CN114020044A - Flexible unmanned aerial vehicle crosswind-resistant flight control method - Google Patents
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Abstract
The invention discloses a crosswind-resistant flight control method for a flexible unmanned aerial vehicle, which comprises the following steps: s1, establishing a flight dynamics equation of the flexible aircraft; s2, simulating the reaction of the steering engine by adopting a second-order system, and establishing a steering engine model, namely selecting a Von Karman turbulence model and establishing a side wind model; coupling a flight dynamics model containing an elastic mode in a state space form with a steering engine model to obtain a flexible unmanned aerial vehicle flight dynamics model; s3, designing a static output feedback parameter which meets the flight quality requirement and has disturbance suppression capability; and S4, constructing an open loop of a flexible unmanned aerial vehicle flight dynamics high-order system including an elastic mode by using the static output feedback parameters, and designing an outer loop forming controller. The method can obtain gust response of the unmanned aerial vehicle, and provides more accurate basis for anti-crosswind flight control of the flexible unmanned aerial vehicle.
Description
Technical Field
The invention belongs to the technical field of unmanned aerial vehicles, and particularly relates to a crosswind-resistant flight control method for a flexible unmanned aerial vehicle, which is used for flight control of the flexible unmanned aerial vehicle in a crosswind environment.
Background
The unmanned aerial vehicle is an essential important weapon in modern high-tech wars, is a powerful tool for playing the win wars to execute major tasks, and has developed into a hot spot of competitive development of all military and strong countries. In civil fields such as disaster monitoring and emergency response, earth remote sensing, unmanned aerial vehicles are playing an important role. In recent years, a high aspect ratio remote unmanned aerial vehicle and a new energy ultra-long time-of-flight unmanned aerial vehicle have become hot spots of research.
The wing flexibility characteristics of the long-distance unmanned aerial vehicle with the large aspect ratio are obvious, and the structural flexibility of the unmanned aerial vehicle is increased, so that the low-order frequency of the structure is closer to the rigid motion frequency; during air flight, particularly when the aircraft passes over complex terrain environments such as mountainous areas or under severe meteorological conditions, various severe atmospheric turbulence, particularly the influence of transverse crosswind, is often encountered, and the dynamic structural load of the aircraft is increased. Therefore, it is difficult to meet performance requirements using a single dynamical model and goal when designing a control system.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provides a crosswind-resistant flight control method for a flexible unmanned aerial vehicle.
The purpose of the invention is realized by the following technical scheme: a crosswind-resistant flight control method for a flexible unmanned aerial vehicle comprises the following steps:
s1, establishing a flight dynamics equation of the flexible aircraft:
the method comprises the following steps of (1) utilizing small disturbance to assume that the flexible aircraft is linearized near a balance point to obtain a linearized model of a flight dynamics equation of the flexible aircraft as follows:
wherein x is a state quantity, u is an input, and y is an observation output; b is an input matrix; c is an output matrix; the system matrix A is
Wherein A isrIs a system matrix in a rigid body unmanned aerial vehicle flight dynamics model, AeA system matrix in a flight dynamics model of the flexible unmanned aerial vehicle;
s2, simulating the reaction of the steering engine by adopting a second-order system, and establishing a steering engine model, namely selecting a Von Karman turbulence model and establishing a side wind model; coupling a flight dynamics model containing an elastic mode in a state space form with a steering engine model to obtain a flexible unmanned aerial vehicle flight dynamics model;
in step S2, in the process of simulating the steering engine reaction by using the second-order system, the transfer function of the second-order system is as follows:
wherein the subscript d denotes steering engine, Kd，εd，ωndAs steering gear transmission coefficient parameters, Gd(s) is the steering engine transfer function, and s is the laplace transform of the steering engine response time.
Selecting a Von Karman turbulence model, and establishing a crosswind model as follows:
wherein L iswIs the side wind scale, ω is the time frequency, Φww(ω) is the temporal crosswind spectrum, α is the crosswind intensity, σwV is the side wind speed, 1.339.
The method comprises the following steps of coupling a flight dynamics model containing an elastic mode in a state space form with a steering engine model to obtain a flexible unmanned aerial vehicle flight dynamics model:
the method comprises the following steps of coupling a flight dynamics model, a crosswind model and a steering engine model of the flexible unmanned aerial vehicle in a state space form to obtain a state space equation of the flexible unmanned aerial vehicle under the crosswind condition, wherein the state space equation is as follows:
where x is the state quantity, u is the input, and u is [ δ ═ de δa]TD is the crosswind disturbance and y is the observed output. B is an input matrix; c is an output matrix; d is a disturbance matrix related to crosswind; the system matrix A embodies the relationship with each sub-model:
wherein A isfIs a system matrix in a flight dynamics model of a flexible unmanned aerial vehicle, AaIs a system matrix in a crosswind model, AafFor the influence of the crosswind model on the flight dynamics model of the flexible unmanned aerial vehicle, AsSystem matrix being a model of the steering engine, AsfThe influence of the steering engine model on the flight dynamics model of the flexible unmanned aerial vehicle is shown.
