards the model of Iterative Design, and the optimization to model is realized using dove colony optimization algorithm
Iterative Design, to meet desired performance indications requirement.
The content of the invention
The technical problems to be solved by the invention are, there is provided a kind of hypersonic vehicle Iterative Design method,
The restriction relation between different flying condition drag parameters and expected performance index is built, by Iterative Design, is realized to mould
The optimization of shape parameter, obtains that hypersonic aircraft is optimal designs a model.
In order to solve the above technical problems, the present invention provides a kind of hypersonic vehicle Iterative Design method, including
Following steps：
(1) hypersonic aircraft parameterized model is built by geometric design method；
(2) the crucial model parameter of hypersonic aircraft is extracted by sensitivity method, reduced parameter model, obtained
Agent model of the hypersonic aircraft towards Iterative Design；
(3) model parameter of hypersonic aircraft is optimized using dove colony optimization algorithm, obtains different flight bars
The poised state of part drag；
(4) the desired performance indications of hypersonic aircraft are determined, the poised state of model is iterated, flown
Device is optimal to design a model.
Preferably, in step (1), building hypersonic aircraft parameterized model by method of geometry is specially：First
Hypersonic aircraft basis configuration is disassembled into strategy using part and is decomposed into forebody, stage casing, rear body, wing, control
The parts such as face, it is then determined that to describe the geometric parameter of various pieces resemblance, and determine these parameters whether completely solely
It is vertical, existing constraint between parameter, obtain that the complete geometric parameters manifold of unmanned plane can be described, and then the value of parameter set is specified,
Specific unmanned plane profile is generated, to examine the geometric parameters manifold being previously obtained to describe unmanned plane profile.Finally by high ultrasound
The geometric shape of fast aircraft parameters carries out binning, using the power needed for engineering estimating method estimation modeling, constructs
Hypersonic aircraft parameterized model.
Preferably, in step (2), hypersonic aircraft agent model, the high ultrasound of extraction are obtained by sensitivity method
The crucial model parameter of fast aircraft specifically includes following steps：
(21) sampling of hypersonic aircraft parameterized model data；If with SiRepresent the value of design variable i-th dimension
Set, n (Si) represent set in contained element number, then sample range be defined as：
According to definition it is recognised that sampling range represents that any one-dimensional number of samples will not be less than C in design space,
C is bigger, then it represents that the coverage rate of sampling is wider, and C is up to the capacity of sample space；
The uniformity for being directed to experimental design proposes sample minimum range and the concept of sample potential, determines according to 2 norms
The distance D of i point and j point in adopted sample spaceij, then sample minimum range be defined as：
The same number for defining minimum range and occurring, is designated as n (D), from the perspective of the criterion, it is believed that minimum range is got over
Greatly, then experimental design is better；In the case of minimum range identical, the number that minimum range occurs is fewer, then experimental design is better；
, can be by calculating the potential in sample space or being sample potential energy if being introduced into the concept of potential in physics：
Wherein N represents the capacity of sample space, from the perspective of the criterion, it is believed that the repulsion of whole system is smaller, real
Test design it is better, two kinds of optiaml ciriterions have certain uniformity；
(22) structure of hypersonic aircraft aerodynamic force and thrust agent model, using Morse's Sensitivity Analysis Method come
Select suitable hypersonic aircraft agent model；Morse's Sensitivity Analysis Method is used based on a fractional analysis (OAT)
Random searching strategy；If the input parameter of system is x ∈ Rn, in order to eliminate the influence of each parameter dimension, each parameter is returned
One, which changes processing, causes each element x in xiIt is satisfied by xi∈ [0,1], i=1 ..., n；
The output of system is defined as y=f (x) ∈ Rm.Then i-th of input factor xiBasic effect be defined as：
Wherein eiIt is 1 for i-th of element, other elements are 0 n-dimensional vector；Δ is step-length；X is the random of parameter space
Sampling, and ensure x+ Δs eiStill in parameter space；If in R sample point of parameter space stochastical sampling, by each samples of R
Point is once analyzed, meter sensitivity, is being carried out the statistical properties analysis to each sensitivity of this R, is being calculated its average and standard
Difference：
If sensitivity mean μiSignificantly different from 0, then i-th of element has global impact for output y；Sensitiveness standard
Poor σiI-th of element of bigger expression has significant nonlinear characteristic, including the interaction work between high-order term and parameter for output
With；When analyzing different objects, due to the influence of output response dimension, its corresponding line of demarcation is different, or, can be with
Output is responded and carries out nondimensionalization, and then can be to different analysis objects, using identical criteria for classification；According to Morse
Analytic approach, the basic effect of i-th of input factor can approximately be considered as system accordingly for i-th of input in given sampled point
The partial derivative at place, μiWith σiFrom statistical angle, qualitatively analyzing influence degree；
(23) checking of hypersonic aircraft aerodynamic force and thrust agent model, after obtaining agent model, using variance
The agent model established is verified than evaluation indexes such as, mean square deviation error, the goodness of fit and maximum residuals.
