CN110532614B - Pneumatic optimization method for rotating speed characteristic of rotating missile - Google Patents
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Abstract
A pneumatic optimization method for rotating speed characteristics of rotating missiles comprises the following steps: s1, determining parameters of a genetic algorithm; s2, determining the pneumatic appearance characteristic dimension influencing the roll driving torque and the damping torque, and arranging the pneumatic appearance characteristic dimension as a chromosome combination of a genetic algorithm; s3, determining the characteristic size as a gene fragment, and setting a reasonable feasible range; s4, determining a fitness function; s5, randomly determining an initial parent population; s6, completing chromosome gene crossing and mutation operations on the parent population to form a child population; s7, performing CFD calculation on each individual in the parent population and the child population to obtain six-component aerodynamic force, and substituting the six-component aerodynamic force into the dynamic simulation model; s8, substituting the key overall indexes of the simulation model into a fitness function, and screening out a new population with the best performance as a parent of the next generation; and S9, repeating the steps S6-S8 until the evolution end condition is met. The invention can solve the problem of non-continuous strong coupling global optimization of the pneumatic appearance optimization of the rotating missile rotating speed characteristic.
Description
Technical Field
The invention belongs to the general technical field of missiles, and relates to a pneumatic optimization method for rotating speed characteristics of a rotating missile.
Background
The rotary missile is a key and main force device in the field of short-range/terminal air defense, currently, the rotary missile as a low-cost high-efficiency missile plays an important role in an air defense weapon system, and the research object is a typical canard pneumatic layout rotary missile which is detected by a head antenna and driven by a fixed tail wing to roll. The optimization of the pneumatic appearance of the missile is a very important link in the missile development stage, particularly the scheme development stage, because with the gradual deepening of the detailed design of the missile, the condition that the allowance is insufficient or even the requirement of the top layer can not be met appears in part of tactical technical indexes. For the design of a rotating missile, the rotating speed characteristic of the missile is an important technical index, the rotating missile realizes the maneuvering in two directions of pitching and yawing controlled by a pair of control surfaces through the self high-speed rotation, the rotating speed is high, the design of a guidance control system is not facilitated, the rotating speed is low, and the period equivalent aerodynamic force cannot be realized, so that the aerodynamic shape needs to be continuously optimized and improved in an iteration mode, and the rotating speed characteristic of the missile is expected to reach an ideal state.
The problem of the pneumatic optimization of the rotating speed characteristic is a nonlinear and strong coupling, even a non-continuous multidisciplinary cross optimization problem of mathematics, pneumatics, mechanics and the like, and belongs to an NP-hard (non-deterministic polynomial) problem, namely a non-deterministic polynomial problem. Considering that flow field coupling of space and time exists between aerodynamic shapes, the independent modification of the shape of a certain aerodynamic component may bring unexpected results to the rotating speed, for example, the reduction of the area of a rolling driving tail wing can reduce rolling damping and improve the rotating speed, but simultaneously brings about the reduction of the driving torque of the tail wing and the reduction of the rotating speed, the comprehensive result of the rotation is unpredictable, and more importantly, the modification of a certain component may bring adverse effects to other overall performance indexes. In fact, the pneumatic optimization of the rotating speed characteristic is a multi-component combined optimization process. The problem is that the solution space is discontinuous, and the solution neighborhood is difficult to express, so that an accurate solution does not exist in the academic world. The existing traditional optimization algorithm comprises a steepest gradient descent method and a Newton iteration method, although the iteration convergence rate is high, the traditional optimization algorithm cannot be suitable for searching for an irreducible and discontinuous system, and the difficulty that the system falls into a local optimal solution rather than a global optimal solution exists; the existing method also comprises the step of carrying out multi-scheme comparison and selection on the pneumatic optimization target by utilizing expert knowledge, and the method has the advantages that the improved pneumatic appearance can be obtained in a short time, but the trial and error mode is very dependent on the engineering experience of experts, and the optimal pneumatic appearance is difficult to find accurately.
