CN108563914B - Track control thrust fitting coefficient calculation method based on summer least square - Google Patents
Track control thrust fitting coefficient calculation method based on summer least square Download PDFInfo
- Publication number
- CN108563914B CN108563914B CN201810583499.1A CN201810583499A CN108563914B CN 108563914 B CN108563914 B CN 108563914B CN 201810583499 A CN201810583499 A CN 201810583499A CN 108563914 B CN108563914 B CN 108563914B
- Authority
- CN
- China
- Prior art keywords
- calculating
- thrust
- control
- coefficient
- track
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/10—Geometric CAD
- G06F30/15—Vehicle, aircraft or watercraft design
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
- G06F17/16—Matrix or vector computation, e.g. matrix-matrix or matrix-vector multiplication, matrix factorization
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/20—Design optimisation, verification or simulation
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Geometry (AREA)
- General Engineering & Computer Science (AREA)
- Computational Mathematics (AREA)
- Mathematical Analysis (AREA)
- Mathematical Optimization (AREA)
- Mathematical Physics (AREA)
- Pure & Applied Mathematics (AREA)
- Data Mining & Analysis (AREA)
- Computer Hardware Design (AREA)
- Evolutionary Computation (AREA)
- Software Systems (AREA)
- Databases & Information Systems (AREA)
- Algebra (AREA)
- Automation & Control Theory (AREA)
- Aviation & Aerospace Engineering (AREA)
- Computing Systems (AREA)
- Control Of Position, Course, Altitude, Or Attitude Of Moving Bodies (AREA)
- Feedback Control In General (AREA)
Abstract
The invention provides a summer least square-based track control thrust fitting coefficient calculation method, which comprehensively analyzes the correlation of theoretical speed increment, actual speed increment and track control thrust coefficient of previous track control, adopts summer least square estimation to represent the fitting coefficient of thrust, establishes a model capable of simulating real system behavior, and predicts the future evolution of system output by using the current measurable system input and output. The method utilizes the historical orbit control data as input, and calculates the actual thrust fitting coefficient by using the generalized least square of the Charpy method, and has the characteristics of high calculation efficiency, no need of repeated data filtering and the like; the deviation in the least square trajectory can be eliminated through iteration, so that the method is relatively simple in calculation and high in prediction accuracy.
Description
Technical Field
The invention relates to the field of measurement and control management of in-orbit spacecrafts, which is suitable for the fitting calculation of a thrust coefficient during the control of a near-earth satellite orbit.
Background
The ground track of the near-earth satellite gradually deviates from the set running track due to the attenuation of the track caused by atmospheric resistance, and the track maintenance control needs to be carried out by regularly controlling the thruster through the track, so that the ground track of the satellite always meets the design requirement of a track network. The thrust of the satellite orbit control thruster is a polynomial function taking the pressure of a propellant storage tank as an independent variable, and the coefficient of the polynomial function is a binding constant and is kept unchanged in the whole service life of the satellite. With the increase of the satellite orbit control times, the pressure of the propellant storage tank is continuously reduced, and the satellite speed increment calculated on the basis of theoretical thrust and the actual speed increment have larger errors, so that the orbit control precision is reduced. In view of the foregoing, a method for calculating a fitting of a thrust coefficient for trajectory control is needed.
The traditional track control speed increment calculation only takes the calibration coefficient of the previous thruster as a calculation basis, the thrust coefficient is kept unchanged, and the control data of the track of the previous time is not effectively utilized to carry out optimization calculation, so that the error between the theoretical speed increment and the actual speed increment is not measurable, and certain difficulty is brought to the formulation of a track control strategy.
Disclosure of Invention
In order to overcome the defects of the prior art, the invention provides a track control thrust fitting coefficient calculation method based on summer least squares, which comprehensively analyzes the correlation among the theoretical speed increment, the actual speed increment and the track control thrust coefficient of the previous track control, adopts the summer least squares to estimate the fitting coefficient of the characteristic thrust, establishes a model capable of simulating the real system behavior, predicts the future evolution of the system output by using the current measurable system input and output, and has the characteristic of high prediction precision.