S3, designing a static output feedback parameter which meets the flight quality requirement and has disturbance suppression capability according to a rigid equation;
the step S3 includes:
the form of expression of the control quantity u is given
u＝-Ky＝-KCx
K is a static parameter for system stability, and L is made2The gain satisfies a given boundary γ;
the solving step of K is as follows:
1) selecting weighting matrix Q, R, and gain index gamma, and designing L0＝0；
2) Side wind disturbance pattern
For a given gamma, if there is a static output inversionFeeding K stabilizes the system, there is a matrix R, P, L, satisfying:
KC＝R-1(BP+L)；
in each step of iterative solution process, P is obtained by solving Riccati equationn；
By inverting the matrix, the updated L can be obtainedn+1And Kn+1
Kn+1＝R-1(BTPn+Ln)CT(CCT)-1
Ln+1＝RKn+1C-BTPn
When Ln+1-LnE is less than or equal to e, and e is a set error, convergence is achieved, namely K equals to Kn+1
And S4, constructing an open loop of a flexible unmanned aerial vehicle flight dynamics high-order system including an elastic mode by using the static output feedback parameters, and designing an outer loop forming controller.
The step S4 includes:
on the basis of the initial feedback gain K, a pre-compensation link W is selected1And a post-compensation link W2(ii) a Initial W1And W2Predesignated, set epsilonmaxGreater than 0.3, the stability margin epsilon is less than epsilonmax(ii) a Through the calculation of the following formula, when the stability margin requirement is met, the K infinity meeting the requirement is obtained
Wherein I is an identity matrix, G is a steering engine transfer function, and M-1Is obtained by G left coprime decomposition;
since u ═ K ∞ y ═ K ∞ Cx, the input u can be obtained from K ∞, and u includes rudder offset and accelerator;
the deviation of the accelerator and the rudder is output to realize unmanned aerial vehicle control; that is, the output quantity is determined by the unmanned aerial vehicle state quantity x, the output matrix C and the output feedback gain K ∞; and after K infinity is designed, combining the state quantity x of the unmanned aerial vehicle and an output matrix C to obtain an output quantity.
The invention has the beneficial effects that: the method utilizes an average shafting theory to establish the flight dynamics equation of the unmanned aerial vehicle, carries out balancing linearization on the equation under the assumption of small disturbance, establishes the wing elastic motion equation under a modal coordinate based on a modal truncation method, adopts a second-order system to simulate the reaction process of a steering engine, converts the transfer function of the steering engine model into a state space form, couples the flight dynamics model, an atmosphere model and the steering engine model in the state space form, can obtain the gust response of the unmanned aerial vehicle, and provides more accurate basis for the anti-crosswind flight control of the flexible unmanned aerial vehicle.
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FIG. 1 is a schematic diagram of the method of the present invention;
FIG. 2 shows lateral overload frequency responses of a rigid body model and a flexible flight dynamics model in a crosswind environment;
FIG. 3 is a graph of the turbulent power spectral response of crosswind overload with and without control.
Detailed Description
The technical solutions of the present invention are further described in detail below with reference to the accompanying drawings, but the scope of the present invention is not limited to the following.
As shown in fig. 1, a method for controlling crosswind resistance flight of a flexible unmanned aerial vehicle comprises the following steps:
s1, establishing a flight dynamics equation of the flexible aircraft:
the method comprises the following steps of (1) utilizing small disturbance to assume that the flexible aircraft is linearized near a balance point to obtain a linearized model of a flight dynamics equation of the flexible aircraft as follows:
wherein x is a state quantity, u is an input, and y is an observation output; b is an input matrix; c is an output matrix; the system matrix A is
Wherein A isrIs a system matrix in a rigid body unmanned aerial vehicle flight dynamics model, AeA system matrix in a flight dynamics model of the flexible unmanned aerial vehicle;
s2, in the process of simulating the reaction of the steering engine by adopting a second-order system, the transfer function of the second-order system is as follows:
wherein the subscript d denotes steering engine, Kd，εd，ωndAs steering gear transmission coefficient parameters, Gd(s) is the steering engine transfer function; and s is Laplace transformation of the response time of the steering engine.