Disclosure of Invention
The invention aims to solve the problems that: in the aspect of pneumatic optimization of the rotating speed characteristic of the rotating missile, the global optimal pneumatic shape cannot be obtained only by means of the existing expert knowledge or the traditional optimization algorithm, and in order to solve the problems, the invention provides a pneumatic optimization method of the rotating speed characteristic of the rotating missile.
The technical scheme adopted by the invention is as follows: a pneumatic optimization method for rotating speed characteristics of a rotating missile comprises the following steps:
s1, determining parameters of a genetic algorithm; the parameters comprise a population size M value, an evolution stopping algebra G, a cross probability Pc and a variation probability Pm.
S2, determining the characteristic size of the aerodynamic shape influencing the roll driving torque and the damping torque, and arranging the characteristic size to be used as a chromosome combination of a genetic algorithm;
aerodynamic profile features that affect roll drive torque and damping torque include:
the length L of a head antenna of the missile, the length-to-fineness ratio eta of an ellipsoid of the antenna, the Form of a rolling driving aerodynamic surface of a tail airfoil, a deflection angle D, the characteristic length L and the width W of the driving aerodynamic surface;
the profile of any aerodynamic profile is described by chromosome Ω:
Ω＝{l,η,Form,D,L,W}；
s3, determining the pneumatic appearance characteristic size as a gene fragment, and setting the feasible range of the gene fragment;
s4, determining a fitness function; the fitness function is as follows:
wherein omega is a chromosome corresponding to a certain individual in the population, vmaxIs the maximum flight speed v obtained by dynamics simulation0Optimizing the maximum flying speed of the front missile; rmaxIs the maximum effective range, R, obtained through dynamics simulation0To optimize the maximum effective range of the front missile; n ismaxFor maximum overload capability obtained by dynamic simulation, n0To optimize the maximum overload capacity of the pre-missile, (x)cp-xcg)minFor simulation by dynamicsThe minimum static stability margin, x, under the maximum overload rudder deflection angle is obtainedcpTo optimize the core pressure, x, of the missilecgTo optimize the center of gravity of the missile, (x)cp0-xcg0)minFor optimizing the minimum static stability margin, x, under the maximum overload rudder deflection angle of the pilot missile cruise segmentcp0To optimize the core pressure, x, of the pre-missilecg0To optimize the center of gravity of the missile before use;
is the mean rotating speed of the missile obtained by dynamics simulation, F0Is the natural frequency of the projectile body; lambda [ alpha ]ω,λv,λR,λn,λzRespectively corresponding weight coefficients of each item, satisfying lambdaω+λv+λR+λn+λzAbs () is an absolute value function; whether cone motion occurs is represented by conc, 1 is represented, and 0 is taken out;
s5, randomly determining an initial parent population according to the chromosome combination requirement in S2 and the feasible range of the gene fragment determined in S3;
s6, according to the chromosome combination requirement in S2 and the feasible range of the gene fragment determined in S3, completing chromosome gene crossing and mutation operations on the parent population to form a child population;
s7, performing CFD calculation on each individual in the parent population and the child population to obtain six-component aerodynamic force, and substituting the six-component aerodynamic force into the dynamic simulation model;
s8, substituting the overall indexes of the dynamic simulation model into a fitness function, and screening out a new population of M individuals with the minimum objective function value as a parent of the next generation; the overall indexes of the dynamic simulation model comprise rotating speed, range, overload, static stability and conical motion;
and S9, repeating the steps S6-S8, and ending the method when the target fitness function value is not reduced obviously any more or the evolution algebra reaches the set evolution stopping algebra G.
Compared with the prior art, the invention has the advantages that:
(1) compared with the traditional optimization methods such as a Newton method and the like, the method adopts a genetic algorithm in a modern optimization algorithm, can solve the problem of discontinuous strong coupling global optimum of the pneumatic appearance optimization of the rotating missile rotating speed characteristic, and approaches a theoretical optimum solution rather than a local optimum solution;
(2) the method skillfully establishes association with pneumatic components (the characteristic sizes of a head antenna and a rolling tail wing) related to the rotating speed characteristic of the rotating missile, saves the computer computation of a genetic algorithm, and ensures that the rotating speed of the rotating missile is matched with the theoretical expected rotating speed by setting a specific fitness function;
(3) the method for optimizing the rotating speed aerodynamic shape of the rotating missile does not depend on expert experience, and industrial beginners can easily master and obtain an expected optimized shape.