Preferably, in step (3), tool is optimized to the model parameter of hypersonic aircraft using dove colony optimization algorithm
Body comprises the following steps：
(31) fitness function is built；
(32) species information and algorithm parameter initialization, including population quantity, optimized variable dimension, operation operator parameter with
And the iterations N of two operation operatorsc1maxAnd Nc2max；Individual speed and positional information initialization, it is right according to fitness quality
Local and global optimum's information initializing；
(33) map compass operator is run, earth magnetism and altitude of the sun information, and kind are passed through according to each individual in dove group
Optimal information in group, updates position and the speed of each pigeon, compares to obtain optimal path；
(34) if iterations NcMore than Nc1max, iteration is switched to terrestrial reference operator from map compass operator；Otherwise, return
(33) step；
(35) every pigeon is sorted according to adaptive value, retains the high pigeon of adaptive value；By the use of population central point as surplus
The reference flight direction of remaining dove group, the position of individual is updated, calculates dove group center and adjust the position of each pigeon, make
It flies to dove group center；
(36) if iterations NcMore than Nc2max, iteration ends and output result；Otherwise, (35) step is returned.
Preferably, the poised state for obtaining different flying condition drags is specially：For flat under various boundary conditions
Weighing apparatus state Solve problems, establish and value function are adapted to corresponding to it, and its concrete form is as follows：
In formula, tfTo emulate end time, η is as Dynamic Weights, for weakening the unstable Effect of Mode of time integral；
βi, i=1,2..., 5 be weights so that each state derivative index is equably intended to optimal index；Optimized using dove colony intelligence
The Fast Convergent ability of algorithm and its weak dependence to initial value precision, direct searching optimization make adaptive value function convergence to extreme value,
Find optimal solution, as hypersonic aircraft poised state.
Preferably, in step (4), determine that the desired performance indications of hypersonic aircraft, the poised state to model are entered
Row iteration, obtain that aircraft is optimal designs a model specially：It is optimal that hypersonic aircraft is obtained using dove colony optimization algorithm
Design a model, it is to find the optimal cruising condition of flight to obtain optimal models, because the selection of optimal cruising condition is with flying
The poised state of row device is relevant, therefore, construction 2-level optimization's strategy optimizes to optimal cruising condition, Optimizing Flow is：It is first
First set algorithm hunting zone, algorithm parameter and optimization initial value；In first order optimization, solved using dove colony optimization algorithm different
Poised state amount and controlled quentity controlled variable under state of flight, on this basis, again by dove colony optimization algorithm to optimal state of flight
Optimize；According to the adaptive value of each individual in cost function calculation population, again return in algorithm and carry out state of flight more
Newly；When simulation times reach maximum, stop calculating, output result；Once find the optimal cruise shape of hypersonic aircraft
State, you can to obtain the aerodynamic force and thrust under optimum state, and then derive that optimal hypersonic aircraft designs a model.
