CN109870271A - Kalman Filter Identification Method for Moment of Inertia of Large Scale Flexible Spacecraft - Google Patents
Kalman Filter Identification Method for Moment of Inertia of Large Scale Flexible Spacecraft Download PDFInfo
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Abstract
本发明公开了一种大尺度挠性航天器转动惯量卡尔曼滤波辨识方法，用于解决现有航天器转动惯量辨识方法实用性差的技术问题。技术方案是首先针对大尺度挠性航天器，根据小角度机动下的动力学方程确定观测方程。继而采用闭环控制激励的PD控制器，控制卫星转过设定的角度。根据观测方程，应用卡尔曼滤波进行转动惯量辨识。由于采用卡尔曼滤波方法，考虑大尺度挠性航天器挠性耦合的影响因素进行转动惯量辨识，实现了转动惯量在轨辨识。降低了由于航天器刚挠耦合系数大、挠性振动对姿态角和姿态角速度对系统产生的较大影响。辨识的转动惯量为后续的姿态控制提供了基础，增强了航天器姿态控制系统的精度，实用性好。
The invention discloses a large-scale flexible spacecraft moment of inertia Kalman filter identification method, which is used to solve the technical problem of poor practicability of the existing spacecraft moment of inertia identification method. The technical solution is to first determine the observation equation for the large-scale flexible spacecraft according to the dynamic equation under small-angle maneuvering. Then, a PD controller with closed-loop control excitation is used to control the satellite to rotate through a set angle. According to the observation equation, Kalman filter is applied to identify the moment of inertia. Due to the Kalman filter method, the inertia moment identification is carried out considering the influence factors of the flexible coupling of the large-scale flexible spacecraft, and the on-orbit identification of the rotational inertia moment is realized. The large influence of the spacecraft on the attitude angle and attitude angular velocity due to the large rigid-flexible coupling coefficient of the spacecraft and the flexible vibration on the system is reduced. The identified moment of inertia provides the basis for the subsequent attitude control, which enhances the accuracy of the spacecraft attitude control system and has good practicability.
Description
Technical field
The present invention relates to a kind of spacecraft method for identification of rotational inertia, in particular to a kind of large scale flexible spacecraft rotation
Inertia Kalman filtering discrimination method.
Background technique
Document " the in-orbit identification method of Xu Wenfu, He Yong, Wang Xueqian, Liang Bin, Liu Yu spacecraft mass characterisitic parameter
[J] aerospace journal, 2010,31 (8): 1906-1914 " disclose it is a kind of on the basis of Rigid Body Dynamics Model based on the non-of PSO
The Global Optimal Problem that parameter identification problem is converted to nonlinear system is picked out spacecraft by linear optimization method, this method
Rotary inertia parameter.In the case that document the method is suitable for satellite as rigid body, does not account for large scale flexible spacecraft and scratch
Property influence of the coupling to rotary inertia parameter identification；For large scale flexible spacecraft, the rigid-flexible coefficient of coup is larger, is turning
If ignored when dynamic inertia identification, identifier substantial deviation true value will cause, so that identification be caused to fail.Therefore, this method
It is not applied for the identification of rotational inertia of large scale flexible spacecraft.
Summary of the invention
In order to overcome the shortcomings of existing spacecraft method for identification of rotational inertia, the practicability is poor, and the present invention provides a kind of large scale
Flexible spacecraft rotary inertia Kalman filtering discrimination method.This method is first against large scale flexible spacecraft, according to small angle
Spend it is motor-driven under kinetics equation determine observational equation.Then using the PD control device of closed-loop control excitation, control satellite is turned over
The angle of setting.According to observational equation, identification of rotational inertia is carried out using Kalman filtering.Due to using Kalman filtering side
Method considers that the influence factor of large scale flexible spacecraft flexibility coupling carries out identification of rotational inertia, it is in-orbit to realize rotary inertia
Identification.It reduces since the rigid-flexible coefficient of coup of spacecraft is big, flexible vibration generates attitude angle and attitude angular velocity to system
Larger impact.The rotary inertia of identification is that subsequent gesture stability provides the foundation, and enhances spacecraft attitude control system
Precision, practicability are good.
A kind of the technical solution adopted by the present invention to solve the technical problems: large scale flexible spacecraft rotary inertia karr
Graceful filter identification method, its main feature is that the following steps are included:
Step 1: determining identified parameters and inputting out the observational equation between measurement data.
Rotary inertia parameter to be identified is expressed as to the inverse form of parameter to be identified,
In formula, x is the vector for needing to estimate, each element corresponds to six elements of the inverse matrix of inertial matrix I.