Drawings
FIG. 1 is a block flow diagram of the optimization process of the method of the present invention.
FIG. 2 is a graph showing the comparison between the aerodynamic profile determined by conventional engineering experience and the rotational speed of the aerodynamic profile provided by the present invention.
FIG. 3 is a flow field display diagram of a high-precision CFD calculation according to an embodiment of the present invention.
Fig. 4 is a graph showing the variation of population objective function values with evolution generations in the embodiment of the present invention.
Detailed Description
The spirit and substance of the present invention will be further explained with reference to the drawings and examples.
As shown in fig. 1, the pneumatic optimization method for the rotational speed characteristic of the rotating missile provided by the embodiment of the invention comprises the following steps:
firstly, determining parameters of a genetic algorithm;
the larger the set population size M value is, the more the optimal population can be evolved in a short time, but because of the limitation of the computing capability of a computer, the heavier computation amount is brought by the huge population quantity, so that M can be selected to be 20, namely 20 initial population quantities are generated, and under the condition that the initial population is good, the quantity of the scale can be quickly converged to the global optimal solution.
The larger the value of the evolution stopping algebra G is, the better the value is theoretically, and after 25 generations of evolution is carried out, the population can better complete the optimal solution convergence.
The cross probability Pc can be 1 to ensure the full evolution of the population;
the variation probability Pm is 0.2, and generally, the probability of variation occurrence is small, but the probability is an important guarantee condition that the population evolution process can approach the global optimal solution.
And step two, determining the characteristic size of the pneumatic appearance influencing the rolling driving torque and the damping torque, and arranging the characteristic size to be used as a chromosome combination of a genetic algorithm.
As can be seen from the high-accuracy CFD calculation flow field of fig. 3, for a rotating missile, the roll drive flight is subject to the head component space vortices, and thus the aerodynamic profile features that affect the roll drive torque and damping torque include:
there are the length L of the head antenna, the antenna ellipsoid slenderness ratio η, and the roll drive aerodynamic surface Form, deflection angle D, drive aerodynamic surface characteristic length L and width W of the tail airfoil in the optimization space.
In combination with the above mentioned optimized and modified chromosome genes, the encoding rule of the chromosome can be defined as follows, and the shape of any aerodynamic shape can be described by the chromosome Ω, and Ω contains all the 6 gene information defining all the details of the aerodynamic shape of the rotation speed characteristics:
Ω＝{l,η,Form,D,L,W}
and step three, determining the characteristic size as a gene segment, and setting a reasonable feasible range of the characteristic size.
The reasonable value range of the gene segment has very important significance on the convergence rate of the genetic algorithm, so that the good value range of the gene segment avoids unnecessary search ranges, and the method is an important guarantee for the rapidity and the accuracy of the algorithm. Therefore, the value range of the gene fragment on the chromosome is reasonably framed by fully using the existing engineering experience and engineering research conclusion.
And step four, determining a fitness function.
The population fitness function is used for measuring the degree of population individuals adapting to the objective function, although the optimized object is mainly the rotating speed, the overall performance indexes of missiles such as speed, range, overload, static stability, conical motion and the like are not expected to be reduced, so that the performance reduction except the rotating speed can bring punishment to the fitness function, and the original other overall performance indexes are prevented from being damaged in the optimizing process of the genetic algorithm. It is contemplated that the population fitness function may take the form:
omega in the above formula is a chromosome corresponding to a certain individual in the population, vmaxIs the maximum flight speed v obtained by dynamics simulation0Optimizing the maximum flying speed of the front missile; rmaxIs the maximum effective range, R, obtained through dynamics simulation0To optimize the maximum effective range of the front missile; n ismaxFor maximum overload capability obtained by dynamic simulation, n0To optimize the maximum overload capacity of the pre-missile, (x)cp-xcg)minIs the minimum static stability margin, x, under the maximum overload rudder deflection angle obtained by dynamics simulationcpTo optimize the core pressure, x, of the missilecgTo optimize the center of gravity of the missile, (x)cp0-xcg0)minFor optimizing the minimum static stability margin, x, under the maximum overload rudder deflection angle of the pilot missile cruise segmentcp0To optimize the core pressure, x, of the pre-missilecg0To optimize the center of gravity of the missile before use;
is the mean rotating speed of the missile obtained by dynamics simulation, F0Is the natural frequency of the projectile, λω,λv,λR,λn,λzRespectively corresponding weight coefficients of each item, satisfying lambdaω+λv+λR+λn+λzWith 1, abs () is the absolute value function, conc, representing whether or not a cone motion occurs, 1, and 0 otherwise. A smaller fitness function value indicates a closer approach to the ideal aerodynamic profile.
