CN111966073B - Model-based spacecraft control system robustness verification method - Google Patents

Model-based spacecraft control system robustness verification method Download PDF

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CN111966073B
CN111966073B CN202010700658.9A CN202010700658A CN111966073B CN 111966073 B CN111966073 B CN 111966073B CN 202010700658 A CN202010700658 A CN 202010700658A CN 111966073 B CN111966073 B CN 111966073B
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王淑一
袁利
刘羽白
刘潇翔
陈守磊
林波
石恒
苏晏
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Beijing Institute of Control Engineering
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Abstract

The invention belongs to the field of spacecraft control system fault verification, and relates to a method for verifying robustness of a spacecraft control system based on a model. According to the invention, the robustness verification capability for multiple faults of a plurality of spacecrafts is formed by adopting a modeled robustness verification mode and a matrix type model management and parameter configuration mode, so that the fault simulation capability and robustness verification level of a spacecraft control system are obviously improved, and the on-orbit stable operation of the spacecraft is ensured.

Description

Model-based spacecraft control system robustness verification method
Technical Field
The invention belongs to the field of spacecraft control system fault verification, and relates to a method for verifying robustness of a spacecraft control system based on a model. According to the invention, the robustness verification capability for multiple faults of a plurality of spacecrafts is formed by adopting a modeled robustness verification mode and a matrix type model management and parameter configuration mode, so that the fault simulation capability and robustness verification level of a spacecraft control system are obviously improved, and the on-orbit stable operation of the spacecraft is ensured.
Background
The robustness verification of the spacecraft control system mainly inspects the on-satellite autonomous fault isolation and handling capacity of the control system when system faults and single machine faults occur. The system level robustness verification mainly aims at system level fault types such as the out-of-tolerance of the three-axis attitude angle and the three-axis attitude angular velocity, and the like, and improves the service continuity of the whole satellite and the guarantee capability of the system safety from the system level. From a single-machine level, the related single machines of the current control system are more, and the control system comprises two categories of sensors and actuating mechanisms. The sensor type single machine comprises a gyroscope, a star sensor, a digital sun sensor, an analog sun sensor, a magnetometer and the like; the actuating mechanism type single machine comprises a momentum wheel, a CMG (control moment gyro), a magnetic torquer, an SADA (solar array drive device) and the like. The faults related to different functions of the single machines with various structures are various, and the fault characteristics mainly comprise zero-value faults, saturation faults, nonlinear faults and the like. Thus, from a fault characterization perspective, the fault types of the spacecraft control system can be classified as constant class faults, linear faults, and non-linear faults. Wherein a constant fault relates to a zero fault, a saturation fault, etc.
In the current engineering practice of spacecraft control system robustness verification, aiming at two high-power single-level and system-level fault types of constant value and jump, fault setting is carried out by adopting a mode of selecting manual setting numbers at specific time points in a system interface or a model and an external interface. Although simple and direct, the robustness verification method at the present stage has the problems of insufficient fault type coverage, non-uniform fault setting, non-standard robustness verification, non-solidified fault knowledge, non-universal robustness verification method and the like, and can not meet the robustness verification requirements of multiple faults of multiple spacecrafts. Particularly, in response to a more complex nonlinear slowly-varying fault, the existing robustness verification method has obvious defects, and a new solution needs to be found.
Disclosure of Invention
The technical problem solved by the invention is as follows: based on the existing ground test based on a spacecraft control system and various faults occurring in on-orbit flight, a method for verifying the robustness of the spacecraft control system with universality, standardization and high efficiency is provided by referring to a fault type, fault setting and injection method in engineering practice, and a robustness verification model and a ground simulation verification system which have the characteristics of sufficient fault type coverage (including constant-value type, linear type and nonlinear type faults), uniform fault setting form, contribution to solidification of empirical knowledge and the like are constructed by adopting a modeling concept.