Beneficial effects of the present invention are：The present invention is advantageous to the optimization design problem of hypersonic vehicle parameter,
Under the flying condition of complexity, according to expected performance index, optimal model parameter is obtained using dove colony optimization algorithm, rapidly
The optimal model parameters of expected performance index are met, and can be covered to all flight envelopes, are set for hypersonic aircraft
Count the model optimization instrument provided.
Brief description of the drawings
Fig. 1 is the method implementation process schematic diagram of the present invention.
Fig. 2 is the schematic flow sheet of the hypersonic aircraft geometric shape parametrization of the present invention.
Fig. 3 is the hypersonic aircraft agent model structure schematic flow sheet of the present invention.
The Morris analytic approach influence factors that Fig. 4 is the present invention determine area schematic.
Fig. 5 is the iterative process schematic diagram of the dove colony optimization algorithm of the present invention.
Fig. 6 is the hypersonic aircraft poised state optimization design schematic flow sheet of the present invention.
Fig. 7 is the hypersonic aircraft optimal models design cycle schematic diagram of the present invention.
Embodiment
As shown in figure 1, a kind of hypersonic vehicle Iterative Design method, comprises the following steps：
(1) hypersonic aircraft parameterized model is built by geometric design method；
(2) the crucial model parameter of hypersonic aircraft is extracted by sensitivity method, reduced parameter model, obtained
Agent model of the hypersonic aircraft towards Iterative Design；
(3) model parameter of hypersonic aircraft is optimized using dove colony optimization algorithm, obtains different flight bars
The poised state of part drag；
(4) the desired performance indications of hypersonic aircraft are determined, the poised state of model is iterated, flown
Device is optimal to design a model.
Pin of the present invention is in the characteristic of the multidisciplinary coupling of hypersonic aircraft, it is proposed that a kind of new model Iterative Design side
Method, will be pneumatic by building the geometrical model of parametrization, promote, and the coupling such as control associates, using point of sensitivity
Analysis strategy obtains key model parameter, derives hypersonic aircraft agent model, and then coordinate using dove colony optimization algorithm
Relation between performance indications and model parameter, obtains that hypersonic aircraft is optimal to design a model.
Hypersonic aircraft geometric shape parametrization is the basis of parametric modeling, the only profile when parameter set description
It is close enough with the exact shape of aircraft, practical flight device profile could be replaced to carry out aerodynamic prediction and move with parametrization profile
Mechanical Characteristic analysis.Determined according to sShape features and modeling requirement to describe the geometric parameter of its resemblance, and determine this
Whether a little parameters are completely independent, and establish existing restriction relation between parameter, obtain that the complete geometric parameter of aircraft can be described
Collection, the value of parameter set is then specified, generate given aircraft profile, to examine the geometric parameters manifold being previously obtained to describe
Aircraft profile, specific implementation process are as shown in Figure 2.
The structure of hypersonic aircraft agent model, specific implementation process are as shown in Figure 3.Firstly the need of to hypersonic
The geometric shape of aircraft parameters carries out binning, estimates aerodynamic force and thrust using engineering estimating method, establishes data
Storehouse.The bin data that hypersonic aircraft calculation of aerodynamic characteristics module is obtained by aircraft geometric parameter model, foundation
Flying condition and the pressure and stressing conditions of current flow field lower surface, update bin data.Propulsion system performance calculating module master
It is made up of two parts：Fuselage/propulsion system coupling module (air intake duct module) and scramjet engine module.It is hypersonic
The foundation of flight vehicle aerodynamic power and thrust agent model is to be based on calculation of aerodynamic characteristics module and propulsion system performance calculating module
Obtained database, and then feasible agent model is derived, concrete implementation step includes：
Step1：The sampling of hypersonic vehicle data.The coverage rate for being directed to experimental design proposes sampling range
Concept.If with SiRepresent the value set of design variable i-th dimension, n (Si) represent set in contained element number, then sample
Range is defined as：
According to definition it is recognised that sampling range represents that any one-dimensional number of samples will not be less than C in design space.
C is bigger, then it represents that the coverage rate of sampling is wider, and C is up to the capacity of sample space.