The technical scheme adopted by the invention for solving the technical problem comprises the following steps:
1) calculating the density rho of the propellant of the two storage tanks before the ith orbit controlix＝1025.5-0.875×(Tix273.15), then calculating the remaining mass of fuel in the two tanks before the ith rail control
Where ρ is0x、P0x、T0x、VTxAnd m0xRespectively representing the density, gas pressure, gas absolute temperature, tank volume and initial fuel mass of the two tanks during fillingixAnd PixAbsolute tank temperature and tank pressure before the ith rail control are respectively shown, subscript x represents the number of the fuel storage tank, and x is 1 and 2;
2) calculating the satellite mass m before the ith orbit controlsati＝msat0-m01+mi1-m02+mi2Wherein m issat0The mass of the satellite including fuel when filling the two tanks; then, calculating the total thrust I corresponding to the pressure required to be provided by the rail-controlled thrusteriEx＝msatiΔVx *，ΔVx *Is the theoretically calculated speed variation; and calculating the specific impulse I of each orbit control according to the relation between the specific impulse and the pressureiSx＝G0+G1Pix+G2Pix 2+G3Pix 3，G0、G1、G2、G3Fitting coefficients for the set specific impulse pressure; finally calculating the pressure of the storage tank after rail control
3) Defining P according to the Charpy least squares estimation methodix、Δtix、TixAnd Δ Vx *As an input quantity, where Δ tixIs the thrust action time, Δ VixFitting polynomial coefficients D as output0、D1、D2、D3As the coefficient to be solved; for i groups of measured values of i orbital controls, a measurement matrix is calculated
Computing an output vector
4) Calculating a thrust coefficient vector theta to be solved as [ D ═ D0,D1,D2,D3]TLeast squares estimation of
Calculating residual error
Taken when calculating residual e for the 1 st time
And then using residual construction
Computing consistent unbiased estimates of noise fitting coefficients
Calculating thrust coefficient error
Γ＝(ΦTΦ)-1ΦT；
5) If it is not
The error from the last calculation is less than 1e-5Entering step 6); otherwise, returning to the step 4);
6) calculating a charpy least squares estimate of θ
Obtaining the estimated value of the thrust coefficient
7) Calculating the kth rail-controlled thrust
And rail controlled rear thrust
Calculating the average thrust
Finally, the predicted speed variation of the secondary orbit control is calculated
Wherein, Δ tkFor the duration of the thrust controlled by the rail, msatkIs the current quality of the satellite.
The specific impulse pressure fitting coefficient G0、G1、G2、G31888.8, 635.1, -403.6, and 89.61, respectively.
The invention has the beneficial effects that:
1) the method comprehensively analyzes the correlation among the theoretical velocity increment, the actual velocity increment and the track control thrust coefficient of the control of the track of the past times, adopts the summer least square estimation to represent the fitting coefficient of the thrust, establishes a model which can simulate the real system behavior, predicts the future evolution of the system output by using the input and the output of the currently measurable system, and has high prediction precision and average error within 1.5 percent.
2) The method effectively utilizes the control data of the track of the past times to carry out optimization calculation, and overcomes the defects that the traditional track control speed increment calculation only uses the calibration coefficient of the previous thruster as the calculation basis and the thrust coefficient is kept unchanged.
3) The method has guiding significance for making the orbit control strategy of the in-orbit satellite.
In conclusion, historical orbit control data is used as input, and the actual thrust fitting coefficient is calculated by using the generalized least square of the Charpy method, so that the method has the characteristics of high calculation efficiency, no need of repeated data filtering and the like; the deviation in the least square trajectory can be eliminated through iteration, so that the method is relatively simple in calculation and high in prediction accuracy.
Drawings
FIG. 1 is a flow chart of the method of the present invention.
Detailed Description
The present invention will be further described with reference to the following drawings and examples, which include, but are not limited to, the following examples.
Using the relationship between momentum and impulse during satellite orbit control, the input is defined: pressure P (unit: Mpa) of front storage tank for track control, thrust action time delta T (unit: s) and absolute temperature T of front storage tank for track controlx(unit: K), speed variation amount DeltaV calculated theoreticallyx *(the subscript "x" stands for fuel tank number, x is 1,2), defines the output: and (3) establishing a thrust fitting coefficient identification model according to the actual speed variation delta V (unit: m/s). And gradually eliminating the deviation in the least square track through n groups of measurement data and an alternate solving algorithm for gradually improving the precision of the deviation item so as to obtain an estimation coefficient. The specific process is as follows:
from the relationship between momentum and impulse, we can derive:
in the formula
Is the mean thrust (in N), Δ t is the thrust action time (in s), msatIs the current mass (unit: kg) of the satellite, and the delta V is the speed variation (unit: m/s) after calibration.
F is the rail-controlled forward thrust, FfIs the rail-controlled rear thrust.
