CN101930494A - Method for identifying aircraft model with undetermined order and parameters based on mode segmentation and genetic algorithm - Google Patents
Method for identifying aircraft model with undetermined order and parameters based on mode segmentation and genetic algorithm Download PDFInfo
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Abstract
A method for identifying an aircraft model with undetermined order and parameters based on mode segmentation and genetic algorithm belongs to the aircraft identification modeling field. The method is characterized by comprising a frequency domain response stage, a search and identification stage and a time domain verification stage, wherein the frequency domain response stage is used for acquiring the identification experiment data of the aircraft as the original experiment data for model identification and comprises the steps of sweep frequency flight experiment, time domain data acquisition, frequency domain transformation and data validity test; the search and identification stage is used for probing and identifying all the possible model structures of the aircraft one by one by utilizing mode segmentation and genetic algorithm and comprises the steps of order initialization, mode segmentation model, genetic algorithm identification and mean value result record; and the time domain verification stage is used for verifying the model proximate to the original dynamics data of the aircraft and comprises the steps of identification result optimization, optimal model determination, double-pulse experiment and model verification. The method dispenses with complex mechanism analysis and order estimation process, retains all the parameters of the aircraft dynamics model by utilizing the mode segmentation model and searches for various possible mode segmentation model structures by utilizing genetic algorithm, thus acquiring the high-precision dynamics model of the aircraft, especially the helicopter through identification.
Description
Technical field
The present invention is the discrimination method that is used for aircraft especially helicopter is carried out Dynamic Modeling, and identification obtains kinetic model accurately.Be mainly used in technical fields such as aircraft identification modeling and control.
Background technology
The kinetic model of aircraft is the prerequisite of flight control.Have only the accurate kinetic model of acquisition, could obtain good flight control effect.Otherwise, if there is not accurate kinetic model precision, a lot of advanced flight control algorithms even can't be achieved.
Traditional aircraft modeling method mainly contains 3 kinds, wind-tunnel modeling, modelling by mechanism and identification modeling.And for aircraft especially helicopter, its structure, flow field and flight theory are very complicated.Adopt wind-tunnel modeling and modelling by mechanism to be difficult to disorderly flow field, its surface of precise quantification and inner complicated power and catanator.Therefore, begin to adopt the identification modeling method in recent years, aircraft is carried out modeling according to real flight experiment data.In many identification modeling methods, with the flight modeling tool software CIFER of AUS and NASA (National Aeronautics and Space Administration) joint development
(Comprehensive Identification from Frequency Responses) is the typical case, and it has represented the especially highest level of helicopter identification modeling of current aircraft.Yet the aircraft especially identification modeling technology of helicopter belongs to hard-core technology, and western countries carry out the blockade on new techniques of height to China.Therefore, be necessary to rely on self strength to carry out the especially research of helicopter modeling technique of aircraft.
Traditional identification modeling method has two critical step, and the first is determined the order of dummy vehicle, and it two is that the model of determining order is carried out identification modeling.And carry out identification modeling by these two steps, there is following drawback respectively.
Step 1 is determined the order of dummy vehicle.Traditional order determines that method is Analysis on Mechanism or empirical data.Because aircraft is structure, control and the flow field complexity of helicopter especially, traditional Analysis on Mechanism and empirical data are difficult to accurately determine model order.And whether accurate the influence to identification result of model order be very big.
Step 2 is carried out identification modeling to the model of determining order.Traditional identification modeling method adopts methods such as least square, Levy and numerical optimization more, and the conventionally form of vehicle dynamics model (as polynomial expression transport function, zero limit transport function, state-space model etc.) is directly carried out modeling.Because the aircraft high-order model characteristics that especially helicopter had, so simultaneously, accurately all multiparameters of high-order time model to be carried out identification be unusual difficulty.Model order is high more, and then identification precision is difficult to guarantee more.Therefore, present identification modeling method need be traded off between model order and model accuracy.In addition, methods such as the employed least square of traditional discrimination method, Levy and numerical optimization are difficult to that also vehicle dynamics is decided the order model and carry out multiparameter, multiregion, modeling accurately.Comprehensive above factor, traditional discrimination method (comprises CIFER
) especially the helicopter dynamics modeling accuracy is limited to aircraft.
