A robust model predictive control method for uniform tubes during aerial docking and separation of aircraft

Abstract

Multi-body modular aircraft (MMOs) have attracted widespread attention due to their ability to rapidly dock in mid-air and flexibly separate and reassemble according to mission requirements and flight environment, thus meeting multiple mission needs such as long endurance flight after aggregation and flexible maneuverability after dispersion. However, during the docking and separation process, MMOs face wingtip vortex interference, which affects the aircraft's attitude and trajectory, easily causing instability in the closed-loop system. Current robust flight control methods for the docking and separation process of MMOs cannot simultaneously achieve control surface command and aircraft thrust optimization control while meeting the requirements of multi-constraint and high disturbance rejection control. This invention proposes a robust model predictive control method for uniform tubes during in-air docking and separation of aircraft. This method can achieve robust optimization control during the docking and separation process of MMOs under wingtip vortex interference, which helps to improve the safety of the docking and separation process of MMOs.

Description

Technical Field

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

[0002] Multi-body modular aircraft, as a novel concept, can aggregate multiple individual aircraft via wingtip connections. Depending on mission requirements, a multi-body modular aircraft can autonomously separate into multiple individual aircraft or dock them together to form a modular aircraft. This design retains the flexibility of individual aircraft while addressing the challenge of achieving long endurance, long range, and high maneuverability due to the limited size and weight of a single aircraft. Therefore, multi-body modular aircraft have attracted significant attention in both theoretical and engineering research.

[0003] Considering the presence of wingtip vortex aerodynamic interference during the docking and separation process, the attitude and trajectory of multi-body aircraft are severely affected. Therefore, it is essential to develop relevant control methods for the docking and separation process. Currently, flight control for the docking and separation process of multi-body combined aircraft mainly adopts classical control methods (such as proportional-derivative-integral (PID) and linear quadratic regulators (LQR)). However, existing control methods for the docking and separation process of multi-body aircraft cannot effectively handle flight state, control surfaces, thrust saturation constraints, and safe docking area constraints. Furthermore, due to the presence of wingtip vortex interference during the docking and separation process, classical control methods cannot guarantee the reliability of wingtip docking and separation control tasks under interference.

[0004] Therefore, in response to the multi-constraint and high disturbance rejection control requirements of the wingtip docking and separation process of the aforementioned aircraft, achieving robust optimization control of the control surfaces and aircraft thrust during the wingtip docking and separation process of multi-body combined aircraft is one of the current difficulties and urgent problems to be solved. It is necessary to propose a robust model predictive control method for uniform tube in-flight docking and separation of aircraft. Summary of the Invention

[0005] The technical problem solved by this invention is to overcome the shortcomings of the prior art and propose a robust model predictive control method for uniform tube in-flight docking and separation of aircraft. This method addresses the problem of wingtip vortex interference affecting the attitude and trajectory of aircraft during docking and separation, causing system instability, and the problem that existing control methods cannot guarantee that various complex constraints are satisfied during the docking and separation of aircraft wingtip.

[0006] The technical solution of this invention is:

[0007] A robust predictive control method for a uniform tube in mid-air docking and separation of an aircraft, comprising the following steps:

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

[0009] (2) Calculate the disturbance invariant set of the disturbance variables based on the wingtip vortex disturbance variable constraints;

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

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

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

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

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

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

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

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

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

[0019] The discrete state-space equations of the longitudinally fixed-wing aircraft after linearization are as follows:

[0020]

[0021] In the formula, A represents the aircraft system matrix, B represents the aircraft input matrix, and Δα k Let Δω be the angle of attack bias at time k. k Let ΔV be the pitch angular velocity deviator at time k. k Let Δδ be the velocity variable of the aircraft at time k. k The elevator surface bias input at time k is ΔT. kLet d be the thrust variable of the aircraft at time k. k Let Δx be the wingtip vortex disturbance variable at time k; for simplicity, let Δx be... k =[Δα k Δω k ΔV k ] T Δu represents the state of the spacecraft at time k. k =[Δδ k ΔT k ] T For control input;

[0022] Determine the set of constraints for aircraft state, control surface deflection, aircraft thrust, and wingtip vortex disturbance:

[0023] Δx k ∈Θ,Δu k ∈U,d k ∈W

[0024] In the formula, Θ and U are the aircraft state and control input constraint sets, respectively, and W is the wingtip vortex disturbance constraint set.