Di(i is 1,2,3,4) is a fitting polynomial coefficient and P is the rail-controlled front tank pressure (single)Bit: mpa), PfThe pressure of the rear storage tank is controlled by a rail, the subscript "x" represents the number of the fuel storage tank (x is 1 and 2), and the storage tank 1 and the storage tank 2 are mutually switched according to the pressure change when the thruster works.
Wherein, the current density (unit: kg/cm) of the propellant in the storage tanks 1 and 23)：
ρx＝1025.5-0.875×(Tx-273.15) (5)
Residual mass of fuel (unit: kg):
relationship between specific impulse and pressure (unit: N · s/kg):
IS＝G0+G1Px+G2Px 2+G3Px 3 (7)
the total impulse (unit: N · s) corresponding to the pressure required to be provided by the maneuvering thruster at this time is as follows:
IEx＝msatΔVx * (8)
current satellite mass (unit: kg):
msat＝msat0-m01+m1-m02+m2 (9)
wherein, VTxIs the volume (unit: m) of the storage tank3)，TxIs the absolute temperature (unit: K) of the front storage tank controlled by the rail0x、P0xIs the absolute temperature and pressure of the gas at the time of filling (unit: K, Mpa), m01、m02Is the initial fuel mass (unit: kg) of the tanks 1,2, rho0xInitial fuel density (unit: kg/cm)3)，msat0Initial satellite mass (unit: kg), Δ Vx *Is the amount of speed change calculated theoretically, and the subscript "x" represents the fuel tank number (x ═ 1,2)。
to sum up, P is defined according to the method of least squares estimation in Charpyx、Δtx、Tx、ΔVx *Is the input quantity, Δ VxIs the output quantity, D0、D1、D2、D3Is the coefficient to be found. Assuming n sets of measurements, then:
in the formula (10), i represents the ith group of measured values.
After unfolding equation (10) we can obtain:
according to the formula (11), a measurement matrix Φ, a parameter vector θ to be solved, and an output vector y can be obtained:
when considering the influence of system noise xi, the noise fitting coefficient is defined as f ═ f1 f2 f3 f4]TThe fitting formula of the system noise xi is
When considering the effect of system noise, the difference equation for the system can be expressed as:
wherein f is a noise fitting coefficient vector, epsilon is a white noise vector with the average value of 0, and is an uncorrelated random sequence, so that a least square method can be used for obtaining the consistent unbiased estimation of the coefficient f. If there are n sets of measurement data, taking into account the calculation efficiency, and using the Xiahu improvement method, there are
Wherein e is a residual error, and the specific expression of omega is as follows
In conclusion, the estimation coefficient can be obtained by referring to the iterative calculation step.
And selecting a certain low-orbit satellite with n equal to 45 orbit controls for example calculation, wherein the satellite is provided with two propellant storage tanks, and the orbit controls are switched to use each time according to the pressure difference of the storage tanks.
1) And (6) initializing data. Data input, including gas propellant density at filling of two tanks0x(unit: kg/cm)3) Gas pressure P0x(unit: Mpa), gas absolute temperature T0x(unit: K), storage tank volume VTx(unit: m)3) Initial fuel mass m of tank0x(unit: kg), satellite mass (fuel-containing) msat0(unit: kg), coefficient of specific impulse pressure fit G0、G1、G2、G3As shown in table 1;
TABLE 1 simulation parameters
| Serial number | Content providing method and apparatus | Unit of | Numerical value |
| 1 | Density of gas propellant when No. 1 storage tank is filled | kg/m3 | 1.008e3 |
| 2 | Gas pressure (MPa) during filling of No. 1 storage tank | MPa | 1.720 |
| 3 | Absolute temperature of gas during filling of No. 1 storage tank | K | 295.27 |
| 4 | Storage tank volume of No. 1 storage tank | 3 | 0.19982 |
| 5 | Initial fuel quality of tank 1 | kg | 149.85 |
| 6 | Density of gas propellant when No. 2 storage tank is filled | kg/m3 | 1.008e3 |
| 7 | Gas pressure (MPa) when No. 2 storage tank is filled | MPa | 1.715 |
| 8 | Absolute gas temperature during filling of No. 2 storage tank | K | 294.53 |
| 9 | Storage tank volume of No. 2 storage tank | 3 | 0.19936 |
| 10 | Initial fuel quality of tank No. 2 | kg | 149.85 |
| 11 | Quality (kg) of rail-controlled front satellite (containing fuel) | kg | 2635.7 |
| 12 | Coefficient of fit G of specific impulse pressure0 | - | 1888.8 |
| 13 | Coefficient of fit G of specific impulse pressure1 | - | 635.1 |
| 14 | Coefficient of fit G of specific impulse pressure2 | - | -403.6 |
| 15 | Coefficient of fit G of specific impulse pressure3 | - | 89.61 |
Pressure P of reservoir before track controlix(unit: Mpa), absolute tank temperature Tix(unit: K), thrust duration Deltatix(unit: s), theoretical speed measurement quantity Δ Vix *(unit: m/s) and a variation amount DeltaV of the calibrated speedix(unit: m/s) as shown in tables 2 and 3. Where the value 0 indicates that the tank is not in use, the index x indicates the fuel tank number (x 1,2), and the index i indicates the ith tracking (i 1,2, …, n).