Compare with traditional method, the present invention has avoided above-mentioned two committed steps, but relies on the aircraft experimental data fully, and utilizes the strategy of search identification, obtains structure of models and whole parameter.The principle of search identification strategy is: at first all possible order combination of model is converted into the mode segmentation model one by one, and utilizes computing machine automatically to the identification one by one of mode segmentation model; Subsequently, seek the mode segmentation model of cost function minimum in all identification results, thereby find the model the most approaching with the vehicle dynamics response data, i.e. identification obtains the kinetic model of aircraft; At last, utilize time domain checking means that the optimization model that identification obtains is tested, to guarantee its validity.
Through the processing of above step, the present invention can obtain the especially high precision kinetic model of helicopter of aircraft.
Significant advantage of the present invention is the precision that has improved the flight dynamics Model Distinguish, and need not to carry out before identification complicated loaded down with trivial details and modelling by mechanism analysis and model order the precision deficiency are estimated.The high-precision modeling main cause of the present invention is: utilize all possible model structure of Computer Automatic Search identification aircraft, thereby identification obtains the model the most approaching with the vehicle dynamics response data, and is not subjected to the restriction of model order derivation precision and model order.
Through theoretical analysis and a large amount of flight experiment checkings, modeling accuracy of the present invention is far above the most authoritative present flight modeling tool software CIFER
In addition, the present invention also has clear concept, simple to operate, the advantage that is easy to realize and is convenient to the flight control design.Use especially helicopter kinetic model discrimination method of aircraft that the present invention proposes, can effectively shorten aircraft Design of Flight Control cycle of helicopter especially, and significantly improve its flight control effect.Therefore, the present invention can accelerate the development of new model or the improvement of old type tube, and the progress of seriation, universalization, through engineering approaches, shortens the gap with world powers.
Summary of the invention
The object of the present invention is to provide and a kind ofly can high precision obtain the especially discrimination method of helicopter parameter model of aircraft.
The invention is characterized in, contain: frequency domain response, search identification and time domain 3 stages of checking, wherein:
The frequency domain response stage is used to obtain the identification experimental data of aircraft, with original experimental data as Model Distinguish, comprise frequency sweep flight experiment, time domain data collection, frequency domain transform and 4 steps of data validation, its treatment scheme is: by the frequency sweep flight experiment, make aircraft make dynamic response under swept-frequency signal excitation; Through the time domain data collection, obtain the time domain experimental data of aircraft frequency sweep command signal and dynamic response; Through frequency domain transform, time domain data is converted into the frequency domain response data; In the data validation step, by the check frequency domain response data degree of correlation
Judging its validity, thereby whether decision can be used for next step Model Distinguish; The degree of correlation
Test stone be: as not satisfying
Then Identification Data is invalid, should carry out the frequency sweep flight experiment again; Otherwise data are effective, can begin to search for the work in identification stage;
The search identification stage is utilized mode segmentation and genetic algorithm, sound out one by one and all possible model structure of identification aircraft, comprise order initialization, mode segmentation model, genetic algorithm identification and 4 steps of average outcome record, its treatment scheme is: by the order initialization, set the order scope of this dummy vehicle, to determine the hunting zone of genetic algorithm; In mode segmentation model step,, generate a mode segmentation model that is suitable for genetic algorithm according to the model order of current computing; Repeat the identification step in genetic algorithm, utilize genetic algorithm that current mode segmentation model is carried out identification, make it farthest to approach the frequency domain response data; For avoiding the influence of genetic algorithm randomness, can utilize genetic algorithm that each model is carried out repeatedly (as 20 times) and repeat identification, and with the result of mean value as cost function; After each genetic algorithm identification finishes, model and cost function that identification obtains are noted, to be used for the optimizing of next stage; After the traversal identification is finished in all order combinations over to, the work of time domain Qualify Phase will be changed;
The time domain Qualify Phase is used for determining learning the immediate model of data with the aircraft original power, and it is verified, comprise: identification result optimizing, optimization model are determined, dipulse is tested and 4 steps of modelling verification, its treatment scheme is: by the identification result optimizing, find minimum cost function; In the optimization model determining step, the model of minimum cost function correspondence is defined as optimization model; In the dipulse experimental procedure, obtain the time domain data of aircraft dipulse experiment; In the modelling verification stage, utilize the time domain data of dipulse experiment that optimization model is verified; If on setting value (for example 80%), then thinking, the goodness of fit of optimization model and dipulse experimental data obtained satisfied dummy vehicle; Otherwise, should carry out the identification modeling process again.
