A multi-objective optimization control method for on-orbit assembly of large spacecraft

Abstract

The present invention discloses a multi-objective optimization control method for on-orbit assembly of a large spacecraft. The method comprises the following steps: establishing a corresponding state space model based on an orbit-attitude-vibration integrated model of the large spacecraft; determining an orbit-attitude-vibration integrated controller based on the state space model; determining multi-objective optimization constraints according to the operating state of the large spacecraft, and solving the controller based on the multi-objective optimization constraints; applying the solved controller to the orbit-attitude-vibration integrated model, realizing multi-objective optimization control in the on-orbit assembly process of the large spacecraft, and reducing waste of space resources and onboard resources.

Description

Technical Field

[0001] The present invention belongs to the technical field of spacecraft, and in particular relates to a multi-objective optimization control method for on-orbit assembly of large spacecraft. Background Art

[0002] Large spacecraft are important strategic aerospace equipment for future space resource utilization, exploration of cosmic mysteries, and long-term on-orbit residence. They cannot be constructed through a single launch and orbital deployment. They usually require multiple launches and on-orbit assembly for construction. The large scale and configuration changes of large spacecraft during the assembly process make it difficult to accurately know the mass characteristics. The attitude and orbit stability control of large spacecraft is nonlinearly coupled with the vibration of large structures. In the actual space working environment, controller gain perturbation, actuator failure, input limitation or saturation, and input delay will make the orbit-attitude-vibration integrated control problem of large spacecraft more complicated. At the same time, since on-orbit service / assembly is limited by the window, if the orbit-attitude-vibration integrated control cannot be achieved within a limited time, the service window must be reselected, which will inevitably lead to a waste of space resources and seriously affect the on-orbit service life. If the service window is reselected, the on-orbit assembly progress will lag behind, causing the large spacecraft to re-plan the assembly path, further increase the workload of the on-board computer, and cause a waste of on-board resources. The above-mentioned many unfavorable factors make the stable control of large spacecraft under the interaction with the space environment face huge challenges.

[0003] At present, control methods for on-orbit assembly of large spacecraft usually require accurate prior information of mass characteristics at each moment in the on-orbit assembly process of large spacecraft, so it costs a relatively high cost to identify high-precision mass information. Moreover, there are few methods that simultaneously consider and realize the integrated control of attitude, orbit and vibration of large spacecraft. In addition, reliable control methods that take into account adverse factors such as controller gain perturbation, actuator failure, input limitation or saturation, and input lag are not yet mature. In addition, long-term high-quality on-orbit service needs to consider fuel consumption and multi-objective control performance constraints including rapidity and accuracy.

[0004] Therefore, how to achieve integrated multi-objective optimization control of orbit, attitude and vibration during the on-orbit assembly process of large spacecraft is a technical problem that needs to be urgently solved by technical personnel in this field. Summary of the invention

[0005] The purpose of the present invention is to realize the integrated multi-objective optimization control of orbit-attitude-vibration during the on-orbit assembly of large spacecraft, reduce the waste of space resources and on-board resources, and propose a multi-objective optimization control method for on-orbit assembly of large spacecraft.

[0006] The technical solution of the present invention is: a multi-objective optimization control method for on-orbit assembly of large spacecraft, comprising the following steps:

[0007] S1. Establishing a corresponding state space model based on the orbit-attitude-vibration integrated model of the large spacecraft;

[0008] S2. Determine a controller of a track-attitude-vibration integrated model based on the state-space model;

[0009] S3, determining multi-objective optimization constraints according to the operating state of the large spacecraft, and solving the controller based on the multi-objective optimization constraints;

[0010] S4. Applying the solved controller to the orbit-attitude-vibration integrated model.

[0011] Furthermore, the state space model Π is specifically shown in the following formula:

[0012] Π:

[0013] In the formula, t represents time, is the derivative of the controlled state variables including the orbit, attitude and mode of the large spacecraft with respect to time, A is the state matrix obtained after the linearization of the orbit-attitude-vibration integrated dynamic model, ΔA represents the uncertainty matrix caused by modeling errors and inertia unknowns to the state matrix A, x(t) is the controlled state variable including the orbit, attitude and mode of the large spacecraft, B 1 is the control matrix, ΔB 1 Represents the control matrix B composed of modeling error and inertia unknown 1 The disturbance matrix caused by this is u(t), which is the orbit-attitude-vibration integrated controller, B 2 is the interference matrix, ΔB 2 Represents the interference matrix B composed of modeling error and inertia unknown 2 The disturbance matrix caused by the state variable is w(t), w(t) is the total disturbance including external disturbance and actuator failure, y(t) is the measurement output vector, C is the measurement matrix selected according to the actual measurability of the state variables, and v(t) is the measurement error vector.