TABLE 2 input data for tank 1
TABLE 3 input data for tank 2
2) Tank remaining fuel calculation. Firstly, the density rho of the propellant of the two storage tanks before the ith orbit control is calculated by the formula (5)ixThen, the remaining fuel mass m of the two tanks before the i-th rail control is calculated by equation (6)ix。
3) Tank pressure calculation. Firstly, the current mass m of the satellite is calculated by the formula (9)satI, then calculating the total impact I corresponding to the pressure required to be provided by the rail-controlled thruster by using the formula (8)iExAnd calculating the specific impulse I of each orbit control by using an expression (7) according to the relation between the specific impulse and the pressureiSxFinally, the pressure P of the storage tank after rail control is calculated by the formula (4)fix。
4) And (5) calculating a measurement matrix. The measurement matrix Φ is calculated by equation (12), and the output vector y is calculated by equation (13).
5) Thrust coefficient vector theta to be solved is ═ D0,D1,D2,D3]TCharpy least squares estimation calculation. First, a least squares estimate of θ is calculated using equation (11)
The residual error e is calculated and,
it is advisable when calculating the residual e at the 1 st time
Then, using the residual to construct omega, a consistent unbiased estimate of the noise fit coefficient is calculated using equation (16)
According to
Calculating thrust coefficient error
Γ＝(ΦTΦ)-1ΦTIn aThe whole calculation process is invariable and only needs to be calculated once.
6) If it is not
The error from the last calculation is less than 1e-5Turning to the next step; otherwise, repeating the step 5.
7) Using equation (13) to calculate a charpy least squares estimate of θ
Namely the estimated value of the thrust coefficient to be solved
And outputting and storing.
8) Using thrust coefficient estimates
And calculating the predicted speed variation of the kth (k is more than or equal to 1) orbit control. First, a rail-controlled forward thrust F is calculated according to the following formulak(unit: N) and a rail-controlled thrust Ffk(unit: N):
then, an average thrust is calculated
And finally, calculating to obtain the predicted speed variation of the orbit control:
wherein, Δ tkFor the duration of the thrust controlled by the rail, msatkIs the current quality of the satellite.
In summary, there are 45 sets of usable data, one set of data is removed in each simulation, the remaining 44 sets of data are used as samples, the removed set of data are used as the accuracy verification standard, and the simulation is performed, and the simulation results are as follows:
TABLE 4 simulation results
Taking the absolute value of the prediction error percentage, and counting to obtain an error percentage distribution diagram:
as can be seen from table 4, the maximum error is 4.6%, the average error is 1.39%, and the accuracy of the predicted speed variation after the thrust coefficient fitting is performed by using the charpy method is high.