And step five, randomly determining an initial parent population with a certain scale according to the chromosome combination requirement determined in the step two and the range of the gene fragment determined in the step three.
And (4) according to the gene fragment range determined in the step three, randomly determining an initial population with good pneumatic performance. In order to ensure the diversity of the genes of the initial population, random gene segments can be determined according to reasonable gene ranges to form a random chromosome. Assuming that the range of a gene is [ a, b ], a random gene segment can be formed by c ═ a + (b-a) × rand (), random numbers can be randomly generated from the range of [0,1], and so on, and M random individuals can be obtained. The range of the value of the gene meets the requirement of the range of the gene fragment, and the gene arrangement needs to meet the requirement of chromosome combination (the arrangement is performed in the step two).
And step six, finishing chromosome gene crossing and mutation operations according to the chromosome combination requirements and the range of the gene segments to form a progeny population.
After the parent population exists, the process of forming filial generations through natural mating can be simulated, and the process is essentially the cross and variation of dyeing. Different from paired chromosome crossing of natural organisms, the crossing of chromosomes can be properly changed in the actual pneumatic optimization process, namely, crossing points of two parents to the chromosomes are randomly selected according to the set crossing probability Pc, and then chromosomes after the crossing points are crossed with each other. Either a single point crossover or a multiple point crossover may be selected. And all the offspring individuals need to complete the variation operation of the gene segments at different positions according to the variation probability Pm, the value range of the varied gene meets the requirement of the range of the gene segments, and the gene arrangement needs to meet the requirement of chromosome combination (the arrangement is shown in the step two).
And seventhly, performing high-precision CFD calculation on each individual in the parent population and the offspring population to obtain six-component aerodynamic force, and substituting the six-component aerodynamic force into the dynamic simulation model.
In the previous step, a process of parent and offspring propagation is completed, and in the step, the determined offspring (except for the initial population, the parent is a selected population left by the previous generation evolution, and CDF and dynamic simulation of the parent are completed) is required to complete conventional CFD calculation work such as structure modeling, pneumatic grid drawing, flow field calculation, six-component extraction and the like on the pneumatic appearance. After the CFD calculation is completed to the aerial pneumatic six-component mapping relation, the new filial generation pneumatic model is brought into the rotating missile dynamics simulation analysis platform software, and the concerned missile overall performance indexes such as speed, range, overload, static stability, conical motion, rotating speed and the like are obtained through calculation.
And step eight, substituting the general indexes of the simulation model such as rotating speed, range, overload, static stability, conical motion and the like into the fitness function, and screening out M individuals with the minimum objective function value as the parent of the next generation.
And (3) adopting a deterministic selection strategy, namely selecting M individuals with the minimum objective function value from the parent population and the offspring population, and evolving to the next generation, so that the excellent characteristics of the parent can be kept.
And step nine, repeating the step six to the step eight until the evolution end condition is met.
According to the framework of genetic algorithm, the target fitness function value of the population gradually converges to a smaller value along with the increase of the evolution algebra, and the optimization algorithm is generally finished when the target fitness function value is not obviously reduced any more or the evolution algebra reaches a set evolution stopping algebra G. Fig. 4 is a graph showing the variation of the population objective function value with the evolution algebra.