According to the Von Karman turbulence model, it is first converted into a time spectrum, as follows:
wherein L iswIs the side wind scale, ω is the time frequency, Φww(ω) is the temporal crosswind spectrum, α is the crosswind intensity, σwV is the side wind speed, 1.339.
The method comprises the following steps of coupling a flight dynamics model, a crosswind model and a steering engine model of the flexible unmanned aerial vehicle in a state space form to obtain a state space equation of the flexible unmanned aerial vehicle under the crosswind condition, wherein the state space equation is as follows:
where x is the state quantity, u is the input, and u is [ δ ═ de δa]TD is the crosswind disturbance and y is the observed output. B is an input matrix; c is an output matrix; d is a disturbance matrix related to crosswind; moment of the systemThe array A embodies the relationship with each sub-model:
wherein A isfIs a system matrix in a flight dynamics model of a flexible unmanned aerial vehicle, AaIs a system matrix in a crosswind model, AafFor the influence of the crosswind model on the flight dynamics model of the flexible unmanned aerial vehicle, AsSystem matrix being a model of the steering engine, AsfThe influence of the steering engine model on the flight dynamics model of the flexible unmanned aerial vehicle is shown. Fig. 2 shows lateral overload frequency responses of a rigid body model and a flexible flight dynamics model (a high-order model).
S3, according to the flight dynamics state space equation of the unmanned aerial vehicle, static output feedback is considered
u＝-Ky＝-KCx
K is a static parameter for system stability, and L is made2The gain satisfies a given boundary γ.
The solution steps of the unmanned plane flight dynamics state space equation are as follows:
1) selecting weighting matrix Q, R, and gain index gamma, and designing L0＝0；
2) Side wind disturbance pattern
For a given γ, if there is a static output feedback K that makes the system stable, then there is a matrix R, P, L that satisfies:
KC＝R-1(BP+L)；
in each step of iterative solution process, P is obtained by solving Riccati equationn；
By inverting the matrix, the updated L can be obtainedn+1And Kn+1
Kn+1＝R-1(BTPn+Ln)CT(CCT)-1
Ln+1＝RKn+1C-BTPn
When Ln+1-LnE is less than or equal to e, and e is a set error, convergence is achieved, namely K equals to Kn+1。
S4, constructing an open loop of a flexible unmanned aerial vehicle flight dynamics high-order system comprising an elastic mode by using a static output feedback parameter, and designing an outer loop forming controller:
on the basis of the initial feedback gain K, a pre-compensation link W is selected1And a post-compensation link W2(ii) a Initial W1And W2Predesignated, set epsilonmaxGreater than 0.3, the stability margin epsilon is less than epsilonmax(ii) a Through the calculation of the following formula, when the stability margin requirement is met, the K infinity meeting the requirement is obtained
Wherein I is an identity matrix, G is a steering engine transfer function, and M-1Is obtained by G left coprime decomposition;
since u ═ K ∞ y ═ K ∞ Cx, the input u can be obtained from K ∞, and u includes rudder offset and accelerator;
the deviation of the accelerator and the rudder is output to realize unmanned aerial vehicle control; that is, the output quantity is determined by the unmanned aerial vehicle state quantity x, the output matrix C and the output feedback gain K ∞; and after K infinity is designed, combining the state quantity x of the unmanned aerial vehicle and an output matrix C to obtain an output quantity.
In the embodiment of the present application, the weighting matrices Q, R, and the gain index γ are Q ═ diag (0.15, 0.1, 0.1, 0.05), respectively; r ═ diag (0.01, 0.1); γ is 0.5. Calculating static output feedback gain to obtain corresponding closed loop characteristic values of-1.07 +/-0.947 i, -1.79, -0.616 to meet the stability requirement; fig. 3 shows that the turbulence power spectrum response of crosswind overload when there is control and no control, reflects that the active control system can effectively inhibit crosswind disturbance, and simultaneously has good effect on frequency bands with remarkable elastic movement caused by flexibility.
The above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (6)
1. The utility model provides a flexible unmanned aerial vehicle anti crosswind flight control method which characterized in that: the method comprises the following steps:
s1, establishing a flight dynamics equation of the flexible aircraft:
the method comprises the following steps of (1) utilizing small disturbance to assume that the flexible aircraft is linearized near a balance point to obtain a linearized model of a flight dynamics equation of the flexible aircraft as follows:
wherein x is a state quantity, u is an input, and y is an observation output; b is an input matrix; c is an output matrix; the system matrix A is
Wherein A isrIs a system matrix in a rigid body unmanned aerial vehicle flight dynamics model, AeA system matrix in a flight dynamics model of the flexible unmanned aerial vehicle;
s2, simulating the reaction of the steering engine by adopting a second-order system, and establishing a steering engine model, namely selecting a Von Karman turbulence model and establishing a side wind model; coupling a flight dynamics model containing an elastic mode in a state space form with a steering engine model to obtain a flexible unmanned aerial vehicle flight dynamics model;
s3, designing a static output feedback parameter which meets the flight quality requirement and has disturbance suppression capability;
and S4, constructing an open loop of a flexible unmanned aerial vehicle flight dynamics high-order system including an elastic mode by using the static output feedback parameters, and designing an outer loop forming controller.