Compare with traditional method, the present invention has avoided above-mentioned two committed steps, but obtains structure of models and whole parameter by the aircraft experimental data identification fully.The present invention at first is converted into the mode segmentation model one by one with all possible order combination of model, and utilizes computing machine automatically to the identification one by one of mode segmentation model by adopting the strategy of search identification; Subsequently, seek the mode segmentation model of cost function minimum in all identification results, thereby find the model the most approaching with the vehicle dynamics response data, i.e. identification obtains the kinetic model of aircraft; At last, utilize time domain checking means that the optimization model that identification obtains is tested, to guarantee its validity.
Through the processing of above step, the present invention can obtain the especially high precision kinetic model of helicopter of aircraft.
Significant advantage of the present invention is the precision that has improved the flight dynamics Model Distinguish, and need not to carry out before identification complicated loaded down with trivial details and modelling by mechanism analysis and model order the precision deficiency are estimated.The high-precision modeling main cause of the present invention is: utilize all possible model structure of Computer Automatic Search identification aircraft, thereby identification obtains the model the most approaching with the vehicle dynamics response data, and is not subjected to the restriction of model order derivation precision and model order.
Through theoretical analysis and a large amount of flight experiment checkings, modeling accuracy of the present invention is far above the most authoritative present flight modeling tool software CIFER
In addition, the present invention also has clear concept, simple to operate, the advantage that is easy to realize and is convenient to the flight control design.Use especially helicopter kinetic model discrimination method of aircraft that the present invention proposes, can effectively shorten aircraft Design of Flight Control cycle of helicopter especially, and significantly improve its flight control effect.Therefore, the present invention can accelerate the development of new model or the improvement of old type tube, and the progress of seriation, universalization, through engineering approaches, shortens the gap with world powers.
Description of drawings
Fig. 1 is based on the process flow diagram of the indefinite order parameter model of the aircraft discrimination method of mode segmentation and genetic algorithm.Obtain the frequency domain response data of aircraft among Fig. 1 by frequency domain response, sound out all possible model structure, and determine and check the kinetic model of optimum at the time domain Qualify Phase by the search identification.
Embodiment
Form by frequency domain response, search identification and time domain 3 stages of checking based on the indefinite order parameter model of the aircraft of mode segmentation and genetic algorithm discrimination method.
The frequency domain response stage is used to obtain the identification experimental data of aircraft, with original experimental data as Model Distinguish, comprise frequency sweep flight experiment, time domain data collection, frequency domain transform and 4 steps of data validation, its treatment scheme is: by the frequency sweep flight experiment, make aircraft make dynamic response under swept-frequency signal excitation; Through the time domain data collection, obtain the time domain experimental data of aircraft frequency sweep command signal and dynamic response; Through frequency domain transform, time domain data is converted into the frequency domain response data; In the data validation step, by the check frequency domain response data degree of correlation
Judging its validity, thereby whether decision can be used for next step Model Distinguish; The degree of correlation
Test stone be: as not satisfying
Then Identification Data is invalid, should carry out the frequency sweep flight experiment again; Otherwise data are effective, can begin to search for the work in identification stage;
The search identification stage is utilized mode segmentation and genetic algorithm, sound out one by one and all possible model structure of identification aircraft, comprise order initialization, mode segmentation model, genetic algorithm identification and 4 steps of average outcome record, its treatment scheme is: by the order initialization, set the order scope of this dummy vehicle, to determine the hunting zone of genetic algorithm; In mode segmentation model step,, generate a mode segmentation model that is suitable for genetic algorithm according to the model order of current computing; Repeat the identification step in genetic algorithm, utilize genetic algorithm that current mode segmentation model is carried out identification, make it farthest to approach the frequency domain response data; For avoiding the influence of genetic algorithm randomness, can utilize genetic algorithm that each model is carried out repeatedly (as 20 times) and repeat identification, and with the result of mean value as cost function; After each genetic algorithm identification finishes, model and cost function that identification obtains are noted, to be used for the optimizing of next stage; After the traversal identification is finished in all order combinations over to, the work of time domain Qualify Phase will be changed;
The time domain Qualify Phase is used for determining learning the immediate model of data with the aircraft original power, and it is verified, comprise: identification result optimizing, optimization model are determined, dipulse is tested and 4 steps of modelling verification, its treatment scheme is: by the identification result optimizing, find minimum cost function; In the optimization model determining step, the model of minimum cost function correspondence is defined as optimization model; In the dipulse experimental procedure, obtain the time domain data of aircraft dipulse experiment; In the modelling verification stage, utilize the time domain data of dipulse experiment that optimization model is verified; If on setting value (for example 80%), then thinking, the goodness of fit of optimization model and dipulse experimental data obtained satisfied dummy vehicle; Otherwise, should carry out the identification modeling process again.