[0014] Furthermore, the controller u(t) is specifically shown in the following formula:

[0015] u(t)=U(t,λ(u m ,t),D(τ),K,ΔK(t))

[0016] Where t is time, λ(u m ,t) is the input saturation function, u mis the maximum value of the absolute values of the components of the input torque, D(τ) is the input time-delay function, K is the gain matrix of the controller, ΔK(t) is the gain perturbation of the controller, and U is a composite function composed of time t, input saturation function λ(u m ,t), input time-delay function D(τ), controller gain matrix K, and controller gain perturbation ΔK(t).

[0017] Further, the operating states in step S3 include a first state and a second state. The first state is specifically when the large spacecraft is in the on-orbit assembly period or receiving on-orbit services, and the second state is specifically when the large spacecraft is in normal on-orbit operation and becomes unstable due to interference. The multi-objective optimization constraint conditions corresponding to the first state are J 1 , and the multi-objective optimization constraint conditions corresponding to the second state are J 2 . The expressions of the multi-objective optimization constraint conditions are as follows:

[0018]

[0019]

[0020] where t 0 represents the moment when control starts to be applied to the large spacecraft, is the time required to complete the control, where α > 0, β > 0, p > 1, 0 < q < 1 are variables to be optimized, are parameters to be selected, where i = 1, 2, 3, 4; j = 1, 2, and η(t) represents the modal displacement vector of the flexible spacecraft, and η T (t) is the transpose of η(t), represents the derivative of the modal displacement with respect to time, is the transpose of, R 11 is the weight matrix selected when the large spacecraft is in the on-orbit assembly period or receiving on-orbit services to determine the vibration energy consumption, is the stiffness matrix of the flexible spacecraft, t represents time, x(t) is the controlled state variable including the orbit, attitude, and mode of the large spacecraft, and x T (t) is the transpose of x(t), u(t) is the orbit-attitude-vibration integrated controller, and u T (t) is the transpose of u(t), R 12 is the weight matrix selected when the large spacecraft is in the on-orbit assembly period or receiving on-orbit services to determine the total energy consumption, and Q 1 is the weight matrix selected when the large spacecraft is in the on-orbit assembly period or receiving on-orbit services to determine the system stability accuracy, and R21 is the weight matrix for determining the vibration energy consumption when a large spacecraft is in normal orbital operation and is disturbed and unstable. 22 It is the weight matrix that determines the total energy consumption when a large spacecraft is in normal orbital operation and is disturbed and unstable. 2 It is the weight matrix that determines the stability accuracy of the system when a large spacecraft is in normal orbit operation and is disturbed and unstable. d is the differential operation symbol.

[0021] Compared with the prior art, the present invention has the following beneficial effects:

[0022] The present invention establishes a corresponding state-space model based on an orbit-attitude-vibration integrated model of a large spacecraft; determines an orbit-attitude-vibration integrated controller based on the state-space model; determines multi-objective optimization constraints according to the operating state of the large spacecraft, and solves the controller based on the multi-objective optimization constraints; and applies the solved controller to the orbit-attitude-vibration integrated model, thereby realizing multi-objective optimization control during the on-orbit assembly of the large spacecraft and reducing waste of space resources and onboard resources. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 Shown is a flow chart of a multi-objective optimization control method for on-orbit assembly of a large spacecraft provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0024] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0025] like Figure 1 The figure is a flow chart of a multi-objective optimization control method for on-orbit assembly of a large spacecraft proposed in an embodiment of the present application, the method comprising the following steps:

[0026] Step S1, establishing a corresponding state space model based on the orbit-attitude-vibration integrated model of the large spacecraft.

[0027] In the embodiment of the present application, the state space model Π is specifically shown as follows:

[0028] Π:

[0029] In the formula, t represents time, is the derivative of the controlled state variables including the orbit, attitude and mode of the large spacecraft with respect to time, A is the state matrix obtained after the linearization of the orbit-attitude-vibration integrated dynamic model, ΔA represents the uncertainty matrix caused by modeling errors and inertia unknowns to the state matrix A, x(t) is the controlled state variable including the orbit, attitude and mode of the large spacecraft, B 1 is the control matrix, ΔB 1 Represents the control matrix B composed of modeling error and inertia unknown 1 The disturbance matrix caused by this is u(t), which is the orbit-attitude-vibration integrated controller, B 2 is the interference matrix, ΔB 2 Represents the interference matrix B composed of modeling error and inertia unknown 2 The disturbance matrix caused by the state variable is w(t), w(t) is the total disturbance including external disturbance and actuator failure, y(t) is the measurement output vector, C is the measurement matrix selected according to the actual measurability of the state variables, and v(t) is the measurement error vector.