On the other hand, the uniformity for being directed to experimental design proposes sample minimum range and the concept of sample potential.If adopt
The distance D of i point and j point in sample space is defined with 2 normsij, then sample minimum range be defined as：
The same number for defining minimum range and occurring, is designated as n (D).From the perspective of the criterion, it is believed that minimum range is got over
Greatly, then experimental design is better；In the case of minimum range identical, the number that minimum range occurs is fewer, then experimental design is better.
, can be by calculating the potential in sample space or being sample potential energy if being introduced into the concept of potential in physics：
Wherein N represents the capacity of sample space.From the perspective of the criterion, it is believed that the repulsion of whole system is smaller, real
Test design it is better, two kinds of optiaml ciriterions have certain uniformity.
Step2：The structure of hypersonic aircraft aerodynamic force and thrust agent model, using Morse's Sensitivity Analysis Method
To select suitable hypersonic aircraft agent model.Morse's Sensitivity Analysis Method (also known as basic to influence method) is global
Sensitivity Analysis Method, it is the random iteration based on a fractional analysis (OAT).If the input parameter of system is x ∈ Rn, in order to eliminate
The influence of each parameter dimension, each parameter is normalized so that each element x in xiIt is satisfied by xi∈ [0,1], i=1 ...,
n；
The output of system is defined as y=f (x) ∈ Rm.Then i-th of input factor xiBasic effect be defined as：
Wherein eiIt is 1 for i-th of element, other elements are 0 n-dimensional vector；Δ is step-length；X is the random of parameter space
Sampling, and ensure x+ Δs eiStill in parameter space.If in R sample point of parameter space stochastical sampling, by each samples of R
Point is once analyzed, meter sensitivity, is being carried out the statistical properties analysis to each sensitivity of this R, is being calculated its average and standard
Difference：
If sensitivity mean μiSignificantly different from 0, then i-th of element has global impact for output y；Sensitiveness standard
Poor σiI-th of element of bigger expression has significant nonlinear characteristic, including the interaction work between high-order term and parameter for output
With.Influences of the input parameter xi for exporting y can be indicated by Fig. 4.Should be noted that is, when the different object of analysis
When, because the influence of output response dimension, its corresponding line of demarcation are different.Or output response can be carried out immeasurable
Guiding principle, and then can be to different analysis objects, using identical criteria for classification.According to Morse's analytic approach, i-th of input because
The basic effect of son can approximately be considered as system and accordingly give the partial derivative of sample point for i-th of input.μiWith σiFrom
Statistical angle, qualitatively analyzing influence degree.
Step3：The checking of hypersonic aircraft aerodynamic force and thrust agent model, after obtaining agent model, using side
Difference is verified than evaluation indexes such as, mean square deviation error, the goodness of fit and maximum residuals to the agent model established.
Hypersonic aircraft poised state, dove colony intelligence optimized algorithm Iterative Design stream are obtained using dove colony optimization algorithm
Journey is as shown in figure 5, realize that step includes：
Step1：Build fitness function；
Step2：Species information and algorithm parameter initialization, including population quantity, optimized variable dimension, operation operator parameter
And the iterations N of two operation operatorsc1maxAnd Nc2max；
Step3：Individual speed and positional information initialization, it is initial to part and global optimum's information according to fitness quality
Change；
Step4：Map compass operator is run, according to each individual in dove group by earth magnetism and altitude of the sun information, and
Optimal information in population, position and the speed of each pigeon are updated, compares to obtain optimal path；
Step5：If iterations NcMore than Nc1max, iteration is switched to terrestrial reference operator from map compass operator；Otherwise, return
Return the 4th step；
Step6：Every pigeon is sorted according to adaptive value, retains the high pigeon of adaptive value.By the use of population central point as
The reference flight direction of remaining dove group, the position of individual is updated, calculates dove group center and adjust the position of each pigeon,
It is set to fly to dove group center；
Step7：If iterations NcMore than Nc2max, iteration ends and output result；Otherwise, the 6th step is returned.
