Robust model predictive control method for air docking and separating uniform pipe of aircraft

Abstract

The multi-body combined aircraft can be quickly butted in the air and flexibly separated and recombined according to task requirements and flight environments, so that the multi-task requirements of long-endurance flight after aggregation and flexible maneuvering after dispersion are met, and the multi-body combined aircraft is widely concerned. However, in the wingtip docking and separating process of a multi-body combined aircraft, the attitude and trajectory of the aircraft in the docking and separating process are affected by wingtip vortex interference, and a closed-loop system is likely to be unstable. At present, a robust flight control method for the docking and separation process of a multi-body combined aircraft cannot realize control plane instruction and aircraft thrust optimization control at the same time and meet the multi-constraint and high-disturbance-rejection control requirements. According to the aircraft air docking and separating uniform tube robust model prediction control method, robust optimization control in the docking and separating process of a multi-body combined type aircraft can be achieved under wingtip eddy current interference, and the safety of the docking and separating process of the multi-body combined type aircraft can be improved.

Description

Technical Field

[0001] The invention belongs to the field of multi-fixed-wing aircraft control, and relates to a uniform tube robust model predictive control method for subsonic aircraft aerial docking and separation, which is used to realize robust optimization control of control surfaces and aircraft thrust during the aerial docking and separation process of multiple aircraft. Background Art

[0002] As a new concept aircraft, multi-body combined aircraft can aggregate multiple single-body aircraft through wingtip connection. According to the flight mission requirements, the multi-body combined aircraft can autonomously separate into multiple single-body aircraft, or dock single-body aircraft to form a combined aircraft. This design not only retains the flexibility of single-body aircraft, but also solves the problem that a single aircraft is difficult to meet the multiple requirements of long flight time, long range and maneuverability due to its limited size and weight. Therefore, multi-body combined aircraft has attracted much attention in the field of theoretical and engineering research.

[0003] Considering the existence of wingtip vortex aerodynamic interference during the docking and separation process of the aircraft, the attitude and trajectory of the wingtip of the multi-body aircraft will be seriously affected during the docking and separation process, so it is very necessary to develop a related docking and separation process control method invention. At present, the flight control of the docking and separation process of multi-body combined aircraft basically adopts classical control methods (such as proportional-differential-integral (PID) and linear quadratic regulator (LQR)), but the existing docking and separation process control methods for multi-body aircraft cannot effectively handle the flight state, control surfaces, and aircraft thrust saturation constraints and safe docking area constraints. At the same time, due to the existence of wingtip vortex interference during the docking and separation process of the aircraft, the classical control method cannot guarantee the reliability of the completion of the wingtip docking and separation control task under interference.

[0004] Therefore, in response to the multi-constraint and high anti-disturbance control requirements of the above-mentioned aircraft wingtip docking and separation process, realizing robust optimization control of the rudder and aircraft thrust during the wingtip docking and separation process of a multi-body combined aircraft is one of the current difficulties and urgent problems to be solved. It is necessary to propose a uniform tube robust model predictive control method for aircraft aerial docking and separation. Summary of the invention

[0005] The technical problem solved by the present invention is: to overcome the shortcomings of the prior art and propose a uniform tube robust model predictive control method for aircraft aerial docking and separation, so as to solve the problem that during the wingtip docking and separation process of multiple aircraft, wingtip vortex interference affects the aircraft attitude and trajectory during the docking and separation process, causing system instability, and the problem that the existing control method cannot ensure that multiple complex constraints are satisfied during the wingtip docking and separation process of aircraft.