The present invention propose the identification modeling process need not loaded down with trivial details Analysis on Mechanism (as order determine, parameter measurement etc.) process.Only need progressively processing, can obtain the especially high precision kinetic model of helicopter of aircraft through above three phases.
Compare with traditional method, the present invention has avoided above-mentioned two committed steps, but obtains structure and whole parameter of model fully by the flight experiment data identification, thereby determines the kinetic model of aircraft. The present invention at first is converted into the mode segmentation model with the possible order combination of model one by one by adopting the strategy of search identification, and as one by one identification of object; Subsequently, seek the mode segmentation model of cost function minimum in all identification results, thereby find the model that approaches the most with the vehicle dynamics response data, i.e. identification obtains the kinetic model of aircraft; At last, utilize time domain checking means that the optimal models that identification obtains is tested, to guarantee its validity.
Claims (1)
1. belong to the aircraft identification modeling field based on the indefinite order parameter model of the aircraft of mode segmentation and genetic algorithm discrimination method, it is characterized in that, contain: frequency domain response, search identification and time domain 3 stages of checking, wherein:
The frequency domain response stage is used to obtain the identification experimental data of aircraft, with original experimental data as Model Distinguish, comprise frequency sweep flight experiment, time domain data collection, frequency domain transform and 4 steps of data validation, its treatment scheme is: by the frequency sweep flight experiment, make aircraft make dynamic response under swept-frequency signal excitation; Through the time domain data collection, obtain the time domain experimental data of aircraft frequency sweep command signal and dynamic response; Through frequency domain transform, time domain data is converted into the frequency domain response data; In the data validation step, by the check frequency domain response data degree of correlation
Judging its validity, thereby whether decision can be used for next step Model Distinguish; The degree of correlation
Test stone be: as not satisfying
Then Identification Data is invalid, should carry out the frequency sweep flight experiment again; Otherwise data are effective, can begin to search for the work in identification stage;
The search identification stage is utilized mode segmentation and genetic algorithm, sound out one by one and all possible model structure of identification aircraft, comprise order initialization, mode segmentation model, genetic algorithm identification and 4 steps of average outcome record, its treatment scheme is: by the order initialization, set the order scope of this dummy vehicle, to determine the hunting zone of genetic algorithm; In mode segmentation model step,, generate a mode segmentation model that is suitable for genetic algorithm according to the model order of current computing; Repeat the identification step in genetic algorithm, utilize genetic algorithm that current mode segmentation model is carried out identification, make it farthest to approach the frequency domain response data; For avoiding the influence of genetic algorithm randomness, can utilize genetic algorithm that each model structure is carried out repeatedly (as 20 times) and repeat identification, and with the result of mean value as cost function; After each genetic algorithm identification finishes, model and cost function that identification obtains are noted, to be used for the optimizing of next stage; After the traversal identification is finished in all order combinations over to, the work of time domain Qualify Phase will be changed;
The time domain Qualify Phase is used for determining learning the immediate model of data with the aircraft original power, and it is verified, comprise: identification result optimizing, optimization model are determined, dipulse is tested and 4 steps of modelling verification, its treatment scheme is: by the identification result optimizing, find minimum cost function; In the optimization model determining step, the model of minimum cost function correspondence is defined as optimization model; In the dipulse experimental procedure, obtain the time domain data of aircraft dipulse experiment; In the modelling verification stage, utilize the time domain data of dipulse experiment that optimization model is verified; If on setting value (as 80%), then can thinking, the goodness of fit of optimization model and dipulse experimental data obtained enough accurate dummy vehicle; Otherwise, should carry out whole identification modeling processes again.
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| CN111538237A (en) * | 2020-03-20 | 2020-08-14 | 北京航空航天大学 | Method for identifying and correcting non-linear light gray model of tilt rotor unmanned aerial vehicle |
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