[0030] Specifically, the orbit-attitude-vibration integrated model of a large spacecraft is composed of the orbit-attitude coupling dynamic equations and the attitude-vibration coupling dynamic equations. The orbit-attitude-vibration integrated model of a large spacecraft can be converted into a controllable state space model through linearization and the like, and can then be used in the control design of the present invention.

[0031] Step S2: determining a controller of the orbit-attitude-vibration integrated model based on the state-space model.

[0032] In the embodiment of the present application, the controller u(t) is specifically shown as follows:

[0033] u(t)=U(t,λ(u m ,t),D(τ),K,ΔK(t))

[0034] Where t is time, λ(u m ,t) is the input saturation function, u m is the maximum value of the absolute value of each component of the input torque, D(τ) is the input lag function, K is the gain matrix of the controller, ΔK(t) is the gain perturbation of the controller, and U is the function of time t, input saturation function λ(u m ,t), the input time lag function D(τ), the controller gain matrix K and the controller gain perturbation ΔK(t).

[0035] Specifically, the controller effectively addresses controller gain perturbation, input saturation, and input time delay. Under the limitation of input saturation, it can overcome the existing input time delay and inevitable controller gain perturbation to achieve integrated attitude-orbit-vibration control during the on-orbit assembly of large spacecraft.

[0036] Step S3: Determine the multi-objective optimization constraint conditions according to the operating state of the large spacecraft, and solve the controller based on the multi-objective optimization constraint conditions.

[0037] In the embodiment of the present application, the operating state in step S3 includes a first state and a second state. The first state is specifically when the large spacecraft is in the on-orbit assembly period or receiving on-orbit services, and the second state is specifically when the large spacecraft is in normal on-orbit operation and is disturbed and becomes unstable. The multi-objective optimization constraint condition corresponding to the first state is J 1 and the multi-objective optimization constraint condition corresponding to the second state is J 2 The expression of the multi-objective optimization constraint condition is as follows:

[0038]

[0039]

[0040] where t 0 represents the moment when control starts to be applied to the large spacecraft, is the time required to complete the control, where α > 0, β > 0, p > 1, 0 < q < 1 are variables to be optimized, is a parameter to be selected, where i = 1, 2, 3, 4; j = 1, 2, and η(t) represents the modal displacement vector of the flexible spacecraft, and η T (t) is the transpose of η(t), represents the derivative of the modal displacement with respect to time, is the transpose of, R 11 is a weight matrix for determining the vibration energy consumption selected when the large spacecraft is in the on-orbit assembly period or receiving on-orbit services, is the stiffness matrix of the flexible spacecraft, t represents time, x(t) is the controlled state variable including the orbit, attitude, and mode of the large spacecraft, and x T (t) is the transpose of x(t), u(t) is the integrated orbit-attitude-vibration controller, and u T (t) is the transpose of u(t), R 12 is a weight matrix for determining the total energy consumption selected when the large spacecraft is in the on-orbit assembly period or receiving on-orbit services, and Q 1is the weight matrix that determines the stability accuracy of the system when the large spacecraft is in the on-orbit assembly period or receiving on-orbit service. 21 is the weight matrix for determining the vibration energy consumption when a large spacecraft is in normal orbital operation and is disturbed and unstable. 22 It is the weight matrix that determines the total energy consumption when a large spacecraft is in normal orbital operation and is disturbed and unstable. 2 is the weight matrix that determines the stability accuracy of the system when the large spacecraft is in normal orbital operation and is disturbed and unstable, and d is the differential operator symbol. It should be noted that the above form is only one form of multi-objective optimization constraint conditions.

[0041] The specific process of solving the controller is:

[0042]

[0043] Where V(x(t)) is the Lyapunov function corresponding to the closed-loop system, is the derivative of V(x(t)) with respect to time, V p (x(t)) represents V(x(t)) to the power of p, V q (x(t)) represents V(x(t)) raised to the power of q.

[0044] Step S4: applying the solved controller to the orbit-attitude-vibration integrated model.

[0045] The obtained controller u(t) can be directly substituted into the state space model of the orbit-attitude-vibration integrated control to simultaneously control the orbit, attitude and vibration of a large spacecraft undergoing on-orbit assembly. At the same time, u(t) satisfies the input saturation condition and can overcome input lag and controller gain perturbation.