[0006] The technical solution of the present invention is:

[0007] A robust model predictive control method for uniform pipe separation during aerial docking of aircraft, the steps are as follows:

[0008] (1) Determine a linearized discrete dynamic system model of a constrained fixed-wing sub-aircraft under wingtip vortex interference, wherein the sub-aircraft is a controlled aircraft during the wingtip docking and separation process, and the main aircraft maintains level flight;

[0009] (2) According to the wingtip vortex disturbance variable constraint, calculate the disturbance invariant set with respect to the disturbance variable;

[0010] (3) Calculate the flight state, control surfaces, and tight constraints of the sub-aircraft thrust;

[0011] (4) Considering the wingtip docking process, construct terminal constraints for the wingtip docking safety area between the sub-aircraft and the main aircraft;

[0012] (5) Design a docking robust model predictive control problem with attitude error as the objective function;

[0013] (6) solving the docking robust model predictive control problem to obtain the optimal control surface and aircraft thrust control instructions for the wingtip docking process at the current sampling moment;

[0014] (7) At the next sampling time, repeat step (6) until the docking task is completed;

[0015] (8) Considering the wingtip separation process, a separation robust model predictive control problem with wingtip separation constraints is designed;

[0016] (9) Solve the separation robust model predictive control problem and obtain the optimal control surface and aircraft thrust control instructions for the wingtip separation process at the current sampling moment;

[0017] (10) At the next sampling moment, repeat step (9) until the separation task is completed.

[0018] Furthermore, the linearized discrete dynamic system model of the constrained fixed-wing aircraft under the wingtip vortex interference described in step (1) is specifically:

[0019] The discrete state space equation of the longitudinal fixed-wing aircraft after linearization is:

[0020]

[0021] Where A represents the aircraft system matrix, B represents the aircraft input matrix, Δα k is the angle of attack deviation at time k, Δω k is the pitch angular velocity deviation at time k, ΔV k is the velocity variable of the aircraft at time k, Δδ k is the elevator surface deflection input at time k, ΔT kis the thrust variable of the aircraft at time k, d k is the wingtip vortex disturbance variable of the aircraft at time k; for simplicity, let Δx k =[Δα k Δω k ΔV k ] T represents the state of the aircraft at time k, Δu k =[Δδ k ΔT k ] T is the control input;

[0022] Determine the vehicle state, control surface deflection, vehicle thrust, and wingtip vortex interference constraint set:

[0023] Δx k ∈Θ,Δu k ∈U,d k ∈W

[0024] Where Θ and U are the aircraft state and control input constraint set, respectively, and W is the wingtip vortex interference constraint set.

[0025] Furthermore, in step (2), according to the wingtip vortex disturbance variable constraint, the disturbance invariant set about the disturbance variable is calculated, as follows:

[0026] Step (2a): Set m = 0 and calculate the set

[0027]

[0028] In the formula K is the feedback control gain, Ψ 0 =W;

[0029] Step (2b): If Ψ m+1 =Ψ m If not satisfied, m = m + 1, that is, the value of m increases by 1, and steps (2a) to (2b) are repeated until Ψ m+1 =Ψ m , obtain the interference invariant set Ψ ∞ .

[0030] Furthermore, the specific method of calculating the compressed constraint set of the sub-aircraft flight state, control surface and aircraft thrust in step (3) is as follows:

[0031]

[0032] In the formula They are respectively the vehicle state after compression and the control input constraint set.

[0033] Furthermore, during the wingtip docking process of the sub-aircraft and the main aircraft in step (4), the terminal constraint of the wingtip docking safety area is:

[0034]

[0035] In the formula, Δx k+N|k =[Δα k+N|k Δω k+N|k ΔV k+N|k ] T The k+N-step model predicts the terminal flight state of the sub-aircraft at time k, The reference flight state of the main level-flying aircraft at time k+N, safe It is the terminal constraint of the safe area.

[0036] Furthermore, the docking robust model predictive control problem designed in step (5) with attitude error as the objective function is:

[0037]

[0038] In the formula, is the nominal aircraft dynamics system, where the nominal aircraft dynamics system refers to the aircraft dynamics model without disturbance, is the nominal rudder deflection input, Predict the k+i nominal flight state at time k,

[0039]

[0040] Predict the optimal control surface and vehicle thrust sequence at time k;

[0041] Objective Function Defined as

[0042]

[0043] Where Q a With R a They are respectively the state variable weight matrix and the input variable weight positive definite matrix of the aircraft docking process; is the terminal cost function, where P a is the terminal state weight positive definite matrix of the docking process; is the initial value of the state.