2. The method for controlling anti-crosswind flight of the flexible unmanned aerial vehicle according to claim 1, wherein the method comprises the following steps: in step S2, in the process of simulating the steering engine reaction by using the second-order system, the transfer function of the second-order system is as follows:
wherein, Kd，εd，ωndAs steering gear transmission coefficient parameters, Gd(s) is the steering engine transfer function, and s is the laplace transform of the steering engine response time.
3. The method for controlling anti-crosswind flight of the flexible unmanned aerial vehicle according to claim 1, wherein the method comprises the following steps: in the step S2, a Von Karman turbulence model is selected, and the established crosswind model is as follows:
wherein L iswIs the side wind scale, ω is the time frequency, Φww(ω) is the temporal crosswind spectrum, α is the crosswind intensity, σwV is the side wind speed, 1.339.
4. The method for controlling anti-crosswind flight of the flexible unmanned aerial vehicle according to claim 1, wherein the method comprises the following steps: in the step S2, the flight dynamics model in the state space form and the steering engine model are coupled to obtain a flexible unmanned aerial vehicle flight dynamics model, and the process is as follows:
the method comprises the following steps of coupling a flight dynamics model, a crosswind model and a steering engine model of the flexible unmanned aerial vehicle in a state space form to obtain a state space equation of the flexible unmanned aerial vehicle under the crosswind condition, wherein the state space equation is as follows:
where x is the state quantity, u is the input, and u is [ δ ═ de δa]TD is the crosswind disturbance and y is the observed output. B is an input matrix; c is an output matrix; d is a disturbance matrix related to crosswind; the system matrix A embodies the relationship with each sub-model:
wherein A isfIs a system matrix in a flight dynamics model of a flexible unmanned aerial vehicle, AaIs a system matrix in a crosswind model, AafFor the influence of the crosswind model on the flight dynamics model of the flexible unmanned aerial vehicle, AsSystem matrix being a model of the steering engine, AsfThe influence of the steering engine model on the flight dynamics model of the flexible unmanned aerial vehicle is shown.
5. The method for controlling anti-crosswind flight of the flexible unmanned aerial vehicle according to claim 1, wherein the method comprises the following steps: the step S3 includes:
the expression of the control quantity u is given:
u＝-Ky＝-KCx
k is a static parameter for system stability, and L is made2The gain satisfies a given boundary γ;
the solving step of K is as follows:
1) selecting weighting matrix Q, R, and gain index gamma, and designing L0＝0；
2) Side wind disturbance pattern
For a given gamma, if there is a static output feedback K, the system is enabledStable, then there is a matrix R, P, L, satisfying:
KC＝R-1(BP+L)；
in each step of iterative solution process, P is obtained by solving Riccati equationn；
By inverting the matrix, the updated L can be obtainedn+1And Kn+1
Kn+1＝R-1(BTPn+Ln)CT(CCT)-1
Ln+1＝RKn+1C-BTPn
When Ln+1-LnE is less than or equal to e, and e is a set error, convergence is achieved, namely K equals to Kn+1。
6. The method for controlling anti-crosswind flight of the flexible unmanned aerial vehicle according to claim 1, wherein the method comprises the following steps: the step S4 includes:
on the basis of the initial feedback gain K, a pre-compensation link W is selected1And a post-compensation link W2(ii) a Initial W1And W2Predesignated, set epsilonmaxGreater than 0.3, the stability margin epsilon is less than epsilonmax(ii) a Through the calculation of the following formula, when the stability margin requirement is met, the K infinity meeting the requirement is obtained
Wherein I is an identity matrix, G is a steering engine transfer function, and M-1Is obtained by G left coprime decomposition;
since u ═ K ∞ y ═ K ∞ Cx, the input u can be obtained from K ∞, and u includes rudder offset and accelerator;
the deviation of the accelerator and the rudder is output to realize unmanned aerial vehicle control; that is, the output quantity is determined by the unmanned aerial vehicle state quantity x, the output matrix C and the output feedback gain K ∞; and after K infinity is designed, combining the state quantity x of the unmanned aerial vehicle and an output matrix C to obtain an output quantity.
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