The technical solution of the invention is as follows:
a method for verifying robustness of a spacecraft control system based on a model comprises the following steps:
(1) establishing a single-machine level or system level fault characterization model f (t) as follows:
f(t)＝(a0+a1t+a2t2+a3t3+…+amtm)
in the formula, a0,a1,…,amIs a polynomial coefficient, m is an order, a0,a1,…,amM is obtained by polynomial fitting of actual measurement data such as ground test data, on-orbit operation data and the like, and further different fault representations are configured; for a constant value fault, the polynomial order m is 0, and for a linear fault, the polynomial order m is 1; for nonlinear faults, determining the polynomial order according to the complexity of a fitting fault characterization curve, wherein m generally does not exceed 9, t is a time variable of the polynomial and is used for calculating linear and nonlinear fault characterizations related to time;
(2) constructing a robustness verification model Y, wherein the input of the robustness verification model is a single machine model to be verified or system-level output, and accessing the model to a control system in a serial mode for robustness verification;
Y＝s×u(T0)×f(t)+(1-s×u(T0))×z(t)
where z (T) is the stand-alone or system level output to be verified, u (T)0) As a function of time of occurrence of the fault, i.e. time of occurrence of the fault T0The unit step function completes the configuration of the fault occurrence time, s is a robustness verification mark, if s is 0, the robustness verification is not performed, and then the robustness verification model outputs Y (z) (t). If s is 1, the robustness verification is performed, and then the robustness verification model outputs Y ═ f (t);
(3) constructing parameter configuration vector K ═ s, T of robustness verification model0,a0,a1,…,am]From the robustness verification flag s, the failure occurrence time T0And polynomial coefficient a0,a1,…,amThe method comprises the steps of (1) realizing the representation of different faults by a verification model in a parameter configuration mode;
the parameter setting steps of the parameter configuration vector K of the robustness verification model are as follows:
the first step, according to whether robustness verification is carried out, the value of a robustness verification mark s in the parameter configuration vector K is determined, and if robustness verification is not carried out, the value of the robustness verification mark s is set to be 0. At this time, the output of the robustness verification model is Y ═ z (t), the subsequent steps of other parameter configuration are skipped, if robustness verification is carried out, the value of the robustness verification mark s is set to 1, and the subsequent parameter configuration steps are continued;
secondly, determining the fault occurrence time T in the parameter configuration vector K according to the time corresponding to the fault occurrence working condition to be verified0When the system time is less than the fault occurrence time T0If yes, outputting the robustness verification model as Y ═ z (t), otherwise, outputting the robustness verification model as Y ═ f (t);
thirdly, determining polynomial parameters a in the parameter configuration vector K according to different fault types0,a1,…,amThe configuration process of the parameter vector K is completed, and for constant-value faults including zero-value faults, saturation faults and the like, the polynomial parameter a is used0Is set to the constant value of the fault, a1,…,amThe value of (d) is set to 0. For time-dependent linear faults, the polynomial parameter a is set0And a1Is set to a corresponding value describing a linear fault, a2,…,amIs set to 0, if a non-linear fault is configured, the non-linear fault characterization to be configured is first specified, and the source of the fault characterization data may be ground test data, test data or on-track operation data. Determining polynomial parameters a by polynomial fitting to fault characterization data0,a1,…,amA value of (d);
(4) the robustness verification model and the parameter configuration vector are used for constructing a robustness verification model matrix and a configuration parameter matrix based on a single fault working condition of a single spacecraft, and the application of the robustness verification model and the configuration parameter matrix is expanded to robustness verification of multiple faults of multiple spacecrafts:
Yi×j＝[Y11,Y12,…,Y1j；…；Yi1,Yi2,…,Yij]
Ki×j＝[K11,K12,…,K1j；…；Ki1,Ki2,…,Kij]
robustness verification modelMatrix Yi×jThe robustness verification model can cover various single-machine-level and system-level robustness of a plurality of spacecrafts, wherein i represents the number of covered spacecrafts, and j represents the number of different single-machine or system-level fault conditions of a single involved spacecraft. Configuration parameter matrix Ki×jAnd Yi×jCorrespondingly, the parameter configuration vectors of a plurality of spacecrafts and a plurality of single-machine-level and system-level robustness verification models are covered. And based on a parameter configuration vector K configuration method, completing the unified setting of multiple faults of the multiple spacecrafts by configuring a parameter matrix.
Compared with the prior art, the invention has the beneficial effects that:
(1) the robustness verification method completely decouples the robustness verification model from each model of the control system by adopting a modeled robustness verification mode, and has strong universality. The robustness verification model is accessed to the control system in a serial mode, unified configuration of system faults and single machine faults is completed in a parameter configuration mode, fault setting is flexible, clear and definite, and fault knowledge solidification is facilitated.
(2) The fault characterization based on polynomial description not only can cover common fault types in engineering practice such as constant value, jump, linear slow change and the like, but also meets the setting requirement of complex nonlinear slow change faults, and realizes more sufficient coverage on the fault types.
(3) The invention adopts a matrix type model management and parameter configuration mode to form multi-fault robustness verification capability for multi-configuration combined spacecraft or combination of a plurality of spacecrafts.
(4) A method for verifying the robustness of a spacecraft control system based on a model is provided, which is based on the existing ground test of the spacecraft control system and various faults occurring in on-orbit flight and refers to a fault type, fault setting and injection mode method in engineering practice, and provides a method for verifying the robustness of the spacecraft control system with universality, standardization and high efficiency.