Claims (1)
1. A method for calculating a track control thrust fitting coefficient based on summer least squares is characterized by comprising the following steps:
1) calculating the density rho of the propellant of the two tanks before the ith track controlix＝1025.5-0.875×(Tix273.15), then calculating the remaining mass of fuel in the two tanks before the ith rail control
Where ρ is0x、P0x、T0x、VTxAnd m0xRespectively representing the density, gas pressure, gas absolute temperature, tank volume and initial fuel mass of the two tanks during fillingixAnd PixThe absolute temperature of the storage tank and the absolute temperature of the storage tank before the ith rail controlPressure, subscript x denotes the fuel tank number, x ═ 1, 2;
2) calculating the satellite mass m before the ith orbit controlsati＝msat0-m01+mi1-m02+mi2Wherein m issat0The mass of the satellite including fuel when filling the two tanks; then, calculating the total thrust I corresponding to the pressure required to be provided by the rail-controlled thrusteriEx＝msati△Vx *，△Vx *Is the theoretically calculated speed variation; and calculating the specific impulse I of each orbit control according to the relation between the specific impulse and the pressureiSx＝G0+G1Pix+G2Pix 2+G3Pix 3，G0、G1、G2、G3Fitting coefficients for the set specific impulse pressure; finally calculating the pressure of the storage tank after rail control
3) Defining P according to the method of least squares estimation of Charpyix、△tix、TixAnd Δ Vx *As input quantity, where Δ tixIs the track control thrust action time, DeltaVixFitting polynomial coefficients D as output0、D1、D2、D3As the coefficient to be solved; for i groups of measured values of i orbital controls, a measurement matrix is calculated
Computing an output vector
4) Calculating a vector theta of the control thrust coefficient of the track to be solved as [ D ]0,D1,D2,D3]ΤLeast squares estimation of
Calculating residual error
Taken when calculating residual e for the 1 st time
And then using residual construction
Consistent unbiased estimation of calculated noise fitting coefficients
Calculating track control thrust coefficient error
5) If the track controls the thrust coefficient error
The error from the last calculation is less than 1e-5Entering step 6); otherwise, returning to the step 4);
6) charpy least square estimation for calculating thrust coefficient vector theta to be solved
Obtaining the estimated value of the track control thrust coefficient
7) Calculating the ith orbit control front orbit control thrust
And rail-controlled rear rail control thrust
Calculating average orbital control thrust
Finally, the predicted speed variation of the ith orbit control is calculated
Wherein, Δ tkControl of thrust duration, m, for the tracksatkIs the current quality of the satellite.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810583499.1A CN108563914B (en) | 2018-06-08 | 2018-06-08 | Track control thrust fitting coefficient calculation method based on summer least square |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810583499.1A CN108563914B (en) | 2018-06-08 | 2018-06-08 | Track control thrust fitting coefficient calculation method based on summer least square |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN108563914A CN108563914A (en) | 2018-09-21 |
| CN108563914B true CN108563914B (en) | 2022-05-17 |
Family
ID=63553334
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201810583499.1A Active CN108563914B (en) | 2018-06-08 | 2018-06-08 | Track control thrust fitting coefficient calculation method based on summer least square |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN108563914B (en) |
Families Citing this family (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110954153B (en) * | 2019-11-08 | 2021-09-24 | 电子科技大学 | Distributed adaptive combination coefficient optimization method |
| CN112304169B (en) * | 2020-10-28 | 2023-05-02 | 北京星际荣耀空间科技股份有限公司 | Carrier rocket guidance method and system based on thrust adjustment |
Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US7411543B1 (en) * | 2004-08-13 | 2008-08-12 | Lockheed Martin Corporation | Maximum-likelihood rocket identifier |
| CN103020338A (en) * | 2012-11-29 | 2013-04-03 | 北京理工大学 | Low-thrust gravity-assist trajectory solution space pruning method |
| CN103662096A (en) * | 2013-12-13 | 2014-03-26 | 北京控制工程研究所 | Self-adaptation powered explicit guidance method |
| CN106564622A (en) * | 2016-11-02 | 2017-04-19 | 北京控制工程研究所 | Synchronous orbit satellite relative dip angle remote correcting method based on line-of-sight measurement |
| CN107102549A (en) * | 2017-05-19 | 2017-08-29 | 西北工业大学 | Space rope system robot target approaches appearance rail stable control method under the conditions of Parameter uncertainties |
| CN107323688A (en) * | 2017-06-29 | 2017-11-07 | 上海航天控制技术研究所 | It is a kind of for when change propulsive spaceborne computer thruster jet duration calculation method |
| CN107554820A (en) * | 2017-09-04 | 2018-01-09 | 上海航天控制技术研究所 | A kind of satellite Autonomous Maneuver strategy based on gain On-line Estimation |
