CN108509684A - Steering engine and dynamic load simulator adaptation design method - Google Patents
Steering engine and dynamic load simulator adaptation design method Download PDFInfo
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- CN108509684A CN108509684A CN201810179239.8A CN201810179239A CN108509684A CN 108509684 A CN108509684 A CN 108509684A CN 201810179239 A CN201810179239 A CN 201810179239A CN 108509684 A CN108509684 A CN 108509684A
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- steering engine
- load simulator
- dynamic load
- rigidity
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/10—Geometric CAD
- G06F30/15—Vehicle, aircraft or watercraft design
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/12—Computing arrangements based on biological models using genetic models
- G06N3/126—Evolutionary algorithms, e.g. genetic algorithms or genetic programming
Abstract
A kind of steering engine of disclosure offer and dynamic load simulator adaptation design method, including：Step 1)：The first parameter with reference to steering engine is obtained, the static rigidity with reference to steering engine is calculated according to the first parameter, according to the static rigidity with reference to steering engine, obtains the upper limit value of the mechanical integrated rigidity of dynamic load simulator；Step 2)：The second parameter with reference to steering engine is obtained, the lower limiting value of the mechanical integrated rigidity of dynamic load simulator is obtained；Step 3)：According to upper limit value and lower limiting value, the matching relationship formula of target steering engine and the mechanical integrated rigidity of dynamic load simulator is built；And step 4)：Using matching relationship formula as the evaluation function of genetic algorithm, the fitness of the individual in the iteration population in in-service evaluation function pair genetic algorithm is evaluated；Limited number of time iterative evolution is carried out to the individual in iteration population, obtains the mechanical integrated rigidity of best match load simulator of target steering engine.
Description
Technical field
This disclosure relates to which steering engine corollary system apparatus field more particularly to a kind of steering engine are matched with dynamic load simulator and are set
Meter method, for matching standard termination simulated loading system for different steering engines.
Background technology
One of the typical case of dynamic load simulator is to carry out simulation loading to the steering engine position servomechanism of aircraft,
Ground simulation rudder face aerodynamic load suffered in flight course in the air is may be implemented in, half to constitute flight control system is real
Object emulates, to effectively shorten development period of aircraft.It is embedded according in load simulator control simulation computer
There is the aircraft six degrees of freedom model that wind tunnel data and effectively accurate Aviate equation are established, according to flying height, speed, rudder face
The related physical quantity such as corner and atmosphere data, it is suffered pneumatic in the entire flight course of computer sim- ulation aircraft in real time
Hinge moment load forms torque load spectrum.Dynamic load simulator can real-time reception simulation computer load instruction, and will
It is accurately loaded onto by loading channel in steering engine servo mechanism.
Dynamic load simulator, can be to entire servo as a kind of higher test of real-time and analog simulation equipment
The product life cycels of structure development play the role of it is highly important, it run through servo-drive system optimization design, performance test with
Calibration and fault diagnosis, so the design requirement of load simulator is usually very high, especially in its loading accuracy and required dynamic
On state requires.Dynamic load simulator is that the HWIL simulation to steering engine servo mechanism and the test of steering engine relevant parameter are mating
Equipment, so in practical applications must access steering engine to be tested wherein.But in actual loading experiment often exist pair
For the loading system that certain steering engine has been debugged, after replacing another steering engine, the loading system Control platform meeting of load simulator
It changes, loading system can influence the limiting performance of dynamic load simulator because of the access of different steering engines, or even sometimes
The case where generating loss of stability and then diverging out of control, it not only threatens the safety problem of steering engine mechanism itself, or even big
Power can threaten the personal safety of related commissioning personnel during loading, so collateral security safety and dynamic load simulator
The angle of the Control platform matching process found between a kind of effective and feasible steering engine and load simulator that sets out very has engineering
Meaning.Since there are the more theoretical parameters for being difficult to accurately obtain in the matching primitives of load simulator, this is matching process
Can difficulty really be increased applied to Practical Project, introduce genetic algorithm thus.
Genetic algorithm is that a kind of mechanism of selection and heredity by natural imitation circle finds the natural evolution of optimal solution
Algorithm.The main means of Solve problems are to be realized by iteration, but general alternative manner holds in general numerical method
It is easily absorbed in the trap of local minimum and " endless loop " phenomenon occurs, make iteration that can not continue.Genetic algorithm overcomes well
This disadvantage, is a kind of global optimization approach.Genetic algorithm has good ability of searching optimum, can be rapidly empty by solution
Between in all solutions search out, the rapid decrease trap without being absorbed in locally optimal solution；And its intrinsic parallism is utilized,
Distributed Calculation can be easily carried out, solving speed is accelerated.
Invention content
The purpose of the disclosure is looked for be matched under conditions of ensureing limiting performance for specific steering engine in practice in engineering
To suitable dynamic load simulator is used, a kind of effective way is provided for the design of dynamic load simulator.
A kind of steering engine of disclosure offer and dynamic load simulator adaptation design method, including：
Step 1)：The first parameter with reference to steering engine is obtained, the static rigidity with reference to steering engine is calculated according to the first parameter, according to
With reference to the static rigidity of steering engine, the upper limit value of the mechanical integrated rigidity of dynamic load simulator is obtained；
Step 2)：The second parameter with reference to steering engine is obtained, the lower limiting value of the mechanical integrated rigidity of dynamic load simulator is obtained；
Step 3)：According to upper limit value and lower limiting value, structure target steering engine and the mechanical integrated rigidity of dynamic load simulator
Matching relationship formula；And
Step 4)：Using matching relationship formula as the evaluation function of genetic algorithm, in in-service evaluation function pair genetic algorithm
The fitness of individual in iteration population is evaluated；Limited number of time iterative evolution is carried out to the individual in iteration population, obtains mesh
Mark the mechanical integrated rigidity of best match load simulator of steering engine.
Further include step 5) according at least one embodiment of the disclosure：According to best match load simulator machinery
Integral stiffness makes dynamic load simulator.
According at least one embodiment of the disclosure, in step 1), the first parameter is piston area with reference to steering engine, rudder
Machine servo valve valve core displacement drive coefficient and/or steering engine servo valve current amplifier gain.
According at least one embodiment of the disclosure, in step 2), the second parameter is steering engine bandwidth；According to steering engine wideband
Requirement, the closed loop wideband of loading system is calculated, to obtain the lower limiting value of the mechanical integrated rigidity of dynamic load simulator.
It is hydraulic sterring engine with reference to steering engine according at least one embodiment of the disclosure.
According at least one embodiment of the disclosure, in step 3), matching relationship formula is
Wherein faFor the bandwidth of steering engine, JtTotal inertia, G are converted into for the machinery of load simulatortFor the machinery of load simulator
Integral stiffness, n are proportionality coefficient, and n needs to meetγa0For the static rigidity with reference to steering engine.
According at least one embodiment of the disclosure, step 4) specifically includes：
Step 41)：The requirement of redundant force is eliminated according to load simulator, is formulated mechanical integrated about dynamic load simulator
The decision variable of object function is arranged in the object function of rigidity；
Step 42)：Convert decision variable to binary coding string；
Step 43)：Initial population is generated, N row binary coding strings are randomly generated, often row binary coding string is a m
The individual that a binary digit is constituted, N row binary coding strings constitute a group, the iteration starting point as genetic algorithm；M is certainly
So number, N is natural number；
Step 44)：Fitness function is formulated by matching relationship formula, by N row binary coding string Gray codes at actual value
Fitness function is brought into evaluate quality individual in population；
Step 45)：Adaptive value is calculated according to fitness function to individual in population and is selected, then to individual
Binary coding string carries out intersection and the variation of setting probability, completes the primary evolution to population；And
Step 46)：Stop genetic algorithm if reaching iterations, if not up to iterations go to step 44).
According at least one embodiment of the disclosure, in step 41), the decision variable of object function is set as 1, certainly
Plan variable is the mechanical integrated rigidity of dynamic load simulator.
According at least one embodiment of the disclosure, in step 42), specifically, it is first determined coding and Gray code are calculated
Method, then convert decision variable to the binary coding string that regular length is m, m is natural number.
According at least one embodiment of the disclosure, in step 45), by " in a manner of roulette " to individual in population according to
The adaptive value that fitness function is calculated is selected.
Specific implementation mode
The disclosure is described in further detail below.It is understood that the specific embodiments described herein
It is only used for explaining related content, rather than the restriction to the disclosure.
It should be noted that in the absence of conflict, the feature in embodiment of the present disclosure can be combined with each other.
The basic thought of genetic algorithm is the parameter coding problem to be optimized, uses the shape of specific bit string herein
Formula, then forms candidate solution of the initial population as problem to be asked by several bit strings, and assessment is obtained in evaluation function
By selection, the iterative search procedures intersected, made a variation under conditions of value, optimum state is finally converged on, below in conjunction with heredity
The matching formula of the step of algorithm and steering engine and dynamic load simulator elaborates to the disclosure.
The steering engine of present embodiment and dynamic load simulator adaptation design method, including：
Step 1)：The first parameter with reference to steering engine is obtained, the static rigidity with reference to steering engine is calculated according to the first parameter, according to
With reference to the static rigidity of steering engine, the upper limit value of the mechanical integrated rigidity of dynamic load simulator is obtained；Step 2)：It obtains and refers to steering engine
The second parameter, obtain the mechanical integrated rigidity of dynamic load simulator lower limiting value；Step 3)：According to upper limit value and lower limiting value,
Build the matching relationship formula of target steering engine and the mechanical integrated rigidity of dynamic load simulator；Step 4)：Using matching relationship formula as
The fitness of the evaluation function of genetic algorithm, the individual in the iteration population in in-service evaluation function pair genetic algorithm is commented
Valence；Limited number of time iterative evolution is carried out to the individual in iteration population, obtains the best match load simulator machinery of target steering engine
Integral stiffness；And step 5)：Dynamic load simulation is made according to the mechanical integrated rigidity of best match load simulator
Device.The dynamic load simulator made by the mechanical integrated rigidity Design of this best match load simulator is ensureing loading system pole
It is sex-limited can and in the requirement of bandwidth using the frequency characteristic of static load come reflect its band material object steering engine characteristic, design rudder
" the standard loading system " of machine.Above-mentioned reference steering engine is hydraulic sterring engine.
Wherein the first parameter is with reference to the piston area of steering engine, steering engine servo valve valve core displacement drive coefficient and/or steering engine
Servo valve current amplifier gain, the second parameter are steering engine bandwidth.
Wherein, when obtaining the lower limiting value of the mechanical integrated rigidity of dynamic load simulator, specifically, according to steering engine wideband
It is required that the closed loop wideband of loading system is calculated, to obtain the lower limiting value of the mechanical integrated rigidity of dynamic load simulator.
The matching relationship formula of structure is in step 3)
Wherein faFor the bandwidth of steering engine, JtTotal inertia, G are converted into for the machinery of load simulatortFor the machinery of load simulator
Integral stiffness, n are proportionality coefficient, and n needs to meetγa0For the static rigidity with reference to steering engine.
Wherein step 4) specifically includes：Step 41)：The requirement of redundant force is eliminated according to load simulator, is formulated about dynamic
The object function of the mechanical integrated rigidity of state load simulator, is arranged the decision variable of the object function；The object function
Decision variable is set as 1, and the decision variable is the mechanical integrated rigidity of the dynamic load simulator；Step 42)：By institute
It states decision variable and is converted into binary coding string：Coding and Gray code algorithm are determined first, then convert the decision variable to
Regular length is the binary coding string of m, and m is natural number；Step 43)：Initial population is generated, N row binary systems volume is randomly generated
Sequence, often row binary coding string is the individual that a m binary digit is constituted, and N row binary coding strings constitute a group,
Iteration starting point as genetic algorithm；M is natural number, and N is natural number；Step 44)：It is formulated and is adapted to by the matching relationship formula
Function is spent, it is individual excellent in population to evaluate at actual value to bring N rows binary coding string Gray code into the fitness function
It is bad；Step 45)：Individual in population is selected according to the adaptive value that the fitness function is calculated by " in a manner of roulette "
It selects, then carries out intersection and the variation of setting probability to the binary coding string of individual, complete the primary evolution to population；And step
It is rapid 46)：Stop genetic algorithm if reaching iterations, if not up to iterations go to step 44).
In addition the adaptation design method of the disclosure can also be used for judging whether specific dynamic load simulator can be used for certain
The load of type steering engine need to only be sentenced in this case using the type steering engine parameter as the related coefficient of evaluation function in genetic algorithm
Whether mechanical integrated rigidity represented after being decoded according to the individual that genetic algorithm iteration is eliminated of being completely cured is included.
It will be understood by those of skill in the art that the 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 steering engine and dynamic load simulator adaptation design method, which is characterized in that including：
Step 1)：The first parameter with reference to steering engine is obtained, the static rigidity with reference to steering engine is calculated according to first parameter, according to
The static rigidity with reference to steering engine obtains the upper limit value of the mechanical integrated rigidity of dynamic load simulator；
Step 2)：The second parameter with reference to steering engine is obtained, the lower limiting value of the mechanical integrated rigidity of dynamic load simulator is obtained；
Step 3)：According to the upper limit value and the lower limiting value, structure target steering engine is mechanical integrated just with dynamic load simulator
The matching relationship formula of degree；And
Step 4)：Using the matching relationship formula as the evaluation function of genetic algorithm, using the evaluation function to genetic algorithm
In iteration population in individual fitness evaluated；Limited number of time iterative evolution is carried out to the individual in iteration population, is obtained
Obtain the mechanical integrated rigidity of best match load simulator of target steering engine.
2. steering engine according to claim 1 and dynamic load simulator adaptation design method, which is characterized in that further include step
It is rapid 5)：Dynamic load simulator is made according to the mechanical integrated rigidity of best match load simulator.
3. steering engine according to claim 1 and dynamic load simulator adaptation design method, which is characterized in that step 1)
In, first parameter is with reference to the piston area of steering engine, steering engine servo valve valve core displacement drive coefficient and/or steering engine servo valve
Current amplifier gain.
4. steering engine according to claim 1 and dynamic load simulator adaptation design method, which is characterized in that step 2)
In, second parameter is steering engine bandwidth；According to the requirement of the steering engine wideband, the closed loop wideband of loading system is calculated, to
Obtain the lower limiting value of the mechanical integrated rigidity of dynamic load simulator.
5. according to claim 1-4 any one of them steering engine and dynamic load simulator adaptation design method, which is characterized in that
The reference steering engine is hydraulic sterring engine.
6. steering engine according to claim 1 and dynamic load simulator adaptation design method, which is characterized in that step 3)
In, the matching relationship formula is
Wherein faFor the bandwidth of steering engine, JtTotal inertia, G are converted into for the machinery of load simulatortFor the mechanical integrated of load simulator
Rigidity, n are proportionality coefficient, and n needs to meetγa0For the static rigidity with reference to steering engine.
7. according to claim 1-6 any one of them steering engine and dynamic load simulator adaptation design method, which is characterized in that
Step 4) specifically includes：
Step 41)：The requirement of redundant force is eliminated according to load simulator, is formulated about the mechanical integrated rigidity of dynamic load simulator
Object function, the decision variable of the object function is set；
Step 42)：Convert the decision variable to binary coding string；
Step 43)：Initial population is generated, N row binary coding strings are randomly generated, often row binary coding string is a m two
The individual that system position is constituted, N row binary coding strings constitute a group, the iteration starting point as genetic algorithm；M is nature
Number, N is natural number；
Step 44)：Fitness function is formulated by the matching relationship formula, by N row binary coding string Gray codes at actual value
The fitness function is brought into evaluate quality individual in population；
Step 45)：Adaptive value is calculated according to the fitness function to individual in population and is selected, then to individual
Binary coding string carries out intersection and the variation of setting probability, completes the primary evolution to population；And
Step 46)：Stop genetic algorithm if reaching iterations, if not up to iterations go to step 44).
8. steering engine according to claim 7 and dynamic load simulator adaptation design method, which is characterized in that step 41)
In, the decision variable of the object function is set as 1, and the decision variable is the mechanical integrated of the dynamic load simulator
Rigidity.
9. steering engine according to claim 7 and dynamic load simulator adaptation design method, which is characterized in that step 42)
In, specifically, it is first determined coding and Gray code algorithm, then convert the decision variable to the binary system that regular length is m
Coded strings, m are natural number.
10. steering engine according to claim 7 and dynamic load simulator adaptation design method, which is characterized in that step 45)
In, individual in population is selected according to the adaptive value that the fitness function is calculated by " in a manner of roulette ".
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| CN113656920A (en) * | 2021-10-20 | 2021-11-16 | 中国空气动力研究与发展中心计算空气动力研究所 | Missile rudder surface hinge moment design method capable of reducing power redundancy of steering engine |
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| CN113656920A (en) * | 2021-10-20 | 2021-11-16 | 中国空气动力研究与发展中心计算空气动力研究所 | Missile rudder surface hinge moment design method capable of reducing power redundancy of steering engine |
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