[0044] Furthermore, step (6) solves the docking robust model predictive control problem and obtains the optimal control surface and aircraft thrust control instructions for the wingtip docking process at the current sampling moment:

[0045]

[0046] In the formula Solve the optimal control sequence of the control surface and the aircraft thrust obtained by the robust model predictive control problem in step (5) at time k The first element of .

[0047] Furthermore, at the next sampling moment in step (7), step (6) is repeated until the docking task is completed. The model predictive control problem in step (5) is solved online at each sampling moment to minimize the energy consumption during the docking process between the sub-aircraft and the main aircraft.

[0048] Furthermore, step (8) considers the wingtip separation process and designs the separation robust model predictive control problem with wingtip separation constraints as follows:

[0049]

[0050] Where Ξ d is the terminal constraint of the wingtip separation process, d is the minimum state norm difference between the main aircraft and the sub-aircraft, and the objective function Defined as

[0051]

[0052] Where Q d With R d They are respectively the state variable weight matrix and the input variable weight positive definite matrix of the aircraft separation process; is the terminal cost function, where P d is the positive definite matrix of terminal state weights of the separation process.

[0053] Furthermore, in step (9), the model prediction optimization control problem of the separation stage in step (8) is solved to obtain the optimal control surface and aircraft thrust control instructions of the wingtip separation process at the current sampling moment:

[0054]

[0055] In the formula Solve the optimal control sequence of the control surface by solving the separated robust model predictive control problem in step (8) at time k The first element of .

[0056] Furthermore, at the next sampling moment in step (10), step (9) is repeated until the separation task is completed. The model predictive control problem in step (8) is solved online at each sampling moment to minimize the energy consumption during the separation of the sub-aircraft and the main aircraft.

[0057] The advantages of the present invention compared with the prior art are:

[0058] (1) Compared with the existing classical control methods, the wingtip docking and separation model predictive control method proposed in the present invention can effectively handle the flight state, control surface and aircraft thrust saturation constraints during the docking and separation process. At the same time, according to the wingtip docking and separation objective function design, the control surface operation instructions, aircraft thrust and flight state can be optimized under multiple constraints to provide the optimal control surface and thrust instructions for each sampling moment.

[0059] (2) The robust model predictive control method based on uniform tube proposed in the present invention aims at the lack of a strategy for ensuring the stable control of the flight attitude of the aircraft during the wingtip docking and separation process under the interference of wingtip vortices in the existing control methods. The present invention avoids the constraint violation problem caused by the wingtip vortex disturbance term in the process of solving the wingtip docking and separation optimization problem by constructing a tightened constraint set. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] Figure 1 is a flow chart of the method of the present invention;

[0061] Figure 2 Schematic diagram of the docking process between the main aircraft and the sub-aircraft. DETAILED DESCRIPTION

[0062] Multi-body combined aircraft can perform rapid aerial docking and flexible separation and reorganization according to mission requirements and flight environment, thus meeting multiple mission requirements of long-duration flight after aggregation and flexible maneuverability after dispersion, and thus has attracted widespread attention, such as Figure 2 Shown is a schematic diagram of the docking process between the main aircraft and the sub-aircraft. However, during the docking and separation process of the wingtips of the multi-body combined aircraft, the wingtip vortex interference affects the aircraft attitude and trajectory during the docking and separation process, which can easily cause instability in the closed-loop system. At present, the robust flight control method for the docking and separation process of the multi-body combined aircraft cannot simultaneously realize the control of the rudder instructions and the aircraft thrust optimization and meet the requirements of multi-constraint and high anti-disturbance control. The present invention proposes a uniform tube robust model predictive control method for aircraft aerial docking and separation. The method can realize robust optimization control in the docking and separation process of the multi-body combined aircraft under the interference of wingtip vortices, which helps to improve the safety of the docking and separation process of the main aircraft and the sub-aircraft.

[0063] like Figure 1 As shown, the present invention designs a uniform tube robust model predictive control method for aircraft aerial docking and separation, which realizes robust optimization control in the docking and separation process of a multi-body combined aircraft under the interference of wingtip vortexes, thereby improving the safety of the docking and separation process between the main aircraft and the sub-aircraft.