| CN107562691A (en) * | 2017-08-14 | 2018-01-09 | 中国科学院力学研究所 | A kind of micro thrust dynamic testing method based on least square method |
-
2018
- 2018-06-08 CN CN201810583499.1A patent/CN108563914B/en active Active
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US7411543B1 (en) * | 2004-08-13 | 2008-08-12 | Lockheed Martin Corporation | Maximum-likelihood rocket identifier |
| CN103020338A (en) * | 2012-11-29 | 2013-04-03 | 北京理工大学 | Low-thrust gravity-assist trajectory solution space pruning method |
| CN103662096A (en) * | 2013-12-13 | 2014-03-26 | 北京控制工程研究所 | Self-adaptation powered explicit guidance method |
| CN106564622A (en) * | 2016-11-02 | 2017-04-19 | 北京控制工程研究所 | Synchronous orbit satellite relative dip angle remote correcting method based on line-of-sight measurement |
| CN107102549A (en) * | 2017-05-19 | 2017-08-29 | 西北工业大学 | Space rope system robot target approaches appearance rail stable control method under the conditions of Parameter uncertainties |
| CN107323688A (en) * | 2017-06-29 | 2017-11-07 | 上海航天控制技术研究所 | It is a kind of for when change propulsive spaceborne computer thruster jet duration calculation method |
| CN107562691A (en) * | 2017-08-14 | 2018-01-09 | 中国科学院力学研究所 | A kind of micro thrust dynamic testing method based on least square method |
| CN107554820A (en) * | 2017-09-04 | 2018-01-09 | 上海航天控制技术研究所 | A kind of satellite Autonomous Maneuver strategy based on gain On-line Estimation |
Non-Patent Citations (5)
| Title |
|---|
| Robust control for constant thrust collision avoidance maneuver;Yongqiang Qi et al.;《2015 34th Chinese Control Conference (CCC)》;20150914;第5067-5072页 * |
| Study on Orbit Control Error Propagation Characteristics by Covariance technique;Li, Wei et al.);《2017 IEEE International Conference on Cybernetics and Intelligent Systems (CIS) and IEEE Conference on Robotics, Automation and Mechatronics (RAM)》;20180201;第446-451页 * |
| 一种确定侵蚀函数的新方法;陈军等;《推进技术》;19980628;第19卷(第3期);第13-16页 * |
| 基于MATLAB的最小二乘法参数辨识与仿真;石贤良等;《微处理机》;20051230(第6期);第44-46页 * |
| 航天器捕获制动过程的质量特性在轨辨识方法研究;韩宇等;《载人航天》;20171215;第23卷(第6期);第724-730页 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN108563914A (en) | 2018-09-21 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN108563914B (en) | Track control thrust fitting coefficient calculation method based on summer least square | |
| CN105224737B (en) | A kind of first value correction method of extraterrestrial target improvement of orbit | |
| CN109992927B (en) | Reentry forecasting method of small elliptical target under sparse data condition | |
| CN106249599B (en) | Neural network prediction-based networked control system fault detection method | |
| CN111301715B (en) | Hoeman orbital transfer-based constellation layout and orbit adjustment method and device for same-orbit specific phase distribution and computer storage medium | |
| CN107554820B (en) | A kind of satellite Autonomous Maneuver strategy based on gain On-line Estimation | |
| CN103453963B (en) | A kind of spacecraft in-orbit Residual Propellant measuring device and method | |
| CN109870260B (en) | Method for online measurement of output thrust of MEMS solid micro-thruster array | |
| CN111731513B (en) | Method for maintaining regression orbit in high-precision gravitational field based on monopulse orbit control | |
| CN105807610A (en) | Self-adaptive weight matrix weighing pseudo-inverse thrust distribution and saturation handling method | |
| CN103662096A (en) | Self-adaptation powered explicit guidance method | |
| CN102904519A (en) | Robust excitation system parameter identification method based on exponential-type target function | |
| CN112560343B (en) | J2 perturbation Lambert problem solving method based on deep neural network and targeting algorithm | |
| Lichota et al. | A priori model inclusion in the multisine maneuver design | |
| US5934621A (en) | Batched optimized method for transfer orbit construction | |
| CN107323688B (en) | It is a kind of for when change propulsive spaceborne computer thruster jet duration calculation method | |
| CN108241303A (en) | A kind of Vacuum Plume effect Method for Accurate Calculation | |
| CN113311851B (en) | Spacecraft chase-escaping intelligent orbit control method, device and storage medium | |
| CN115204449A (en) | Track prediction method based on self-adaptive Legendre Picard iteration method | |
| CN114035611A (en) | Reusable hypersonic aircraft ascending section track optimization and guidance method | |
| CN111950074B (en) | Method and device for determining emission centroid of parallel storage tank spacecraft | |
| CN113761662A (en) | Generation method of trajectory prediction pipeline of gliding target | |
| CN112134612B (en) | Low-orbit communication constellation on-orbit reconstruction method and system | |
| Wang et al. | Satellite Constellation Reconfiguration Method Using Improved PSO Algorithm for Communication and Navigation | |
| McCrate et al. | Higher Order Methods for Determining Optimal Controls and Their Sensitivities |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |