Air docking reliable control method based on additive state decomposition

Abstract

The invention relates to an air docking reliable control method based on additive state decomposition, and belongs to the field of flight control. Comprising the steps that a docking aircraft model, a docking device model on a docking aircraft and a docking device model on an aircraft to be docked are constructed, and an air docking comprehensive model is obtained based on the three sorts; carrying out equivalent decomposition on the air docking comprehensive model based on additive state decomposition to obtain an accurate nonlinear subsystem, an accurate linear subsystem and a linear subsystem with interference; designing a first controller based on the precise nonlinear subsystem, designing a second controller based on the precise linear subsystem, and designing a third controller based on the linear subsystem with interference; and adding the three controllers to obtain an air docking reliable controller. According to the method, complex interference and nonlinear characteristics in an air docking system can be effectively processed, high-precision tracking docking control is realized, and the safety, reliability and robustness of air docking are improved.

Description

Technical Field

[0001] The invention relates to a reliable control method for aerial docking based on additive state decomposition, in particular to a safe docking control method for two aircraft in a complex aerial unmanned system, and belongs to the field of flight control. Background Art

[0002] Aerial docking technology is a prerequisite for realizing aerial services such as assembly, recovery, replenishment and maintenance between aircraft. For example, the aerial refueling docking of fighter jets, the automatic docking of spacecraft, the aerial docking and recovery of drones, and the fixed-point landing docking of aircraft are all specific applications of this technology. These aerial docking technologies are essentially the docking of two aircraft in flight through docking devices such as hoses, hooks or grippers.

[0003] During the aerial docking process, due to environmental interference such as external airflow, the docking device may swing, causing the flight trajectory of the docking aircraft to deviate, or even cause a collision, resulting in docking failure. Secondly, due to the nonlinear characteristics of the system, the control difficulty of robust anti-interference and precise docking increases, which brings great challenges to robust and precise docking in the air. Therefore, the control system during the aerial docking process needs to have extremely strong robust anti-interference capabilities and high-precision docking capabilities. Summary of the invention

[0004] The technical problems to be solved by the present invention are:

[0005] In order to avoid the shortcomings of the prior art, the present invention provides a robust and precise control method based on additive state decomposition, which is used to solve the problems of precise docking, robust anti-interference and system nonlinear characteristics of the aerial docking system.

[0006] In order to solve the above technical problems, the technical solution adopted by the present invention is:

[0007] A reliable control method for aerial docking based on additive state decomposition, characterized by comprising:

[0008] Constructing a docking aircraft model, a docking device model on the docking aircraft, and a docking device model on the aircraft to be docked, and obtaining an aerial docking comprehensive model based on the docking aircraft model, the docking device model on the docking aircraft, and the docking device model on the aircraft to be docked;

[0009] Based on additive state decomposition, the aerial docking integrated model is equivalently decomposed to obtain an accurate nonlinear subsystem, an accurate linear subsystem and a linear subsystem with interference;

[0010] Designing a first controller based on the precise nonlinear subsystem, designing a second controller based on the precise linear subsystem, and designing a third controller based on the linear subsystem with interference;

[0011] Based on the addition of the first controller, the second controller and the third controller, a reliable controller for air docking is obtained.

[0012] A further technical solution of the present invention: the integrated model of aerial docking is specifically:

[0013]

[0014] in, It is the status of the air docking system. is the docking device system status on the aircraft to be docked, is the docking aircraft system status; the system output is The control input is is the system matrix,

[0015] is the docking device system matrix on the aircraft to be docked, To dock the aircraft system matrix; is the input matrix, where It is the input matrix of the docking aircraft system; is the output matrix, where is the output matrix of the docking device system on the aircraft to be docked, Output matrix for docking aircraft system; represents the nonlinearity in the mid-air docking process, where is the input matrix of the docking device system on the aircraft to be docked, and the nonlinear term is a nonlinear function vector, p d -p p is the position difference between the two docking devices; is the external and internal interference to the docking system, d represents the relative distance between the docking vehicle and the docking device on it, and x0 is the initial state of the air docking system.