[0025] Furthermore, in step (2), based on the constraints of the wingtip vortex disturbance variables, the disturbance-invariant set of the disturbance variables is calculated, as follows:

[0026] Step (2a): Let m = 0, calculate the set

[0027]

[0028] In the formula K is the feedback control gain, Ψ0 = 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 for calculating the compact constraint set of the sub-aircraft's flight state, control surfaces, and thrust in step (3) is as follows:

[0031]

[0032] In the formula These represent the control input constraint set for the compressed state of the aircraft.

[0033] Furthermore, during the docking process between the sub-vehicle and the main vehicle's wingtip, the terminal constraint of the wingtip docking safety zone is as follows:

[0034]

[0035] In the formula, Δx k+N|k =[Δα k+N|k Δω k+N|k ΔV k+N|k ] T The model predicts the terminal flight state of the sub-aircraft at time k in k+N steps. For the docking reference flight state of the level flight main aircraft at time k+N, Ξ safe For terminal constraints in the safe zone.

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

[0037]

[0038] In the formula, The nominal aircraft dynamics system refers to the aircraft dynamics model without disturbances. For nominal control surface offset input, Predict the nominal flight state at time k+i.

[0039]

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

[0041] objective function Defined as

[0042]

[0043] In the formula Q a With R a These are the weight matrix of the state variables and the positive definite weight matrix of the input variables during the docking process of the aircraft, respectively. Let P be the terminal cost function, where P is the terminal cost function. a This is a positive definite matrix representing the terminal state weights during the docking process; This is the initial state value.

[0044] Furthermore, step (6) solves the docking robust model predictive control problem to obtain the optimal control surface and aircraft thrust control commands for the wingtip docking process at the current sampling time.

[0045]

[0046] In the formula The optimal control sequence of control surfaces and aircraft thrust obtained by solving step (5) of the docking robust model predictive control problem at time k is given. The first element.

[0047] Furthermore, in step (7), at the next sampling time, step (6) is repeated until the docking task is completed. The requirement is: at each sampling time, the model predictive control problem in step (5) is solved online 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 a separation robust model predictive control problem with wingtip separation constraints.

[0049]

[0050] In the formula Ξ d For the terminal constraint of the wingtip separation process, d is the minimum state norm difference between the master aircraft and the slave aircraft during separation, and the objective function is... Defined as

[0051]

[0052] In the formula Q d With R d These are the weight matrix of the state variables and the positive definite weight matrix of the input variables during the aircraft separation process, respectively. Let P be the terminal cost function, where P is the terminal cost function. d This is the positive definite weight matrix of the terminal state in 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 commands for the wingtip separation process at the current sampling moment.

[0054]

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

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

[0057] The advantages of this invention compared to the prior art are:

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

[0059] (2) The robust model predictive control method based on uniform tubes proposed in this invention addresses the lack of strategies in existing control methods to ensure stable flight attitude control of the aircraft during wingtip docking and separation under wingtip vortex disturbances. This invention avoids constraint violations caused by wingtip vortex disturbance terms during the solution of the wingtip docking and separation optimization problem by constructing a compact constraint set. Attached Figure Description

[0060] Figure 1 This is a flowchart of the method of the present invention;

[0061] Figure 2 A schematic diagram of the docking process between the main aircraft and the sub-aircraft. Detailed Implementation

[0062] Multi-body modular aircraft can rapidly dock in mid-air and flexibly separate and recombine according to mission requirements and flight environment, thus meeting the multiple mission requirements of long-endurance flight after aggregation and flexible maneuverability after dispersion. Therefore, they have attracted widespread attention. Figure 2 The diagram shows the docking process between the main aircraft and the sub-aircraft. However, during the docking and separation process at the wingtip, multi-body combined aircraft face wingtip vortex interference, which affects the aircraft's attitude and trajectory, easily causing instability in the closed-loop system. Current robust flight control methods for the docking and separation process of multi-body combined aircraft cannot simultaneously achieve control surface commands and aircraft thrust optimization control while meeting the requirements of multi-constraint and high disturbance rejection control. This invention proposes a robust model predictive control method using a uniform tube for in-flight docking and separation. This method can achieve robust optimization control during the docking and separation process of multi-body combined aircraft under wingtip vortex interference, helping to improve the safety of the docking and separation process between the main aircraft and the sub-aircraft.