Fig. 2 is a comparison graph of the rotation speed of the aerodynamic profile (Tail4, Gurney3, Gurney5) determined by the traditional engineering experience and the rotation speed of the aerodynamic profile (Gurney4) provided by the invention, and it can be seen from the graph that the rotation speed of the missile cruising segment provided by the traditional engineering method is either very low (lowest less than 5) or very high (more than 15), while the aerodynamic profile provided by the invention is farthest from the missile revolving frequency by three times on the premise that the rotation speed does not exceed 15, and is a very ideal rotation speed optimization profile.
Although the present invention has been described with reference to the preferred embodiments, it is not intended to limit the present invention, and those skilled in the art can make variations and modifications of the present invention without departing from the spirit and scope of the present invention by using the methods and technical contents disclosed above.
The present invention has not been described in detail, partly as is known to the person skilled in the art.
Claims (3)
1. A pneumatic optimization method for rotating speed characteristics of a rotating missile is characterized by comprising the following steps:
s1, determining parameters of a genetic algorithm;
s2, determining the characteristic size of the aerodynamic shape influencing the roll driving torque and the damping torque, and arranging the characteristic size to be used as a chromosome combination of a genetic algorithm;
at S2, the aerodynamic profile characteristics affecting roll drive torque and damping torque include:
the length L of a head antenna of the missile, the length-to-fineness ratio eta of an ellipsoid of the antenna, the Form of a rolling driving aerodynamic surface of a tail airfoil, a deflection angle D, the characteristic length L and the width W of the driving aerodynamic surface;
the profile of any aerodynamic profile is described by chromosome Ω:
Ω＝{l,η,Form,D,L,W}；
s3, determining the pneumatic appearance characteristic size as a gene fragment, and setting the feasible range of the gene fragment;
s4, determining a fitness function;
in S4, the fitness function is:
wherein omega is a chromosome corresponding to a certain individual in the population, vmaxIs the maximum flight speed v obtained by dynamics simulation0Optimizing the maximum flying speed of the front missile; rmaxIs the maximum effective range, R, obtained through dynamics simulation0To optimize the best of the former missileA large effective range; n ismaxFor maximum overload capability obtained by dynamic simulation, n0To optimize the maximum overload capacity of the pre-missile, (x)cp-xcg)minIs the minimum static stability margin, x, under the maximum overload rudder deflection angle obtained by dynamics simulationcpTo optimize the core pressure, x, of the missilecgTo optimize the center of gravity of the missile, (x)cp0-xcg0)minFor optimizing the minimum static stability margin, x, under the maximum overload rudder deflection angle of the pilot missile cruise segmentcp0To optimize the core pressure, x, of the pre-missilecg0To optimize the center of gravity of the missile before use;
is the mean rotating speed of the missile obtained by dynamics simulation, F0Is the natural frequency of the projectile body; lambda [ alpha ]ω,λv,λR,λn,λzRespectively corresponding weight coefficients of each item, satisfying lambdaω+λv+λR+λn+λzAbs () is an absolute value function; whether cone motion occurs is represented by conc, 1 is represented, and 0 is taken out;
s5, randomly determining an initial parent population according to the chromosome combination requirement in S2 and the feasible range of the gene fragment determined in S3;
s6, according to the chromosome combination requirement in S2 and the feasible range of the gene fragment determined in S3, completing chromosome gene crossing and mutation operations on the parent population to form a child population;
s7, performing CFD calculation on each individual in the parent population and the child population to obtain six-component aerodynamic force, and substituting the six-component aerodynamic force into the dynamic simulation model;
s8, substituting the overall indexes of the dynamic simulation model into a fitness function, and screening out a new population of M individuals with the minimum objective function value as a parent of the next generation;
and S9, repeating the steps S6-S8, and ending the method when the target fitness function value is not reduced obviously any more or the evolution algebra reaches the set evolution stopping algebra G.
2. The pneumatic optimization method for rotational velocity characteristics of rotating missiles as claimed in claim 1, wherein the parameters of the genetic algorithm determined in S1 include population size M, evolution stopping algebra G, cross probability Pc, and variation probability Pm.
3. The method of claim 1, wherein the general indicators of the dynamical simulation model in step S8 include rotation speed, range, overload, static stability, and cone motion.
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