[0016] A further technical solution of the present invention is to perform equivalent decomposition on the aerial docking integrated model based on additive state decomposition to obtain a nonlinear subsystem, a precise linear subsystem and a linear subsystem with interference; comprising:

[0017] Additively decomposing the aerial docking integrated model into a linear subsystem and an accurate nonlinear subsystem;

[0018] The linear subsystem:

[0019]

[0020] Among them, x p is the state of the linear subsystem, and the system output is y p , the control input is u p , r is the expected input trajectory, φ(r) is a known quantity that can be calculated through a nonlinear relationship, is the external and internal disturbances to the docking system, and the initial state is x0;

[0021] The exact nonlinear subsystem:

[0022]

[0023] Among them, x s is the state of the nonlinear subsystem, and the system output is y s , the control input is u s , the initial state is 0, and the state satisfies x=x p +x s ,y=y p +y s ;

[0024] Additively decomposing the linear subsystem into an exact linear subsystem and a linear subsystem with interference;

[0025] The precise linear subsystem:

[0026]

[0027] Among them, x pp is the state of the exact linear subsystem, and the system output is y pp , the control input is u pp ;

[0028] The linear subsystem with interference:

[0029]

[0030] Among them, x ps is the state of the exact linear subsystem, and the system output is y ps , the control input is u ps , state x p =x pp +x ps ,y p =y pp +y ps .

[0031] A further technical solution of the present invention is to design a first controller based on the precise nonlinear subsystem, specifically:

[0032] The Lyapunov method is used to stabilize the precise nonlinear subsystem. The first controller designed is

[0033]

[0034] in, represents the inverse matrix of the docking vehicle system control matrix, and the state x of the nonlinear subsystem s The component x of the docking vehicle system state in the nonlinear subsystem r,s and the component x of the docking device system state on the docking aircraft in the nonlinear subsystem d,s The state consists of two parts: Represents x r,s The transpose of Represents x d,s ; Substitute the expected trajectory r into the nonlinear function φ0(·) to obtain φ0(r).

[0035] A further technical solution of the present invention is to design a second control based on the precise linear subsystem, specifically:

[0036] Iterative learning control is used to perform docking control on the precise linear subsystem. The docking goal is to design a second controller u pp =[u pp,T ,u pp,a ,u pp,e ,u pp,r ] T Make the docking position error zero, the docking speed error zero or keep within a threshold, where u pp,T ,u pp,a ,u pp,e ,u pp,r They are respectively the aircraft throttle, aileron deflection angle, elevator deflection angle and control surface deflection angle components in the precise linear subsystem.

[0037] A further technical solution of the present invention is to design a third controller based on the linear subsystem with interference, specifically:

[0038] The interference rejection control is performed on the linear subsystem with interference by using the ADRC, and the third controller is designed: ps =[u ps,T ,u ps,a ,u ps,e ,u ps,r ] T , where u ps,T 、u ps,a 、u ps,e 、u ps,rThey are respectively the aircraft throttle, aileron deflection angle, elevator deflection angle and control surface deflection angle components in the linear subsystem with interference.

[0039] A computer system, characterized in that it comprises: one or more processors, and a computer-readable storage medium for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors implement the above-mentioned method.

[0040] A computer-readable storage medium, characterized in that it stores computer-executable instructions, which are used to implement the above method when executed.

[0041] A computer program product, characterized by comprising computer executable instructions, wherein the instructions are used to implement the above method when executed.

[0042] The beneficial effects of the present invention are:

[0043] The robust and precise control method based on additive state decomposition provided by the present invention has the following advantages compared with the prior art:

[0044] (1) The present invention establishes multiple subsystem equivalent models of the control-oriented aircraft air docking system through model transformation. The model processing method is conducive to simplifying the subsequent controller design.