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

[0064] The specific design process of this invention is as follows:

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

[0066]

[0067] In the formula, A represents the aircraft system matrix, B represents the aircraft input matrix, and Δα k Let Δω be the angle of attack bias at time k. k Let ΔV be the pitch angular velocity deviator at time k. k Let Δδ be the velocity variable of the aircraft at time k. k The elevator surface bias input at time k is ΔT. k Let d be the thrust variable of the aircraft at time k. k Let Δx be the wingtip vortex disturbance variable at time k; for simplicity, let Δx be... k =[Δα k Δω k ΔV k ] T Δu represents the state of the spacecraft at time k. k =[Δδ k ΔT k ] T For control input;

[0068] Determine the set of constraints for aircraft state, control surface deflection, aircraft thrust, and wingtip vortex disturbance:

[0069] Δx k ∈Θ,Δu k ∈U,d k ∈W

[0070] In the formula, Θ and U are the aircraft state and control input constraint sets, respectively, and W is the wingtip vortex disturbance constraint set.

[0071] The optimized control method of this invention is designed for the longitudinal dynamics model of a subsonic fixed-wing aircraft. In step (1), the dynamics model 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) Calculate the disturbance invariant set of the disturbance variables based on the wingtip vortex disturbance variable constraints.

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

[0074] Step (2a): Let m = 0, calculate the set

[0075]

[0076] In the formula K is the feedback control gain, Ψ0 = 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 that ignores the disturbance variables (the models in steps (5) and (8)).

[0078]

[0079] Flight state error in the formula

[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 set of tight constraints for the flight state, control surfaces, and thrust of the sub-aircraft.

[0082] To facilitate the subsequent model predictive control problem in steps (5) and (8) of the nominal system design, the disturbance invariant set Ω calculated in step (2) is used as a basis. ∞ The Pontryagin set subtraction method is used to calculate the compact sets under different flight conditions, control surface saturation, and aircraft thrust constraints. The feedback gain K can be obtained by solving the Riccati equation for the linear quadratic regulator (LQR).

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

[0084]

[0085] In the formula These represent the control input constraint set for the compressed state of the aircraft.

[0086] (4) Considering the wingtip docking process, construct the terminal constraint of the safe area for 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 follows:

[0088]

[0089] In the formula, Δx k+N|k =[Δα k+N|k Δω k+N|k ΔV k+N|k ] T The model predicts the terminal flight state of the sub-aircraft at time k in k+N steps. For the docking reference flight state of the level flight main aircraft at time k+N, Ξ safe For terminal constraints in the safe zone.

[0090] The terminal constraint design takes into account the differences in terminal flight states between the master and slave aircraft, aiming to ensure that the deviation between the slave aircraft's state and the master aircraft's state variables converges to Ξ. safe This allows the flight status of the main aircraft and the sub-aircraft to converge within a certain range during the docking process. Safe docking zone Ξ safe It can be designed as a neighborhood containing the origin. However, if it is designed as an exact 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 become 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 nominal dynamic system model of the aircraft. The error accumulation effect of the wingtip vortex disturbance on the flight process in step (1) has been eliminated by the compact constraint set design in step (3). Therefore, solving the optimization control problem (5) for the nominal dynamic system of the aircraft avoids the constraint violation problem caused by the accumulation error of the disturbance variables.

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

[0094]

[0095] In the formula, The nominal aircraft dynamics system refers to the aircraft dynamics model without disturbances. For nominal control surface offset input, Predict the nominal flight state at time k+i.

[0096]

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

[0098] Optimize the control objective function Defined as

[0099]

[0100] In the formula Q a With R a These are the weight matrix of the state variables and the positive definite weight matrix of the input variables during the docking process of the aircraft, respectively. Let P be the terminal cost function, where P is the terminal cost function. a This is a positive definite matrix representing the terminal state weights during the docking process; The initial state is given. The first term in the equation introduces the deviation between the state variables of the sub-aircraft and the main aircraft, with the aim of minimizing the difference between the two by solving (5). Additionally, the weight matrix Q in the equation... a R a and P a All weight matrices are positive definite matrices and can be designed according to the specific requirements of the docking task.