Drawings
FIG. 1 is a diagram of a robustness verification model architecture of the method of the present invention;
FIG. 2 is a schematic diagram of a robustness verification method of the present invention;
FIG. 3 is a simulation diagram of the fault gyro robustness verification model output;
FIG. 4 is a diagram of an output simulation of a momentum wheel friction torque increase fault robustness verification model.
Detailed Description
The invention is described in further detail below with reference to the figures and specific embodiments.
The invention relates to a robustness verification method of a spacecraft control system based on a model, which adopts a matrix type model management and parameter configuration mode to realize the unified setting of a plurality of spacecrafts and various faults. Different from the traditional robustness verification method of directly and manually counting inside or outside the model, the invention carries out robustness verification based on the model, solidifies the prior experience and knowledge, and promotes the standardization, normalization and high efficiency of robustness verification. A polynomial method is adopted to describe fault representation, a robustness verification model and a ground simulation verification system are constructed, full coverage of single-level and system-level fault types covered by the existing verification method is achieved, and good adaptability is achieved for complex nonlinear fault setting. As shown in FIG. 1, the robustness verification model in the method of the present invention is divided into a single-level fault verification model and a system-level fault verification model. The single-machine fault verification model is divided into sensor fault verification models by a single-machine type, and specifically comprises fault verification models of on-satellite measurement sensors such as gyros and star sensors, and fault verification models of actuating mechanisms, and specifically comprises fault verification models of on-satellite actuating mechanisms such as momentum wheels and thrusters.
The invention is further illustrated by the following figures and examples.
A method for verifying robustness of a spacecraft control system based on a model comprises the following steps:
(1) establishing a single-machine level or system level fault characterization model f (t) as follows:
f(t)＝(a0+a1t+a2t2+a3t3+…+amtm)
in the formula, a0,a1,…,amIs a polynomial coefficient, m is an order, a0,a1,…,amM is obtained by polynomial fitting of actual measurement data such as ground test data, on-orbit operation data and the like, and further different fault representations are configured; for a constant value fault, the polynomial order m is 0, and for a linear fault, the polynomial order m is 1; for nonlinear faults, determining the polynomial order according to the complexity of a fitting fault characterization curve, wherein m generally does not exceed 9, t is a time variable of the polynomial and is used for calculating linear and nonlinear fault characterizations related to time;
(2) constructing a robustness verification model Y, wherein the input of the robustness verification model is a single-machine model to be verified or system-level output, and accessing the model to a control system in a serial manner for robustness verification, as shown in FIG. 2;
Y＝s×u(T0)×f(t)+(1-s×u(T0))×z(t)
where z (T) is the stand-alone or system level output to be verified, u (T)0) As a function of time of occurrence of the fault, i.e. time of occurrence of the fault T0The unit step function completes the configuration of the fault occurrence time, s is a robustness verification mark, if s is 0, the robustness verification is not performed, and then the robustness verification model outputs Y (z) (t). If s is 1, the robustness verification is performed, and then the robustness verification model outputs Y ═ f (t);
(3) constructing parameter configuration vector K ═ s, T of robustness verification model0,a0,a1,…,am]From the robustness verification flag s, the failure occurrence time T0And polynomial coefficient a0,a1,…,amThe method comprises the steps of (1) realizing the representation of different faults by a verification model in a parameter configuration mode;
the parameter setting steps of the parameter configuration vector K of the robustness verification model are as follows:
the first step, according to whether robustness verification is carried out, the value of a robustness verification mark s in the parameter configuration vector K is determined, and if robustness verification is not carried out, the value of the robustness verification mark s is set to be 0. At this time, the output of the robustness verification model is Y ═ z (t), the subsequent steps of other parameter configuration are skipped, if robustness verification is carried out, the value of the robustness verification mark s is set to 1, and the subsequent parameter configuration steps are continued;
secondly, determining the fault occurrence time T in the parameter configuration vector K according to the time corresponding to the fault occurrence working condition to be verified0When the system time is less than the fault occurrence time T0If yes, outputting the robustness verification model as Y ═ z (t), otherwise, outputting the robustness verification model as Y ═ f (t);