[0045] (2) The present invention designs controllers for the three subsystems and obtains the original system controller by summing them up. The proposed robust and precise control strategy for aircraft air docking can effectively handle the complex interference and nonlinear characteristics in the air docking system, and realize high-precision tracking docking control, thereby improving the safety, reliability and robustness of air docking. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] The drawings are only for the purpose of illustrating particular embodiments and are not to be considered limiting of the present invention. Like reference symbols denote like components throughout the drawings.

[0047] Figure 1 It is the design block diagram of the active disturbance rejection controller in the docking aircraft.

[0048] Figure 2 It is a closed-loop block diagram of a reliable controller for air docking based on additive decomposition.

[0049] Figure 3 It is a flow chart of the reliable control method of aerial docking based on additive state decomposition of the present invention. DETAILED DESCRIPTION

[0050] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention. In addition, the technical features involved in the various embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other.

[0051] The present invention provides a reliable control method for aerial docking based on additive state decomposition, by decomposing the aerial docking system into multiple subsystems of the same order, so that the additive sum system of these subsystems is equivalent to the original aerial docking system. Specifically, the original system with interference, uncertainty and nonlinearity is decomposed into three subsystems: an accurate nonlinear system, an accurate linear system, and a linear system that takes into account the interference and uncertainty in the system. For the three decomposed subsystems, the present invention adopts the following control strategies: applying the Lyapunov method to the nonlinear system to realize the compensation of the nonlinearity of the system; applying iterative learning control to the accurate linear system to realize docking control; applying the self-disturbance rejection controller to the linear system with interference and uncertainty to suppress interference. By adding the three subcontrollers, the controller of the original aerial docking system can be obtained. The method can effectively deal with the complex interference and nonlinear characteristics in the aerial docking system, and realize high-precision docking control. The method is fast and effective, and has high reliability and safety.

[0052] This is achieved through the following steps:

[0053] (a) Establishing a comprehensive model for air docking

[0054] A docking aircraft model, a docking device model on the docking aircraft and a docking device model on the aircraft to be docked are constructed, and a comprehensive aerial docking model is obtained by organizing these three models.

[0055] First, the docking aircraft model is as follows

[0056]

[0057] in, is the docking aircraft system status, the system output is The control input is This is the system matrix after the system is stabilized. is the input matrix, is the output matrix, f a Indicates the interference to the docked aircraft.

[0058] Secondly, the docking device model on the docking aircraft is as follows:

[0059] y p =yr +Δ p / r (2)

[0060] Among them, y p It indicates the position and speed of the docking device on the docking aircraft. r is the output information of the docking vehicle, Δ p / r It is information such as the relative position or relative speed between the docking aircraft and the docking device on it.

[0061] Again, the docking device model on the aircraft to be docked is as follows:

[0062]

[0063] in, is the docking device system status on the aircraft to be docked; the system output is The model has nonlinear terms is a nonlinear function vector, p d -p p is the position difference between the two docking devices; is the system matrix, is the input matrix, is the output matrix, f d Indicates interference with the docking device.

[0064] Finally, the aerial docking comprehensive model is obtained by using the docking aircraft model (1), the docking device model on the docking aircraft (2), and the docking device model on the aircraft to be docked (3):

[0065]

[0066] in, is the air docking system status, the system output is The control input is is the system matrix, is the input matrix, is the output matrix, represents the nonlinearity in the docking process, is the external and internal interference to the docking system, d represents the relative distance between the docking vehicle and the docking device on it, and x0 is the initial state of the system.