[0101] (6) Solve the robust model predictive control problem based on uniform tubes to obtain the optimal control surface and aircraft thrust control commands for the wingtip docking process at the current sampling time.

[0102] Solving (5) yields the optimal control sequence for the control surfaces and the aircraft thrust. The first element This refers to the predicted optimal aircraft control input at time k. Specifically, the optimal control surface and aircraft thrust control commands for the wingtip docking process at the current sampling time are:

[0103]

[0104] In the formula The optimal control sequence of control surfaces and aircraft thrust obtained by solving step (5) of the docking robust model predictive control problem at time k is given. The first element.

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

[0106] By repeating the solution in step (5), the optimal control surface and aircraft thrust commands for the next moment can be obtained, thus minimizing energy consumption during the docking process between the sub-aircraft and the main aircraft.

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

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

[0109] Considering the wingtip separation process, design a robust model predictive control problem with wingtip separation constraints.

[0110]

[0111] In the formula Ξ d For the terminal constraint of the wingtip separation process, d is the minimum state norm difference between the master aircraft and the slave aircraft during separation.

[0112] Unlike the model predictive control problem of the docking process in (5), when designing the model predictive control problem of the wingtip separation process, wingtip separation constraints are introduced. This results in deviations in angle of attack, pitch rate, and velocity (flight state) between the two aircraft. Furthermore, the objective function design in step (8) does not require optimization of the deviation between the sub-aircraft state and the master aircraft state variables; the terminal constraint Ξ d The design incorporates the neighborhood of the origin to ensure the convergence of the longitudinal flight state bias after separation.

[0113] objective function Defined as

[0114]

[0115] In the formula Q d With R d These are the weight matrix of the state variables and the positive definite weight matrix of the input variables during the aircraft separation process, respectively. Let P be the terminal cost function, where P is the terminal cost function. d This is the positive definite weight matrix of the terminal state in the separation process.

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

[0117] In step (9), the optimal control sequence of the control surfaces and the aircraft thrust obtained from solution (8) is solved. The first element This means predicting the optimal aircraft control input at time k.

[0118] That is: the optimal control surfaces and aircraft thrust control commands for the wingtip separation process at the current sampling moment are

[0119]

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

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

[0122] By repeatedly solving (8), the optimal control surface and aircraft thrust command for the next moment can be obtained, thus minimizing energy consumption during the separation of the sub-aircraft from the main aircraft.

[0123] The contents not described in detail in this specification are common knowledge to those skilled in the art.

Claims

1. A robust model predictive control method for uniform tube in-flight docking and separation of an aircraft, characterized in that... The steps are as follows: (1) Determine the linearized discrete dynamics system model of a confined fixed-wing sub-aircraft under wingtip vortex interference, wherein the sub-aircraft is the controlled aircraft during the wingtip docking and separation process, and the main aircraft maintains level flight; (2) Calculate the disturbance invariant set of the disturbance variables based on the wingtip vortex disturbance variable constraints; (3) Calculate the set of tight constraints for the flight state, control surfaces, and thrust of the sub-aircraft; (4) Considering the wingtip docking process, construct the terminal constraint of the safe area for wingtip docking between the sub-aircraft and the main aircraft; (5) Design a robust model predictive control problem for docking with attitude error as the objective function; (6) Solve the docking robust model predictive control problem to obtain the optimal control surface and aircraft thrust control commands for the wingtip docking process at the current sampling time; (7) At the next sampling time, repeat step (6) until the docking task is completed; (8) Considering the wingtip separation process, design a separation robust model predictive control problem with wingtip separation constraints; (9) Solve the separation robust model predictive control problem to obtain the optimal control surface and aircraft thrust control commands for the wingtip separation process at the current sampling time; (10) At the next sampling time, repeat step (9) until the separation task is completed.