The poised state of aircraft is solved using dove swarm intelligence algorithm, specific implementation process is as shown in Figure 6.Its main thought
For：For the poised state Solve problems under various boundary conditions, establish and value function is adapted to corresponding to it, its concrete form is such as
Under：
In formula, tfTo emulate end time, η is as Dynamic Weights, for weakening the unstable Effect of Mode of time integral；
βi, i=1,2..., 5 be weights so that each state derivative index is equably intended to optimal index.
Utilize the Fast Convergent ability and its weak dependence to initial value precision of dove colony intelligence optimized algorithm, direct searching optimization
Adaptive value function convergence is set to find optimal solution, as hypersonic aircraft poised state to extreme value.
Obtain that hypersonic aircraft is optimal designs a model using dove colony optimization algorithm, it is to find to obtain optimal models
The optimal cruising condition of flight, because the selection of optimal cruising condition and the poised state of aircraft are relevant, therefore, construction two level
Optimisation strategy optimizes to optimal cruising condition, and specific implementation process is as shown in Figure 7.Optimizing Flow is：Set algorithm first
Hunting zone, algorithm parameter and optimization initial value；In first order optimization, solved using dove colony optimization algorithm under different flight state
Poised state amount and controlled quentity controlled variable, on this basis, optimal state of flight is optimized again by dove colony optimization algorithm；Root
According to the adaptive value of each individual in cost function calculation population, progress state of flight renewal in algorithm is again returned to；When emulation time
When number reaches maximum, stop calculating, output result.Once find the optimal cruising condition of hypersonic aircraft, you can to obtain
The aerodynamic force and thrust under optimum state are obtained, and then derives that optimal hypersonic aircraft designs a model.
Generally speaking, the present invention proposes a kind of hypersonic vehicle Iterative Design method, constructs aircraft
Agent model, according to desired performance indications, design is iterated using dove colony optimization algorithm, obtain dummy vehicle parameter and
The optimum matching relation of flying condition, feasible design work is provided with iteration for the structure of hypersonic vehicle from now on
Tool.
Although the present invention is illustrated and described with regard to preferred embodiment, it is understood by those skilled in the art that
Without departing from scope defined by the claims of the present invention, variations and modifications can be carried out to the present invention.
Claims (6)
- A kind of 1. hypersonic vehicle Iterative Design method, it is characterised in that comprise the following steps：(1) hypersonic aircraft parameterized model is built by geometric design method；(2) the crucial model parameter of hypersonic aircraft is extracted by sensitivity method, reduced parameter model, obtained superb Agent model of the velocity of sound aircraft towards Iterative Design；(3) model parameter of hypersonic aircraft is optimized using dove colony optimization algorithm, obtained under different flying conditions The poised state of model；(4) the desired performance indications of hypersonic aircraft are determined, the poised state of model is iterated, obtain aircraft most Excellent designs a model.
- 2. hypersonic vehicle Iterative Design method as claimed in claim 1, it is characterised in that in step (1), lead to Crossing method of geometry structure hypersonic aircraft parameterized model is specially：Hypersonic aircraft basis configuration is used first Part disassembles strategy and is decomposed into forebody, stage casing, rear body, wing, chain of command part；It is then determined that to describe each portion Divide the geometric parameter of resemblance, and determine whether these parameters are completely independent, existing constraint between parameter, obtain describing The complete geometric parameters manifold of unmanned plane；And then the value of parameter set is specified, specific unmanned plane profile is generated, examines what is be previously obtained Can geometric parameters manifold describe unmanned plane profile；The geometric shape of hypersonic aircraft parametrization finally is carried out into bin to draw Point, using the power needed for engineering estimating method estimation modeling, construct hypersonic aircraft parameterized model.