[0067] (b) Equivalent decomposition of the comprehensive docking model

[0068] Based on additive state decomposition, the equivalent model of three subsystems of the control-oriented aircraft air docking system is established. The specific steps are as follows:

[0069] In the first step, the air docking integrated model (4) is additively decomposed into a linear subsystem (5) and a nonlinear subsystem (6). The linear system (5) is written as

[0070]

[0071] Among them, x p is the state of the linear subsystem, and the system output is y p , the control input is u p , r is the expected input trajectory, φ(r) is a known quantity that can be calculated through a nonlinear relationship, is the external and internal disturbance of the docking system, and the initial state is x0. The nonlinear system (6) is written as

[0072]

[0073] Among them, x s is the state of the nonlinear subsystem, and the system output is y s , the control input is u s , the initial state is 0, and the state satisfies x=x p +x s ,y=y p +y s .

[0074] In the second step, the linear system (5) is further decomposed into an exact linear subsystem (7) and a linear subsystem with interference (8). The exact linear system (7) is written as:

[0075]

[0076] Among them, x pp is the state of the exact linear subsystem, and the system output is y pp , the control input is u pp The disturbed linear system (8) is written as:

[0077]

[0078] Among them, x ps is the state of the exact linear subsystem, and the system output is y ps , the control input is u ps , state x p =x pp +x ps ,y p =y pp +y ps .

[0079] (c) Docking controller design

[0080] The controllers of the three equivalent subsystems after decomposition are designed using Lyapunov method, terminal iterative learning control and active disturbance rejection control respectively. Finally, the sum of these three controllers is the controller of the air integrated docking system.

[0081] In the first step, the Lyapunov method is used to stabilize the precise nonlinear system (6). The designed controller is:

[0082]

[0083] The second step is to use iterative learning control to control the precise linear system (7). The docking goal is to design a controller u pp =[u pp,T ,u pp,a ,u pp,e ,u pp,r ] T Make the docking position error zero, the docking speed error zero or keep within a threshold, where u pp,T ,u pp,a ,u pp,e ,u pp,r It is the aircraft throttle, aileron deflection angle, elevator deflection angle and rudder deflection angle.

[0084] Terminal iterative learning control is used to solve the docking control problem, then model (7) can be rewritten as the following control-oriented model:

[0085]

[0086] Where t∈[0,T] is time, and the iteration period T=t end -t start , t start ,t end is the start and end time of docking, is the number of iterations, x 0,k is the initial state value, the expected terminal output y d (T) is known. The controller is designed as

[0087] u k (t) = U b (t)q k (2)

[0088] in, is the control input basis function, is the controller parameter. The controller parameter update rate is

[0089] q k =q k-1 +Le k-1 (T) (3)

[0090] in, is a constant parameter matrix. It is the terminal docking error.

[0091] The third step is to use the anti-disturbance controller to perform interference suppression control on the linear system with interference (8). The corresponding control channel structure is as follows: Figure 1 As shown, the control channel is divided into three control channels: north direction, east direction and height. As a disturbance, each state x is ps,i Construct a first-order ADRC. The following takes the first ADRC in the north channel as an example to describe it.

[0092] The north channel contains disturbances Expanded to a new state variable x2, the new system after expansion is

[0093]

[0094] in, As the perturbation observation, a linear extended state observer is established for the above extended system

[0095]

[0096] Among them, e is the state estimation error, b0 is the state input gain, l1, l2 are observer parameters. Perform simple proportional control on this first-order system:

[0097]

[0098] Among them, ω c is the controller bandwidth parameter. Similarly, x ps =[x ps,1 x ps,2 …x ps,n ] T For each state x ps,i Design a first-order active disturbance rejection controller, and finally Figure 1 As shown, the total control output of the three channels can be obtained: throttle, aileron deflection angle, elevator deflection angle, and rudder deflection angle. The final controller design is

[0099] u ps =[u ps,T ,u ps,a ,u ps,e ,u ps,r ] T (16)

[0100] The fourth step is Figure 2 As shown in the figure, the three subsystem controllers designed are summed to obtain the robust and precise docking controller in the air:

[0101] u=u s +u pp +u ps (17)

[0102] In order to enable those skilled in the art to better understand the present invention, the present invention is described in detail below in conjunction with specific embodiments.

[0103] Here, the docking control of hose-drogue aerial refueling is taken as an example to design a reliable aerial docking controller based on additive decomposition.