For large scale flexible spacecraft, the kinetics equation under low-angle is motor-driven is
Wherein, I is satellite rotary inertia, parameter to be identified；It is spacecraft angular acceleration, ProtIt is that flexible appendage is opposite
In the rotation Coupled Rigid-flexible coefficient of body coordinate system, CηAnd KηFor the modal damping matrix and stiffness matrix of attachment, η is flexible attached
Mode of oscillation of the part under modal coordinate, T are the bonding force squares that satellite is subject to.
It obtains
It enables
It obtains
Determine that observational equation is as follows:
Z=Hx (5)
Here
Here S1、S2、S3It is rolling, pitching, yaw excitation T1、T2、T3And influence of the flexible part to spacecraft, lead to
It crossesIt shows.
Step 2: determining incentive program.
PD control device is motivated using closed-loop control, desired gesture stability torque size are as follows:
In formula, ω and Θ are respectively incremental vector needed for angular speed and Euler angle, and J is rotary inertia, and T is control force
Square, KωAnd KωFor PD control device coefficient.
Step 3: Kalman filtering recognizes.
System state equation
X (k+1)=x (k)+w (k) (8)
Observational equation
Z (k)=H (k) x (k)+v (k) (9)
In formula, w (k) and v (k) is the white noise sequence that mean value is zero, noise characteristic
E [w (k)]=E [v (k)]=0
E[w(k)wT(j)]=Qkδkj
E[v(k)vT(j)]=Rkδkj
E[w(k)vT(j)]=0
In formula, δkjFor Crow Buddhist nun gram δ function, characteristic is
QkFor nonnegative definite matrix, RkFor positive definite matrix.
The step of recognizing rotary inertia based on Kalman filtering is as follows:
The first step, prediction:
(b) P (k+1/k)=P (k/k) (11)
Second step, amendment:
(c) K (k+1)=P (k+1/k) HT(k+1)[H(k+1)P(k+1/k)HT(k+1)+Rk+1]-1 (13)
Wherein, P is error covariance matrix, and K is determining optimum gain matrix, completes large scale flexible spacecraft rotary inertia
Identification.
The beneficial effects of the present invention are: this method is first against large scale flexible spacecraft, according to low-angle it is motor-driven under
Kinetics equation determines observational equation.Then using the PD control device of closed-loop control excitation, control satellite turns over the angle of setting.
According to observational equation, identification of rotational inertia is carried out using Kalman filtering.Due to using kalman filter method, large scale is considered
The influence factor of flexible spacecraft flexibility coupling carries out identification of rotational inertia, realizes rotary inertia in-orbit identification.Reduce by
The larger impact that big, flexible vibration generates attitude angle and attitude angular velocity to system in the rigid-flexible coefficient of coup of spacecraft.Identification
Rotary inertia be subsequent gesture stability provide the foundation, enhance the precision of spacecraft attitude control system, practicability is good.
It elaborates with reference to the accompanying drawings and detailed description to the present invention.
Detailed description of the invention
Fig. 1 is the excitation curve of embodiment of the present invention method.
Fig. 2 is embodiment of the present invention method x-axis identification of rotational inertia curve graph.
Fig. 3 is embodiment of the present invention method y-axis identification of rotational inertia curve graph.
Fig. 4 is embodiment of the present invention method z-axis identification of rotational inertia curve graph.
Fig. 5 is embodiment of the present invention method xy axis product of inertia change curve.
Fig. 6 is embodiment of the present invention method xz axis product of inertia change curve.
Fig. 7 is embodiment of the present invention method yz axis product of inertia change curve.
Specific embodiment
Referring to Fig.1-7.Large scale flexible spacecraft rotary inertia Kalman filtering discrimination method specific steps of the present invention are such as
Under:
Step 1: determining identified parameters and inputs out the observational equation between measurement data.
Rotary inertia parameter to be identified is expressed as to the inverse form of parameter to be identified,
X is the vector for needing to estimate, each element corresponds to six elements of the inverse matrix of inertial matrix I.For example,It is right
Answer the I of the inverse matrix of inertial matrixxxCorresponding element.
For large scale flexible spacecraft, the kinetics equation under low-angle is motor-driven is
Wherein, I is satellite rotary inertia, parameter to be identified；It is spacecraft angular acceleration, ProtIt is that flexible appendage is opposite
In the rotation Coupled Rigid-flexible coefficient of body coordinate system, CηAnd KηFor the modal damping matrix and stiffness matrix of attachment, η is flexible attached
Mode of oscillation of the part under modal coordinate, T are the bonding force squares that satellite is subject to.