- 3. hypersonic vehicle Iterative Design method as claimed in claim 1, it is characterised in that in step (2), lead to Cross sensitivity method and obtain the crucial model parameter of hypersonic aircraft agent model, extraction hypersonic aircraft and specifically wrap Include following steps：(21) sampling of hypersonic aircraft parameterized model data；If with SiRepresent the value set of design variable i-th dimension, n (Si) represent set in contained element number, then sample range be defined as：<mrow> <mi>C</mi> <mo>=</mo> <munder> <mrow> <mi>m</mi> <mi>i</mi> <mi>n</mi> </mrow> <mi>i</mi> </munder> <mi>n</mi> <mrow> <mo>(</mo> <msub> <mi>S</mi> <mi>i</mi> </msub> <mo>)</mo> </mrow> </mrow>According to definition it is recognised that sampling range represents that any one-dimensional number of samples will not be less than C in design space, C is got over Greatly, then it represents that the coverage rate of sampling is wider, and C is up to the capacity of sample space；The uniformity for being directed to experimental design proposes sample minimum range and the concept of sample potential, and sample is defined according to 2 norms The distance D of i point and j point in this spaceij, then sample minimum range be defined as：<mrow> <msub> <mi>D</mi> <mrow> <mi>m</mi> <mi>i</mi> <mi>n</mi> </mrow> </msub> <mo>&equiv;</mo> <munder> <mrow> <mi>m</mi> <mi>i</mi> <mi>n</mi> </mrow> <mrow> <mn>1</mn> <mo>&le;</mo> <mi>i</mi> <mo>,</mo> <mi>j</mi> <mo>&le;</mo> <mi>N</mi> <mo>,</mo> <mi>i</mi> <mo>&NotEqual;</mo> <mi>j</mi> </mrow> </munder> <msub> <mi>D</mi> <mrow> <mi>i</mi> <mo>,</mo> <mi>j</mi> </mrow> </msub> <mo>=</mo> <munder> <mrow> <mi>m</mi> <mi>i</mi> <mi>n</mi> </mrow> <mrow> <mn>1</mn> <mo>&le;</mo> <mi>i</mi> <mo>,</mo> <mi>j</mi> <mo>&le;</mo> <mi>N</mi> <mo>,</mo> <mi>i</mi> <mo>&NotEqual;</mo> <mi>j</mi> </mrow> </munder> <mo>|</mo> <mo>|</mo> <msub> <mi>x</mi> <mi>i</mi> </msub> <mo>-</mo> <msub> <mi>x</mi> <mi>j</mi> </msub> <mo>|</mo> <msub> <mo>|</mo> <mn>2</mn> </msub> </mrow>The same number for defining minimum range and occurring, is designated as n (D), from the perspective of the criterion, it is believed that and minimum range is bigger, Then experimental design is better；In the case of minimum range identical, the number that minimum range occurs is fewer, then experimental design is better；, can be by calculating the potential in sample space or being sample potential energy if being introduced into the concept of potential in physics：<mrow> <mi>P</mi> <mo>&equiv;</mo> <munderover> <mo>&Sigma;</mo> <mrow> <mi>i</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>N</mi> </munderover> <munderover> <mo>&Sigma;</mo> <mrow> <mi>j</mi> <mo>=</mo> <mi>i</mi> <mo>+</mo> <mn>1</mn> </mrow> <mi>N</mi> </munderover> <mfrac> <mn>1</mn> <mrow> <mo>|</mo> <mo>|</mo> <msub> <mi>x</mi> <mi>i</mi> </msub> <mo>-</mo> <msub> <mi>x</mi> <mi>j</mi> </msub> <mo>|</mo> <msup> <mo>|</mo> <mn>2</mn> </msup> </mrow> </mfrac> </mrow>Wherein N represents the capacity of sample space, from the perspective of the criterion, it is believed that the repulsion of whole system is smaller, and experiment is set Meter is better, and two kinds of optiaml ciriterions have certain uniformity；(22) structure of hypersonic aircraft aerodynamic force and thrust agent model, is selected using Morse's Sensitivity Analysis Method Suitable hypersonic aircraft