[0046] Those skilled in the art will appreciate that the embodiments described herein are intended to help readers understand the principles of the present invention, and should be understood that the protection scope of the present invention is not limited to such specific statements and embodiments. Those skilled in the art can make various other specific variations and combinations that do not deviate from the essence of the present invention based on the technical revelations disclosed by the present invention, and these variations and combinations are still within the protection scope of the present invention.

Claims

1. A multi-objective optimization control method for on-orbit assembly of large spacecraft, characterized in that: The method comprises: S1. Establishing a corresponding state space model based on the orbit-attitude-vibration integrated model of the large spacecraft; S2. Determine a controller of a track-attitude-vibration integrated model based on the state-space model; S3, determining multi-objective optimization constraints according to the operating state of the large spacecraft, and solving the controller based on the multi-objective optimization constraints; S4, applying the solved controller to the orbit-attitude-vibration integrated model; The state space model Π is specifically shown in the following formula: In the formula, t represents time, is the derivative of the controlled state variables including the orbit, attitude and mode of the large spacecraft with respect to time, A is the state matrix obtained after linearization of the orbit-attitude-vibration integrated dynamic model, ΔA represents the uncertainty matrix caused by modeling errors and inertia unknowns to the state matrix A, x(t) is the controlled state variable including the orbit, attitude and mode of the large spacecraft, B1 is the control matrix, ΔB1 ​​represents the disturbance matrix caused by modeling errors and inertia unknowns to the control matrix B1, u(t) is the orbit-attitude-vibration integrated controller, B2 is the interference matrix, ΔB2 represents the disturbance matrix caused by modeling errors and inertia unknowns to the interference matrix B2, w(t) is the total interference including external interference and actuator failure, y(t) is the measurement output vector, C is the measurement matrix selected according to the actual measurability of the state variables, and v(t) is the measurement error vector; The controller u(t) is specifically shown in the following formula: u(t)=U(t,λ(u m ,t),D(τ),K,ΔK(t)) Where t is time, λ(u m ,t) is the input saturation function, u m is the maximum value of the absolute value of each component of the input torque, D(τ) is the input lag function, K is the gain matrix of the controller, ΔK(t) is the gain perturbation of the controller, and U is the function of time t, input saturation function λ(u m ,t), the input time lag function D(τ), the controller gain matrix K and the controller gain perturbation ΔK(t).

2. The multi-objective optimization control method for on-orbit assembly of large spacecraft according to claim 1, characterized in that: The operation state in step S3 includes a first state and a second state. The first state is specifically that the large spacecraft is in an on-orbit assembly period or an on-orbit service state. The second state is specifically that the large spacecraft is in a normal on-orbit operation and is disturbed and unstable. The multi-objective optimization constraint condition corresponding to the first state is J1, and the multi-objective optimization constraint condition corresponding to the second state is J2. The expression of the multi-objective optimization constraint condition is as follows: where \(t_0\) represents the moment when control starts to be applied to the large spacecraft, is the time required to complete the control, where \(\alpha>0,\beta>0,p > 1,0<q<1\) are variables to be optimized, is a parameter to be selected, where \(i = 1,2,3,4;j = 1,2\), and \(\eta(t)\) represents the modal displacement vector of the flexible spacecraft, \(\eta\) T (t) is the transpose of \(\eta(t)\), represents the derivative of the modal displacement with respect to time, is the transpose of, \(R\) 11 is the weight matrix for determining the vibration energy consumption selected when the large spacecraft is in the on-orbit assembly period or receiving on-orbit services, is the stiffness matrix of the flexible spacecraft, \(t\) represents time, \(x(t)\) is the controlled state variable including the orbit, attitude and mode of the large spacecraft, \(x\) T (t) is the transpose of \(x(t)\), \(u(t)\) is the orbit-attitude-vibration integrated controller, \(u\) T (t) is the transpose of \(u(t)\), \(R\) 12 is the weight matrix for determining the total energy consumption selected when the large spacecraft is in the on-orbit assembly period or receiving on-orbit services, \(Q_1\) is the weight matrix for determining the system stability accuracy selected when the large spacecraft is in the on-orbit assembly period or receiving on-orbit services, \(R\) 21 is the weight matrix for determining the vibration energy consumption selected when the large spacecraft is in normal on-orbit operation and in a disturbed and unstable state, \(R\) 22 is the weight matrix for determining the total energy consumption selected when the large spacecraft is in normal on-orbit operation and in a disturbed and unstable state, \(Q_2\) is the weight matrix for determining the system stability accuracy selected when the large spacecraft is in normal on-orbit operation and in a disturbed and unstable state, \(d\) is the differential operation symbol.

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