[0064] The specific process of the present invention is as follows:

[0065] (1) A linearized discrete dynamic system model of a constrained fixed-wing sub-aircraft under wingtip vortex interference is given (the sub-aircraft is the controlled aircraft during the wingtip docking and separation process, and the main aircraft maintains level flight).

[0066]

[0067] Where A represents the aircraft system matrix, B represents the aircraft input matrix, Δα k is the angle of attack deviation at time k, Δω k is the pitch angular velocity deviation at time k, ΔV k is the velocity variable of the aircraft at time k, Δδ k is the elevator surface deflection input at time k, ΔT k is the thrust variable of the aircraft at time k, d k is the wingtip vortex disturbance variable of the aircraft at time k; for simplicity, let Δx k =[Δα k Δω k ΔV k ] T represents the state of the aircraft at time k, Δu k =[Δδ k ΔT k ] T is the control input;

[0068] Determine the vehicle state, control surface deflection, vehicle thrust, and wingtip vortex interference constraint set:

[0069] Δx k ∈Θ,Δu k ∈U,d k ∈W

[0070] Where Θ and U are the aircraft state and control input constraint set, respectively, and W is the wingtip vortex interference constraint set.

[0071] The optimization control method of the present invention is aimed at the longitudinal dynamics model of a subsonic fixed-wing aircraft. The dynamics model in step (1) is a linearized discrete state space model of the longitudinal fixed-wing aircraft, and the longitudinal dynamics model ignores the yaw motion of the aircraft. The system matrices A and B of different configurations in the linearized model can be obtained by taking the partial derivative of the Jacobian matrix in the equilibrium flight state, and the wingtip vortex interference range can be obtained by aerodynamic modeling.

[0072] (2) According to the wingtip vortex disturbance variable constraints, calculate the disturbance invariant set with respect to the disturbance variable.

[0073] The purpose of calculating the disturbance invariant set is to determine the maximum impact of the accumulation of disturbance variables on the longitudinal dynamics model of the aircraft, and to prevent the constraints of each variable from being violated due to the existence of disturbance variables. The specific steps are as follows:

[0074] Step (2a): Set m = 0 and calculate the set

[0075]

[0076] In the formula K is the feedback control gain, Ψ 0 =W;

[0077] Calculate Ψ m The error system is constructed by the actual dynamic model of the disturbed aircraft (the model in step (1)) and the nominal dynamic model ignoring the disturbance variables (the models in steps (5) and (8)).

[0078]

[0079] The flight state error

[0080] Step (2b): If Ψ m+1 =Ψ m If not satisfied, m = m + 1, that is, the value of m increases by 1, and steps (2a) to (2b) are repeated until Ψ m+1 =Ψ m , obtain the interference invariant set Ψ ∞ .

[0081] (3) Calculate the compact constraint set of the sub-aircraft flight state, control surfaces, and aircraft thrust.

[0082] In order to facilitate the subsequent model predictive control problem in the nominal system design steps (5) and (8), based on the disturbance invariant set Ω calculated in step (2), ∞ , the Pontryagin set subtraction is used to calculate the different flight states, control surface saturation and vehicle thrust constraint sets. The feedback gain K can be obtained by solving the Riccati equation of the linear quadratic regulator (LQR).

[0083] The specific method for calculating the compact constraint set of the sub-aircraft flight state, control surface and aircraft thrust is as follows:

[0084]

[0085] In the formula They are respectively the vehicle state after compression and the control input constraint set.

[0086] (4) Considering the wingtip docking process, construct terminal constraints for the safe area of ​​wingtip docking between the sub-aircraft and the main aircraft.

[0087] In step (4), the terminal constraint of the wingtip docking safety area is constructed as

[0088]

[0089] In the formula, Δx k+N|k =[Δα k+N|k Δω k+N|k ΔV k+N|k ] T The k+N-step model predicts the terminal flight state of the sub-aircraft at time k, The reference flight state of the main level-flying aircraft at time k+N, safe It is the terminal constraint of the safe area.