agent model；Morse's Sensitivity Analysis Method uses the random search plan based on a fractional analysis Slightly；If the input parameter of system is x ∈ Rn, the influence of each parameter dimension is eliminated, each parameter is normalized so that in x Each element xiIt is satisfied by xi∈ [0,1], i=1 ..., n；The output of system is defined as y=f (x) ∈ Rm.Then i-th of input factor xiBasic effect be defined as：<mrow> <mfrac> <mrow> <mo>&part;</mo> <mi>f</mi> </mrow> <mrow> <mo>&part;</mo> <msub> <mi>x</mi> <mi>i</mi> </msub> </mrow> </mfrac> <mo>&ap;</mo> <msub> <mi>d</mi> <mi>i</mi> </msub> <mrow> <mo>(</mo> <mi>x</mi> <mo>)</mo> </mrow> <mo>=</mo> <mfrac> <mrow> <mi>f</mi> <mrow> <mo>(</mo> <mi>x</mi> <mo>+</mo> <mi>&Delta;</mi> <mo>&CenterDot;</mo> <msub> <mi>e</mi> <mi>i</mi> </msub> <mo>)</mo> </mrow> <mo>-</mo> <mi>f</mi> <mrow> <mo>(</mo> <mi>x</mi> <mo>)</mo> </mrow> </mrow> <mi>&Delta;</mi> </mfrac> </mrow>Wherein eiIt is 1 for i-th of element, other elements are 0 n-dimensional vector；Δ is step-length；X is the stochastical sampling of parameter space, And ensure x+ Δs eiStill in parameter space；If in R sample point of parameter space stochastical sampling, by being clicked through to each samples of R Row is once analyzed, meter sensitivity, is being carried out the statistical properties analysis to each sensitivity of this R, is being calculated its average and standard deviation：<mrow> <msub> <mi>&mu;</mi> <mi>i</mi> </msub> <mo>=</mo> <mfrac> <mn>1</mn> <mi>R</mi> </mfrac> <munderover> <mo>&Sigma;</mo> <mrow> <mi>j</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>R</mi> </munderover> <msub> <mi>d</mi> <mi>i</mi> </msub> <mrow> <mo>(</mo> <msup> <mi>x</mi> <mi>j</mi> </msup> <mo>)</mo> </mrow> </mrow><mrow> <msub> <mi>&sigma;</mi> <mi>i</mi> </msub> <mo>=</mo> <msqrt> <mrow> <mfrac> <mn>1</mn> <mrow> <mi>R</mi> <mo>-</mo> <mn>1</mn> </mrow> </mfrac> <munderover> <mo>&Sigma;</mo> <mrow> <mi>j</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>R</mi> </munderover> <msup> <mrow> <mo>&lsqb;</mo> <msub> <mi>d</mi> <mi>i</mi> </msub> <mrow> <mo>(</mo> <msup> <mi>x</mi> <mi>j</mi> </msup> <mo>)</mo> </mrow> <mo>-</mo> <msub> <mi>&mu;</mi> <mi>i</mi> </msub> <mo>&rsqb;</mo> </mrow> <mn>2</mn> </msup> </mrow> </msqrt> </mrow>If sensitivity mean μiSignificantly different from 0, then i-th of element has global impact for output y；Sensitiveness standard difference σi I-th of element of bigger expression has significant nonlinear characteristic, including the reciprocation between high-order term and parameter for output；When When analyzing different objects, due to the influence of output response dimension, its corresponding line of demarcation is different, or will can export Response carries out nondimensionalization, and then can be to different analysis objects, using identical criteria for classification；Analyzed according to Morse Method, the basic effect of i-th of input factor can approximately be considered as system accordingly for i-th of input in given sample point Partial derivative, μiWith σiFrom statistical angle, qualitatively analyzing influence degree；(23) checking of hypersonic aircraft aerodynamic force and thrust agent model, after obtaining agent model, using variance ratio, The evaluation indexes such as variance error, the goodness of fit and maximum residual are verified to the agent model established.