2. The robust model predictive control method for uniform tube in-flight docking and separation of an aircraft according to claim 1, characterized in that: The linearized discrete dynamics system model of the confined fixed-wing aircraft under wingtip vortex interference described in step (1) is as follows: The discrete state-space equations of the longitudinally fixed-wing aircraft after linearization are as follows: In the formula, A represents the aircraft system matrix, B represents the aircraft input matrix, and Δα k Let Δω be the angle of attack bias at time k. k Let ΔV be the pitch angular velocity deviator at time k. k Let Δδ be the velocity variable of the aircraft at time k. k The elevator surface bias input at time k is ΔT. k Let d be the thrust variable of the aircraft at time k. k Let Δx be the wingtip vortex disturbance variable at time k; for simplicity, let Δx be... k =[Δα k Δω k ΔV k ] T Δu represents the state of the spacecraft at time k. k =[Δδ k ΔT k ] T For control input; Determine the set of constraints for aircraft state, control surface deflection, aircraft thrust, and wingtip vortex disturbance: Δx k ∈Θ,Δu k ∈U,d k ∈W In the formula, Θ and U are the aircraft state and control input constraint sets, respectively, and W is the wingtip vortex disturbance constraint set.

3. The robust model predictive control method for uniform tube in-flight docking and separation of an aircraft according to claim 2, characterized in that: In step (2), based on the constraints of the wingtip vortex disturbance variables, the disturbance invariant set with respect to the disturbance variables is calculated as follows: Step (2a): Let m = 0, 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 robust model predictive control method for uniform tube in-flight docking and separation of an aircraft according to claim 3, characterized in that: Step (3) The specific method for calculating the compact constraint set of the sub-aircraft's flight state, control surfaces, and thrust is as follows: In the formula These represent the control input constraint set for the compressed state of the aircraft.

5. The robust model predictive control method for uniform tube in-flight docking and separation of an aircraft according to claim 1, characterized in that: During the docking process between the neutron spacecraft and the main spacecraft's wingtips in step (4), the terminal constraint of the wingtips docking safety zone is as follows: In the formula, Δx k+N|k =[Δα k+N|k Δω k+N|k ΔV k+N|k ] T The model predicts the terminal flight state of the sub-vehicle at time k using a k+N step prediction method. For the docking reference flight state of the level flight main aircraft at time k+N, Ξ safe For terminal constraints in the safe zone.

6. The robust model predictive control method for uniform tube in-flight docking and separation of an aircraft according to claim 5, characterized in that: In step (5), the docking robust model predictive control problem with attitude error as the objective function is designed as follows: In the formula, The nominal aircraft dynamics system refers to the aircraft dynamics model without disturbances. For nominal control surface offset input, Predict the nominal flight state at time k+i. Predict the optimal control surface and aircraft thrust sequence at time k; Objective function Defined as In the formula Q a With R a These are the weight matrix of the state variables and the positive definite weight matrix of the input variables during the docking process of the aircraft, respectively. Let P be the terminal cost function, where P is the terminal cost function. a This is a positive definite matrix representing the terminal state weights during the docking process; This represents the initial state value.

7. The robust model predictive control method for uniform tube in-flight docking and separation of an aircraft according to claim 6, characterized in that: Step (6) solves the docking robust model predictive control problem to obtain the optimal control surface and aircraft thrust control commands for the wingtip docking process at the current sampling time. In the formula The optimal control sequence of control surfaces and aircraft thrust obtained by solving step (5) of the docking robust model predictive control problem at time k is given. The first element.

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

9. The robust model predictive control method for uniform tube in-flight docking and separation of an aircraft according to claim 1, characterized in that: Step (8) Considering the wingtip separation process, design a robust separation model predictive control problem with wingtip separation constraints. In the formula Ξ d For the terminal constraint of the wingtip separation process, d is the minimum state norm difference between the master aircraft and the slave aircraft during separation, and the objective function is... Defined as In the formula Q d With R d These are the weight matrix of the state variables and the positive definite weight matrix of the input variables during the aircraft separation process, respectively. Let P be the terminal cost function, where P is the terminal cost function. d This is the positive definite weight matrix of the terminal state in the separation process.

10. The robust model predictive control method for uniform tube in-flight docking and separation of an 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 commands for the wingtip separation process at the current sampling time. In the formula Solving the optimal control sequence of the control surface obtained by separating the robust model predictive control problem at time k in step (8) The first element.

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

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