[0104] (a) Consider an aerial refueling docking model of the form (4)

[0105]

[0106] The state vector is [x d ,x r ] T ,x r =[x,h,θ,v,α,q,y,ψ,φ,β,p,r] T , where x d It shows the ten states of the cone sleeve; x r Where x represents the north position, h represents the altitude, θ represents the pitch angle, v represents the velocity, α represents the angle of attack, q represents the pitch angular velocity, y represents the east position, ψ represents the yaw angle, φ represents the roll angle, β represents the sideslip angle, p represents the roll angular velocity, and r represents the yaw angular velocity; the system output [p d -p p v d -v p ] T Indicates the position difference and speed difference of the cone tube and cone sleeve; u r =[δ T ,δ a ,δ e ,δ r ] T is the control input; is the system matrix, [0 B r ] T is the input matrix, [C d -C r ] is the output matrix; the function φ(y) is a known nonlinear term related to the output state y; represents the disturbance and uncertainty in the system; d is the relative position of the cone and the receiving machine; x0 is the initial state.

[0107]

[0108]

[0109] (b) In accordance with Figure 3 As shown in the figure, the first step is to decompose the aerial refueling docking model into three subsystems based on additive decomposition:

[0110] The first exact nonlinear system

[0111]

[0112] The second exact linear system

[0113]

[0114] The third linear system with disturbance and uncertainty

[0115]

[0116] In the second step, the controller (9) is used to design a controller for the exact nonlinear system (23), using Lyapunov nonlinear stabilization control. The designed controller is

[0117]

[0118] In the third step, the controller (11) is used to design a controller for the precise nonlinear system (24). Iterative learning tracking docking control is adopted, and the designed controller is:

[0119] u pp =u k (t) = U b (t)q k (27)

[0120] The controller parameter update rate is

[0121]

[0122] In the fourth step, the controller (16) is used to design a controller for the accurate nonlinear system (25), using the auto-disturbance rejection control, such as Figure 1 As shown, the linear extended state observer (14) parameters l1=2, l2=1 on each first-order ADRC, and the bandwidth parameter ω of the proportional controller (15) c =0.01, then the designed controller is

[0123] u ps =[u ps,T ,u ps,a ,u ps,e ,u ps,r ] T (29)

[0124] Step 5: Figure 2 As shown in Figure 1, the final designed robust and precise controller for aerial refueling docking is (17), that is:

[0125]

[0126] Parts of the present invention that are not described in detail belong to common knowledge among those skilled in the art.

[0127] The above description is only a specific implementation mode of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can easily think of various equivalent modifications or substitutions within the technical scope disclosed in the present invention, and these modifications or substitutions should be included in the protection scope of the present invention.

Claims

1. A reliable control method for aerial docking based on additive state decomposition, characterized in that: include: Constructing a docking aircraft model, a docking device model on the docking aircraft, and a docking device model on the aircraft to be docked, and obtaining an aerial docking comprehensive model based on the docking aircraft model, the docking device model on the docking aircraft, and the docking device model on the aircraft to be docked; Based on additive state decomposition, the aerial docking integrated model is equivalently decomposed to obtain an accurate nonlinear subsystem, an accurate linear subsystem and a linear subsystem with interference; Designing a first controller based on the precise nonlinear subsystem, designing a second controller based on the precise linear subsystem, and designing a third controller based on the linear subsystem with interference; Based on the addition of the first controller, the second controller and the third controller, a reliable controller for air docking is obtained.

2. According to claim 1, a reliable control method for aerial docking based on additive state decomposition is characterized in that: The comprehensive model of aerial docking is specifically as follows: in, It is the status of the air docking system. is the docking device system status on the aircraft to be docked, is the docking aircraft system status; the system output is The control input is is the system matrix, is the docking device system matrix on the aircraft to be docked, To dock the aircraft system matrix; is the input matrix, where It is the input matrix of the docking aircraft system; is the output matrix, where is the output matrix of the docking device system on the aircraft to be docked, The output matrix of the docking aircraft system; represents the nonlinearity in the mid-air docking process, where is the input matrix of the docking device system on the aircraft to be docked, and the nonlinear term is a nonlinear function vector, p d -p p is the position difference between the two docking devices; is the external and internal interference to the docking system, d represents the relative distance between the docking vehicle and the docking device on it, and x0 is the initial state of the air docking system.

3. According to claim 2, a reliable control method for aerial docking based on additive state decomposition is characterized in that: Based on additive state decomposition, the aerial docking integrated model is equivalently decomposed to obtain a nonlinear subsystem, an accurate linear subsystem and a linear subsystem with interference; including: Additively decomposing the aerial docking integrated model into a linear subsystem and an accurate nonlinear subsystem; The linear subsystem: Among them, x p is the state of the linear subsystem, and the system output is y p , the control input is u p , r is the expected input trajectory, φ(r) is a known quantity that can be calculated through a nonlinear relationship, is the external and internal disturbances to the docking system, and the initial state is x0; The exact nonlinear subsystem: Among them, x s is the state of the nonlinear subsystem, and the system output is y s , the control input is u s , the initial state is 0, and the state satisfies x=x p +x s ,y=y p +y s ; Additively decomposing the linear subsystem into an exact linear subsystem and a linear subsystem with interference; The precise linear subsystem: Among them, x pp is the state of the exact linear subsystem, and the system output is y pp , the control input is u pp ; The linear subsystem with interference: Among them, x ps is the state of the exact linear subsystem, and the system output is y ps , the control input is u ps , state x p =x pp +x ps ,y p =y pp +y ps .

4. According to claim 3, a reliable control method for aerial docking based on additive state decomposition is characterized in that: Design a first controller based on the precise nonlinear subsystem, specifically: The Lyapunov method is used to stabilize the precise nonlinear subsystem. The first controller designed is Among them, B r -1 represents the inverse matrix of the docking vehicle system control matrix, and the state x of the nonlinear subsystem s The component x of the docking vehicle system state in the nonlinear subsystem r,s and the component x of the docking device system state on the docking aircraft in the nonlinear subsystem d,s The state consists of two parts: Represents x r,s The transpose of Represents x d,s ; Substitute the expected trajectory r into the nonlinear function φ0(·) to obtain φ0(r).

5. According to claim 1, a reliable control method for aerial docking based on additive state decomposition is characterized in that: The second control is designed based on the precise linear subsystem, specifically: Iterative learning control is used to perform docking control on the precise linear subsystem. The docking goal is to design a second controller u pp =[u pp,T ,u pp,a ,u pp,e ,u pp,r ] T Make the docking position error zero, the docking speed error zero or keep within a threshold, where u pp,T ,u pp,a ,u pp,e ,u pp,r They are respectively the aircraft throttle, aileron deflection angle, elevator deflection angle and control surface deflection angle components in the precise linear subsystem.

6. The reliable control method for aerial docking based on additive state decomposition according to claim 1, characterized in that: The third controller is designed based on the linear subsystem with interference, specifically: The interference rejection control is performed on the linear subsystem with interference by using the ADRC, and the third controller is designed: ps =[u ps,T ,u ps,a ,u ps,e ,u ps,r ] T , where u ps,T 、u ps,a 、u ps,e 、u ps,r They are respectively the aircraft throttle, aileron deflection angle, elevator deflection angle and control surface deflection angle components in the linear subsystem with interference.

7. A computer system, characterized in that include: One or more processors, and a computer-readable storage medium for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors are enabled to implement the method of claim 1.

8. A computer-readable storage medium, characterized in that Computer executable instructions are stored, and when the instructions are executed, they are used to implement the method of claim 1.

9. A computer program product, characterized in that The invention comprises computer executable instructions, which are used to implement the method of claim 1 when being executed.

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