thirdly, determining polynomial parameters a in the parameter configuration vector K according to different fault types0,a1,…,amThe configuration process of the parameter vector K is completed, and for constant-value faults including zero-value faults, saturation faults and the like, the polynomial parameter a is used0Is set to the constant value of the fault, a1,…,amThe value of (d) is set to 0. For time-dependent linear faults, the polynomial parameter a is set0And a1Is set to a corresponding value describing a linear fault, a2,…,amIs set to 0, if a non-linear fault is configured, the non-linear fault characterization to be configured is first specified, and the source of the fault characterization data may be ground test data, test data or on-track operation data. Determining polynomial parameters a by polynomial fitting to fault characterization data0,a1,…,amA value of (d);
(4) the robustness verification model and the parameter configuration vector are used for constructing a robustness verification model matrix and a configuration parameter matrix based on a single fault working condition of a single spacecraft, and the application of the robustness verification model and the configuration parameter matrix is expanded to robustness verification of multiple faults of multiple spacecrafts:
Yi×j＝[Y11,Y12,…,Y1j；…；Yi1,Yi2,…,Yij]
Ki×j＝[K11,K12,…,K1j；…；Ki1,Ki2,…,Kij]
robustness verification model matrix Yi×jThe robustness verification model can cover various single-machine-level and system-level robustness of a plurality of spacecrafts, wherein i represents the number of covered spacecrafts, and j represents the number of different single-machine or system-level fault conditions of a single involved spacecraft. Configuration parameter matrix Ki×jAnd Yi×jCorrespondingly, the parameter configuration vectors of a plurality of spacecrafts and a plurality of single-machine-level and system-level robustness verification models are covered. And based on a parameter configuration vector K configuration method, completing the unified setting of multiple faults of the multiple spacecrafts by configuring a parameter matrix.
A typical attitude control system is taken as an example. The attitude control system comprises a measuring sensor which comprises two star sensors and three mechanical gyros which are normally arranged on three shafts of the body system. The actuating mechanism is three momentum wheels which are positively arranged on three shafts of the system. Accessing the robustness verification model into an attitude control system, and constructing a robustness verification model matrix and a configuration parameter matrix for a single spacecraft: y is1×14＝[Y1,Y2,…,Y14]、K1×14＝[K1,K2,…,K14]. Wherein Y is1×14Y in 14 elements of (1)1、Y2、Y3Respectively, three gyros under the system and being arranged on X, Y, Z axes4、Y5For a robustness verification model of two star sensors, Y6、Y7、Y8Respectively, three momentum wheels which are arranged on X, Y, Z shafts under the system are robustness verification models, Y9、Y10、Y11Attitude angle system level robustness verification model, Y, of spacecraft X, Y, Z axis respectively12、Y13、Y14Attitude angular velocity system-level robustness verification models of the spacecraft X, Y, Z axes, respectively. K1×14The 14 elements in (a) are configuration parameter vectors corresponding to different fault models, respectively.
Y1Robustness verification model for X-axis gyroscope, K1Parameter vectors are configured for the system, and the output of the gyro before the fault is 0.1 degrees/s, and the X-axis gyro is assumed to have zero-value fault with zero output when the system runs to 2000 s. Then, model Y is verified for robustness1Parameter configuration vector K of1The settings were as follows: setting the value of a robustness verification mark s to 1 and setting a fault occurrence time parameter T0The values of (a) and (b) are set to 2000 and the values of the polynomial parameters are all set to 0. Thus the parameter configuration vector K1＝[1,2000,0,0,…,0]。
Y6Robustness verification model for X-axis momentum wheel, K6The parameter vector is configured for the method, and if a momentum wheel common nonlinear gradual change fault that the wheel control voltage exceeds the threshold value due to the increase of the friction torque of the X-axis momentum wheel occurs from 0s of system operation, the friction torque of the X-axis momentum wheel is 0.003Nm in a normal working state, and the wheel control voltage exceeds the threshold value after 10000s of nonlinear increase. Then, model Y is verified for robustness6Parameter configuration vector K of6The settings were as follows: setting the value of a robustness verification mark s to 1 and setting a fault occurrence time parameter T0Is set to 0, and polynomial parameters [ -1.477 × 10 ] determined based on polynomial fitting-41,6.876×10-37,-1.334×10-32，1.381×10-28,-7.923×10-25,2.130×10-21]. Thus the parameter configuration vector K6＝[1,0,-1.477×10-41,6.876×10-37,-1.334×10-32，1.381×10-28,-7.923×10-25,2.130×10-21]。
Setting the value of a robustness verification mark s in other parameter configuration vectors which do not have faults to be 0, and then configuring a parameter matrix K1×14And (4) injecting a robustness verification model to complete the parameter configuration of the robustness verification model. And carrying out robustness verification simulation on the attitude control system according to the configuration, wherein an output fault simulation curve of the X-axis gyro robustness verification model is shown in FIG. 3. The output fault simulation curve of the X-axis momentum wheel robustness verification model is shown in FIG. 4.