- 4. hypersonic vehicle Iterative Design method as claimed in claim 1, it is characterised in that, should in step (3) The model parameter of hypersonic aircraft is optimized with dove colony optimization algorithm and specifically comprised the following steps：(31) fitness function is built；(32) species information and algorithm parameter initialization, including population quantity, optimized variable dimension, operation operator parameter and two The iterations N of individual operation operatorc1maxAnd Nc2max；Individual speed and positional information initialization, according to fitness quality to part With global optimum's information initializing；(33) map compass operator is run, according to each individual in dove group by earth magnetism and altitude of the sun information, and in population Optimal information, position and the speed of each pigeon are updated, compares to obtain optimal path；(34) if iterations NcMore than Nc1max, iteration is switched to terrestrial reference operator from map compass operator；Otherwise, the is returned (33) step；(35) every pigeon is sorted according to adaptive value, retains the high pigeon of adaptive value；Remaining dove is used as by the use of population central point The reference flight direction of group, the position of individual is updated, calculates dove group center and adjust the position of each pigeon, fly it To dove group center；(36) if iterations NcMore than Nc2max, iteration ends and output result；Otherwise, (35) step is returned.
- 5. hypersonic vehicle Iterative Design method as claimed in claim 1, it is characterised in that in step (3), obtain The poised states of different flying condition drags is specially：For the poised state Solve problems under various boundary conditions, build Stand and value function is adapted to corresponding to it, its concrete form is as follows：<mrow> <mi>J</mi> <mo>=</mo> <msubsup> <mo>&Integral;</mo> <mn>0</mn> <msub> <mi>t</mi> <mi>f</mi> </msub> </msubsup> <mi>&eta;</mi> <mrow> <mo>(</mo> <msub> <mi>&beta;</mi> <mn>1</mn> </msub> <mo>|</mo> <mover> <mi>v</mi> <mo>&CenterDot;</mo> </mover> <mo>|</mo> <mo>+</mo> <msub> <mi>&beta;</mi> <mn>2</mn> </msub> <mo>|</mo> <mover> <mi>&gamma;</mi> <mo>&CenterDot;</mo> </mover> <mo>|</mo> <mo>+</mo> <msub> <mi>&beta;</mi> <mn>3</mn> </msub> <mo>|</mo> <mover> <mi>h</mi> <mo>&CenterDot;</mo> </mover> <mo>|</mo> <mo>+</mo> <msub> <mi>&beta;</mi> <mn>4</mn> </msub> <mo>|</mo> <mover> <mi>&alpha;</mi> <mo>&CenterDot;</mo> </mover> <mo>|</mo> <mo>+</mo> <msub> <mi>&beta;</mi> <mn>5</mn> </msub> <mo>|</mo> <mover> <mi>q</mi> <mo>&CenterDot;</mo> </mover> <mo>|</mo> <mo>)</mo> </mrow> <mi>d</mi> <mi>t</mi> </mrow>In formula, tfTo emulate end time, η is as Dynamic Weights, for weakening the unstable Effect of Mode of time integral；βi,i =1,2..., 5 are weights so that each state derivative index is equably intended to optimal index；Utilize dove colony intelligence optimized algorithm Fast Convergent ability and its weak dependence to initial value precision, direct searching optimization adaptive value function convergence is found to extreme value Optimal solution, as hypersonic aircraft poised state.
- 6. hypersonic vehicle Iterative Design method as claimed in claim 1, it is characterised in that in step (4), really Determine the desired performance indications of hypersonic aircraft, the poised state to model is iterated, obtains the optimal design of aircraft Model is specially：Obtain that hypersonic aircraft is optimal designs a model using dove colony optimization algorithm, obtaining optimal models is The optimal cruising condition of flight is found, because the selection of optimal cruising condition and the poised state of aircraft are relevant, therefore, construction 2-level optimization's strategy optimizes to optimal cruising condition, and Optimizing Flow is：First set algorithm hunting zone, algorithm parameter and Optimize initial value；In first order optimization, poised state amount and control under different flight state are solved using dove colony optimization algorithm Amount, on this basis, is optimized again by dove colony optimization algorithm to optimal state of flight；According to cost function calculation population In each individual adaptive value, again return to progress state of flight renewal in algorithm；When simulation times reach maximum, stop Calculate, output result；Once find the optimal cruising condition of hypersonic aircraft, you can to obtain the aerodynamic force under optimum state And thrust, and then derive that optimal hypersonic aircraft designs a model.
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