[0090] The terminal constraint design takes into account the difference in terminal flight state between the main aircraft and the sub-aircraft, and aims to make the deviation between the state variable of the sub-aircraft and the state variable of the main aircraft converge to Ξ safe In this way, the flight status of the main aircraft and the sub-aircraft during the docking process converges within a certain range. Safe docking area Ξ safe It can be designed as a neighborhood containing the origin. If it is designed as an accurate wingtip docking point, it will lead to excessive constraints, sacrificing the performance of the sub-aircraft or causing the model predictive control optimization problem to be unsolvable.

[0091] (5) Design a robust model predictive control problem with attitude error as the objective function;

[0092] The robust model predictive control problem designed in step (5) is for the aircraft dynamics model as the aircraft nominal dynamics system model. The error accumulation effect of the wingtip vortex interference in step (1) on the aircraft flight process has been eliminated by the tightening constraint set design in step (3). Therefore, solving the optimization control problem (5) for the aircraft nominal dynamics system avoids the constraint violation problem caused by the accumulated error of the disturbance variable.

[0093] The docking robust model predictive control problem with attitude error as the objective function is:

[0094]

[0095] In the formula, is the nominal aircraft dynamics system, where the nominal aircraft dynamics system refers to the aircraft dynamics model without disturbance, is the nominal rudder deflection input, Predict the k+i nominal flight state at time k,

[0096]

[0097] Predict the optimal control surface and vehicle thrust sequence at time k;

[0098] Optimizing control objective function Defined as

[0099]

[0100] Where Q a With R a They are respectively the state variable weight matrix and the input variable weight positive definite matrix of the aircraft docking process; is the terminal cost function, where P a is the terminal state weight positive definite matrix of the docking process; is the initial value of the state. The first term in the formula introduces the deviation between the state variable of the sub-aircraft and the state variable of the main aircraft, the purpose of which is to minimize the difference between the two by solving (5). In addition, the weight matrix Q a , R a and P a The weight matrices are all positive definite matrices and can be designed according to the specific docking task requirements.

[0101] (6) Solve the robust model predictive control problem based on the uniform tube and obtain the optimal control surface and vehicle thrust control instructions for the wingtip docking process at the current sampling moment.

[0102] Solve (5) to obtain the optimal control sequence of the control surface and the aircraft thrust The first element in That is, the optimal aircraft control input predicted at time k. That is, the optimal control surface and aircraft thrust control command of the wingtip docking process at the current sampling moment is

[0103]

[0104] In the formula Solve the optimal control sequence of the control surface and the aircraft thrust obtained by the robust model predictive control problem in step (5) at time k The first element of .

[0105] (7) At the next sampling moment, repeat step (6) until the docking task is completed.

[0106] Repeating (5) can obtain the optimal control surface and aircraft thrust command at the next moment, so that the energy consumption of the sub-aircraft and the main aircraft is minimized during the docking process.

[0107] (8) Considering the wingtip separation process, a robust model predictive control problem with wingtip separation constraints is designed.

[0108] The robust model predictive control problem designed in step (8) is the same as that in step (5). It is still aimed at the nominal dynamic system model of the aircraft. The constraint violation problem caused by the influence of the wingtip vortex accumulation error is solved by tightening the constraint set design in step (3). The weight matrix Q in the objective function d , R d and P dThe weight matrices are all positive definite matrices and can be designed according to the specific separation task requirements.

[0109] Considering the wingtip separation process, the separation robust model predictive control problem with wingtip separation constraint is designed as follows:

[0110]

[0111] Where Ξ d is the terminal constraint of the wingtip separation process, d is the minimum state norm difference between the main aircraft and the sub-aircraft,

[0112] Different from the docking process model predictive control problem in (5), the wingtip separation constraint is introduced when designing the wingtip separation process model predictive control problem. There is a deviation in the angle of attack, pitch rate and speed (flight state) between the two aircraft. In addition, the objective function design in step (8) does not need to optimize the deviation between the state variables of the sub-aircraft and the main aircraft. The terminal constraint Ξ d It is designed to include the neighborhood of the origin to ensure the convergence of the longitudinal flight state bias after separation.