It obtains
It enables
It obtains
Determine that observational equation is as follows:
Z=Hx (5)
Here
Here S1、S2、S3It is rolling, pitching, yaw excitation T1、T2、T3And influence of the flexible part to spacecraft, lead to
It crossesIt shows.
Step 2: incentive program is determined.
The incentive program that this step is designed correctly, control satellite turn over the angle of setting.It designs PD control device and uses closed loop
Control excitation, designs desired gesture stability torque size are as follows:
ω and Θ is respectively incremental vector needed for angular speed and Euler angle, and J is rotary inertia, and T is control moment, KωWith
KωFor PD control device coefficient.
Step 3: Kalman filtering identification.
System state equation
X (k+1)=x (k)+w (k) (8)
Observational equation
Z (k)=H (k) x (k)+v (k) (9)
In formula, w (k) and v (k) is the white noise sequence that mean value is zero, noise characteristic
E [w (k)]=E [v (k)]=0
E[w(k)wT(j)]=Qkδkj
E[v(k)vT(j)]=Rkδkj
E[w(k)vT(j)]=0
In formula, δkjFor Crow Buddhist nun gram (Kroneker) δ function, characteristic is
QkFor nonnegative definite matrix, RkFor positive definite matrix.
The step of recognizing rotary inertia based on Kalman filtering is as follows:
The first step, prediction:
(2) P (k+1/k)=P (k/k) (11)
Second step, amendment:
(1) K (k+1)=P (k+1/k) HT(k+1)[H(k+1)P(k+1/k)HT(k+1)+Rk+1]-1 (13)
Wherein, P is error covariance matrix, and K is determining optimum gain matrix, and above step can be completed with large-scale flexible
The identification of rotational inertia of windsurfing satellite.
Example
The selection one typical space flight with large-scale flexible windsurfing is illustrated.
In this example, the gross mass of system is 1.5803e+06kg, inertia J are as follows:
Consider ten rank mode
Prot=
The first row: 1.71909719232044e-11-1.29102143360427e-17 2.78433175158856e-
16
2.89832740153608e-12 -1.62565723128785e-17 1.16330704617975e-13
313397.818665696 -6.29499312000034e-17 7.17940509526988e-13
-38.5913142691036
Second row: 0.0206769221783322 86750.3989421326 41199.5429747264
-6.87008404112719 12912.7899794399 6.13468084264884 -
4.03978886873467e-29
-45074.3325616449 -0.113569550719451 -53.3032831613732
The third line: 280749.877191912-0.210839800425953 4.54715882740672
47333.2785184105 -0.265489973505254 1899.82458124203
-1.91900817744354e-11 -1.02805039362318 11724.8583024403
-66349.2699140260
Step 1: determining identified parameters and inputs out the observational equation between measurement data.
Step 2: incentive program determines.
The initial Euler's angular displacement of system and angular speed deviation are as follows:
Θ=[0.2,0.2 0.2] deg
ω=[0.001,0.001,0.001] deg/s
Control process is from initial deviation to zero.
Design desired gesture stability torque size are as follows:
ω and Θ is respectively incremental vector needed for angular speed and Euler angle.
Posture process is referring to Fig. 1.
Step 3: Kalman filtering identification.
Kalman filtering identification is divided into two steps, first is that prediction, second is that amendment, is turned according to Kalman filtering step
The identification of dynamic inertia.It can be seen that all axes of inertia Identification Errors referring to Fig. 2-Fig. 7 emulation deviation and be less than 10%.
Claims (1)
1. a kind of large scale flexible spacecraft rotary inertia Kalman filtering discrimination method, it is characterised in that the following steps are included:
Step 1: determining identified parameters and inputting out the observational equation between measurement data.
Rotary inertia parameter to be identified is expressed as to the inverse form of parameter to be identified,
In formula, x is the vector for needing to estimate, each element corresponds to six elements of the inverse matrix of inertial matrix I.
For large scale flexible spacecraft, the kinetics equation under low-angle is motor-driven is
Wherein, I is satellite rotary inertia, parameter to be identified；It is spacecraft angular acceleration, ProtIt is flexible appendage relative to this
The rotation Coupled Rigid-flexible coefficient of body coordinate system, CηAnd KηFor the modal damping matrix and stiffness matrix of attachment, η is that flexible appendage exists
Mode of oscillation under modal coordinate, T are the bonding force squares that satellite is subject to.
It obtains
It enables
It obtains
Determine that observational equation is as follows:
Z=Hx (5)
Here
Here S1、S2、S3It is rolling, pitching, yaw excitation T1、T2、T3And influence of the flexible part to spacecraft, pass throughIt shows.
Step 2: determining incentive program.