Claims (10)

1. A method for verifying robustness of a spacecraft control system based on a model is characterized by comprising the following steps:
(1) establishing a single-machine level or system level fault characterization model f (t) as follows:
f(t)＝(a0+a1t+a2t2+a3t3+…+amtm)
in the formula, a0,a1,…,amIs a polynomial coefficient, m is an order, and t is a time variable of the polynomial;
(2) a robustness verification model Y was constructed as follows:
Y＝s×u(T0)×f(t)+(1-s×u(T0))×z(t)
where z (T) is the stand-alone or system level output to be verified, u (T)0) As a function of time of occurrence of the fault, i.e. time of occurrence of the fault T0The unit step function completes the configuration of the fault occurrence time, and s is a robustness verification mark;
(3) constructing parameter configuration vector K ═ s, T of robustness verification model0,a0,a1,…,am]；
(4) Constructing a robustness verification model matrix and a configuration parameter matrix according to the steps (1) to (3) as follows:
Yi×j＝[Y11,Y12,…,Y1j；…；Yi1,Yi2,…,Yij]
Ki×j＝[K11,K12,…,K1j；…；Ki1,Ki2,…,Kij]。
2. the model-based spacecraft control system robustness verification method of claim 1, wherein: in the step (1), a0,a1,…,amAnd m is obtained by polynomial fitting of ground test data, test data and measured data of on-orbit operation data.
3. The model-based spacecraft control system robustness verification method of claim 1, wherein: in the step (1), for a constant-value fault, the polynomial order m is 0.
4. The model-based spacecraft control system robustness verification method of claim 1, wherein: in the step (1), for a linear fault, the polynomial order m is 1.
5. The model-based spacecraft control system robustness verification method of claim 1, wherein: in the step (1), m is less than or equal to 9 for the nonlinear fault.
6. The model-based spacecraft control system robustness verification method of claim 1, wherein: in the step (2), if s is 0, it indicates that the robustness verification is not performed, and at this time, the robustness verification model outputs Y ═ z (t).
7. The model-based spacecraft control system robustness verification method of claim 1, wherein: in the step (2), if s is 1, it indicates that robustness verification is performed, and at this time, the robustness verification model outputs Y ═ f (t).
8. The model-based spacecraft control system robustness verification method of claim 1, wherein: in the step (3), the parameter setting step of the parameter configuration vector K of the robustness verification model is as follows:
the first step, according to whether robustness verification is carried out, the value of a robustness verification mark s in a parameter configuration vector K is determined, if robustness verification is not carried out, the value of the robustness verification mark s is set to be 0, at the moment, the output of a robustness verification model is Y (z) (t), the subsequent steps of other parameter configuration are skipped, if robustness verification is carried out, the value of the robustness verification mark s is set to be 1, and the subsequent parameter configuration steps are continued;
secondly, determining faults in the parameter configuration vector K according to the time corresponding to the fault occurrence working condition to be verifiedTime of occurrence of fault T0When the system time is less than the fault occurrence time T0If yes, outputting the robustness verification model as Y ═ z (t), otherwise, outputting the robustness verification model as Y ═ f (t);
thirdly, determining polynomial parameters a in the parameter configuration vector K according to different fault types0,a1,…,amThe configuration process of the parameter vector K is completed, and for constant-value faults including zero-value faults and saturation faults, the polynomial parameter a is used0Is set to the constant value of the fault, a1,…,amIs set to 0, and for time-dependent linear faults, the polynomial parameter a is set to0And a1Is set to a corresponding value describing a linear fault, a2,…,amIf the nonlinear fault is configured, firstly, the nonlinear fault representation to be configured is determined, and the source of the fault representation data can be ground test data, test data or on-orbit operation data; determining polynomial parameters a by polynomial fitting to fault characterization data0,a1,…,amThe value of (c).
9. The model-based spacecraft control system robustness verification method of claim 1, wherein: in the step (4), the robustness verification model matrix Yi×jThe robustness verification model comprises multiple single-unit-level and system-level robustness verification models covering multiple spacecrafts, wherein i represents the number of covered spacecrafts, and j represents the number of different single-unit or system-level fault conditions of a single involved spacecraft.
10. The model-based spacecraft control system robustness verification method of claim 1, wherein: in the step (4), a parameter matrix K is configuredi×jAnd Yi×jCorrespondingly, parameter configuration vectors of a plurality of spacecrafts and a plurality of single-level and system-level robustness verification models are covered, and based on a parameter configuration vector K configuration method, unified setting of a plurality of faults of the spacecrafts is completed through configuration of a parameter matrix.
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