[0113] Objective Function Defined as

[0114]

[0115] Where Q d With R d They are respectively the state variable weight matrix and the input variable weight positive definite matrix of the aircraft separation process; is the terminal cost function, where P d is the positive definite matrix of terminal state weights of the separation process.

[0116] (9) Solve the model prediction optimization control problem of the separation stage and obtain the optimal control surface and aircraft thrust control instructions for the wingtip separation process at the current sampling moment.

[0117] The optimal control sequence of the control surface and the aircraft thrust obtained by solving (8) in step (9) is The first element in That is, predicting the optimal aircraft control input at time k.

[0118] That is, the optimal control surface and aircraft thrust control command for the wingtip separation process at the current sampling moment is

[0119]

[0120] In the formula Solve the optimal control sequence of the control surface by solving the separated robust model predictive control problem in step (8) at time k The first element of .

[0121] (10) At the next sampling moment, repeat step (9) until the separation task is completed.

[0122] Repeating (8) can obtain the optimal control surface and aircraft thrust command at the next moment, so that the energy consumption during the separation of the sub-aircraft and the main aircraft is minimized.

[0123] The contents not described in detail in the specification of the present invention belong to the common knowledge of those skilled in the art.

Claims

1. A robust model predictive control method for uniform pipe separation during aerial docking of aircraft, characterized in that Here are the steps: (1) Determine a linearized discrete dynamic system model of a constrained fixed-wing sub-aircraft under wingtip vortex interference, wherein the sub-aircraft is a controlled aircraft during the wingtip docking and separation process, and the main aircraft maintains level flight; (2) According to the wingtip vortex disturbance variable constraint, calculate the disturbance invariant set with respect to the disturbance variable; (3) Calculate the flight state, control surfaces, and tight constraints of the sub-aircraft thrust; (4) Considering the wingtip docking process, construct terminal constraints for the wingtip docking safety area between the sub-aircraft and the main aircraft; (5) Design a docking robust model predictive control problem with attitude error as the objective function; (6) solving the docking robust model predictive control problem to obtain the optimal control surface and aircraft thrust control instructions for the wingtip docking process at the current sampling moment; (7) At the next sampling time, repeat step (6) until the docking task is completed; (8) Considering the wingtip separation process, a separation robust model predictive control problem with wingtip separation constraints is designed; (9) Solve the separation robust model predictive control problem and obtain the optimal control surface and aircraft thrust control instructions for the wingtip separation process at the current sampling moment; (10) At the next sampling moment, repeat step (9) until the separation task is completed.

2. The robust model predictive control method for uniform pipe separation during aerial docking of aircraft according to claim 1 is characterized by: The linearized discrete dynamic system model of the constrained fixed-wing aircraft under the wingtip vortex interference described in step (1) is specifically: The discrete state space equation of the longitudinal fixed-wing aircraft after linearization is: Where A represents the aircraft system matrix, B represents the aircraft input matrix, Δα k is the angle of attack deviation at time k, Δω k is the pitch angular velocity deviation at time k, ΔV k is the velocity variable of the aircraft at time k, Δδ k is the elevator surface deflection input at time k, ΔT k is the thrust variable of the aircraft at time k, d k is the wingtip vortex disturbance variable of the aircraft at time k; for simplicity, let Δx k =[Δα k Δω k ΔV k ] T represents the state of the aircraft at time k, Δu k =[Δδ k ΔT k ] T is the control input; Determine the vehicle state, control surface deflection, vehicle thrust, and wingtip vortex interference constraint set: Δx k ∈Θ,Δu k ∈U,d k ∈W Where Θ and U are the aircraft state and control input constraint set, respectively, and W is the wingtip vortex interference constraint set.