PD control device is motivated using closed-loop control, desired gesture stability torque size are as follows:
In formula, ω and Θ are respectively incremental vector needed for angular speed and Euler angle, and J is rotary inertia, and T is control moment, Kω
And KωFor PD control device coefficient.
Step 3: Kalman filtering recognizes.
System state equation
X (k+1)=x (k)+w (k) (8)
Observational equation
Z (k)=H (k) x (k)+v (k) (9)
In formula, w (k) and v (k) is the white noise sequence that mean value is zero, noise characteristic
E [w (k)]=E [v (k)]=0
E[w(k)wT(j)]=Qkδkj
E[v(k)vT(j)]=Rkδkj
E[w(k)vT(j)]=0
In formula, δkjFor Crow Buddhist nun gram δ function, characteristic is
QkFor nonnegative definite matrix, RkFor positive definite matrix.
The step of recognizing rotary inertia based on Kalman filtering is as follows:
The first step, prediction:
(a)
(b) P (k+1/k)=P (k/k) (11)
Second step, amendment:
(c) K (k+1)=P (k+1/k) HT(k+1)[H(k+1)P(k+1/k)HT(k+1)+Rk+1]-1 (13)
(d)
(e)
Wherein, P is error covariance matrix, and K is determining optimum gain matrix, completes distinguishing for large scale flexible spacecraft rotary inertia
Know.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2024114558A1 (en) * | 2022-11-28 | 2024-06-06 | 影石创新科技股份有限公司 | Gimbal state identification method and apparatus, and storage medium and gimbal |
| CN119148759A (en) * | 2024-11-12 | 2024-12-17 | 西北工业大学宁波研究院 | Flexible agile spacecraft attitude control method under asymmetric time-varying constraint |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102620886A (en) * | 2012-03-27 | 2012-08-01 | 南京航空航天大学 | Two-step in-orbit recognition rotary inertia estimation method for combined spacecraft |
| CN106289641A (en) * | 2016-08-31 | 2017-01-04 | 上海航天控制技术研究所 | Spacecraft centroid position and rotary inertia parametric joint discrimination method |
| CN106468554A (en) * | 2016-09-29 | 2017-03-01 | 西北工业大学 | A kind of measuring method of the contactless inertial parameter of rolling satellite |
| CN107036761A (en) * | 2016-11-11 | 2017-08-11 | 大连理工大学 | A method for on-orbit identification of moment of inertia of spacecraft with flexible attachments under large-angle maneuvering |
| WO2018075525A1 (en) * | 2016-10-17 | 2018-04-26 | Raytheon Company | Work piece moment of inertia identification system |
-
2019
- 2019-01-31 CN CN201910094982.8A patent/CN109870271A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102620886A (en) * | 2012-03-27 | 2012-08-01 | 南京航空航天大学 | Two-step in-orbit recognition rotary inertia estimation method for combined spacecraft |
| CN106289641A (en) * | 2016-08-31 | 2017-01-04 | 上海航天控制技术研究所 | Spacecraft centroid position and rotary inertia parametric joint discrimination method |
| CN106468554A (en) * | 2016-09-29 | 2017-03-01 | 西北工业大学 | A kind of measuring method of the contactless inertial parameter of rolling satellite |
| WO2018075525A1 (en) * | 2016-10-17 | 2018-04-26 | Raytheon Company | Work piece moment of inertia identification system |
| CN107036761A (en) * | 2016-11-11 | 2017-08-11 | 大连理工大学 | A method for on-orbit identification of moment of inertia of spacecraft with flexible attachments under large-angle maneuvering |
Non-Patent Citations (5)
| Title |
|---|
| E.BERGMANN,ETC: "Spacecraft Mass Property Identification with Torque-Generating Control", 《 JOURNAL OF GUIDANCE CONTROL AND DYNAMICS》 * |
| 兰聪超 等: "带挠性附件卫星转动惯量的在轨辨识", 《振动与冲击》 * |
| 朱仁璋: "《航天器交会对接技术》", 31 October 2007 * |
| 杨廷梧 等: "《航空飞行试验光电测量理论与方法》", 31 January 2014 * |
| 黄攀峰 等: "《空间绳系机器人技术》", 31 August 2014 * |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2024114558A1 (en) * | 2022-11-28 | 2024-06-06 | 影石创新科技股份有限公司 | Gimbal state identification method and apparatus, and storage medium and gimbal |
| CN119148759A (en) * | 2024-11-12 | 2024-12-17 | 西北工业大学宁波研究院 | Flexible agile spacecraft attitude control method under asymmetric time-varying constraint |
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Application publication date: 20190611 |