3. The robust model predictive control method for uniform pipe separation during aerial docking of aircraft according to claim 2, characterized in that: In step (2), according to the wingtip vortex disturbance variable constraint, the disturbance invariant set about the disturbance variable is calculated, as follows: Step (2a): Set m = 0 and calculate the set In the formula K is the feedback control gain, Ψ0=W; Step (2b): If Ψ m+1 =Ψ m If not satisfied, m = m + 1, that is, the value of m increases by 1, and steps (2a) to (2b) are repeated until Ψ m+1 =Ψ m , obtain the interference invariant set Ψ ∞ .

4. The method for robust model predictive control of uniform pipe for aircraft aerial docking and separation according to claim 3 is characterized by: Step (3) Calculate the flight state, control surface and aircraft thrust of the sub-aircraft. The specific method of the tightened constraint set is: In the formula They are respectively the vehicle state after compression and the control input constraint set.

5. The method for robust model predictive control of uniform pipe for aerial docking and separation of aircraft according to claim 1, characterized in that: In step (4), during the wingtip docking process between the neutron vehicle and the main vehicle, the terminal constraint of the wingtip docking safety area is: In the formula, Δx k+N|k =[Δα k+N|k Δω k+N|k ΔV k+N|k ] T The k+N-step model predicts the terminal flight state of the sub-aircraft at time k, The reference flight state of the main level-flying aircraft at time k+N, safe It is the terminal constraint of the safe area.

6. The method for robust model predictive control of uniform pipe for aerial docking and separation of aircraft according to claim 5, characterized in that: The docking robust model predictive control problem designed in step (5) with attitude error as the objective function is: In the formula, is the nominal aircraft dynamics system, where the nominal aircraft dynamics system refers to the aircraft dynamics model without disturbance, is the nominal rudder deflection input, Predict the k+i nominal flight state at time k, Predict the optimal control surface and vehicle thrust sequence at time k; Objective Function Defined as Where Q a With R a They are respectively the state variable weight matrix and the input variable weight positive definite matrix of the aircraft docking process; is the terminal cost function, where P a is the terminal state weight positive definite matrix of the docking process; is the initial value of the state.

7. The method for robust model predictive control of uniform pipe for aerial docking and separation of aircraft according to claim 6, characterized in that: Step (6) solves the docking robust model predictive control problem and obtains the optimal control surface and aircraft thrust control instructions for the wingtip docking process at the current sampling moment: In the formula Solve the optimal control sequence of the control surface and the aircraft thrust obtained by the robust model predictive control problem in step (5) at time k The first element of .

8. The method for robust model predictive control of uniform pipe for aerial docking and separation of aircraft according to claim 1, characterized in that: At the next sampling moment in step (7), step (6) is repeated until the docking task is completed. The model predictive control problem in step (5) is solved online at each sampling moment to minimize the energy consumption during the docking process between the sub-aircraft and the main aircraft.

9. The method for robust model predictive control of uniform pipe for aerial docking and separation of aircraft according to claim 1, characterized in that: Step (8) Considering the wingtip separation process, the separation robust model predictive control problem with wingtip separation constraints is designed as Where Ξ d is the terminal constraint of the wingtip separation process, d is the minimum state norm difference between the main aircraft and the sub-aircraft, and the objective function Defined as Where Q d With R d They are respectively the state variable weight matrix and the input variable weight positive definite matrix of the aircraft separation process; is the terminal cost function, where P d is the positive definite matrix of terminal state weights of the separation process.

10. The method for robust model predictive control of uniform pipe for aerial docking and separation of aircraft according to claim 9, characterized in that: In step (9), the model prediction optimization control problem of the separation stage in step (8) is solved to obtain the optimal control surface and aircraft thrust control instructions of the wingtip separation process at the current sampling moment: In the formula Solve the optimal control sequence of the control surface by solving the separated robust model predictive control problem in step (8) at time k The first element of .

11. The method for robust model predictive control of uniform pipe for aerial docking and separation of aircraft according to claim 10, characterized in that: At the next sampling moment in step (10), step (9) is repeated until the separation task is completed. The model predictive control problem in step (8) is solved online at each sampling moment to minimize the energy consumption during the separation process of the sub-aircraft and the main aircraft.

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