State estimation method, device, equipment and medium for flat-panel satellite

Abstract

The present disclosure relates to the field of spacecraft state estimation technology, and discloses a state estimation method, device, equipment and medium for a flat-panel satellite, which is used to solve the problem that the state and disturbance torque of a flat-panel satellite cannot be estimated simultaneously. The method includes: establishing a related coordinate system of the flat-panel satellite and determining a system state equation; separating the angular velocity channel in the system state equation and obtaining nonlinear angular velocity observations; determining a local linearization equation based on the observations and the system state equation; calculating the initial dynamic disturbance torque and the initial estimation error covariance matrix based on the disturbance transfer equation in the local linearization equation; determining the reference state estimation value and the reference estimation error covariance matrix of the target dynamic disturbance torque, the intermediate estimation error covariance matrix, the coupling coefficient, and the system state parameters in the non-interference state; and determining the target state estimation value and the target estimation error state matrix based on the above. The state and disturbance torque of the flat-panel satellite can be estimated simultaneously.

Description

Technical Field

[0001] The embodiments of the present disclosure relate to the technical field of spacecraft state estimation, and in particular to a state estimation method, device, equipment and medium for a flat-panel satellite. Background Art

[0002] Flat-panel satellites, due to their high-density stacking on the fairing, can meet the demand for launching small satellites in a "multiple satellites in one rocket" manner with a smaller volume, and can carry out multi-person simultaneous operations in the small satellite assembly process, achieving rapid assembly and mass production.

[0003] Flat-panel satellites are mainly used for low-orbit communications and are greatly affected by environmental torques. The main problem in estimating the attitude of flat-panel satellites is the interference of aerodynamic torques. Most existing methods obtain interference estimation results by establishing interference observers, but cannot achieve simultaneous estimation of flat-panel satellite states and interference torques. Summary of the invention

[0004] In view of this, the embodiments of the present disclosure are intended to provide a method, apparatus, device and medium for estimating the state of a flat-panel satellite, which can simultaneously estimate the state and disturbance torque of the flat-panel satellite.

[0005] The technical solution of the embodiment of the present disclosure is implemented as follows:

[0006] In a first aspect, an embodiment of the present disclosure provides a state estimation method for a flat-panel satellite, comprising:

[0007] Establishing a relevant coordinate system of the flat-panel satellite, and determining a system state equation including system state parameters of the flat-panel satellite based on the relevant coordinate system;

[0008] Separating the angular velocity channel in the system state equation to obtain an angular velocity state equation, and acquiring a nonlinear angular velocity observation value based on the angular velocity state equation;

[0009] Determine a local linearization equation according to the nonlinear angular velocity observation value and the system state equation;

[0010] Calculate the initial dynamic disturbance torque and the initial estimation error covariance matrix based on the disturbance transfer equation in the local linearization equation;

[0011] Determine a target dynamic disturbance torque, an intermediate estimation error covariance matrix, a coupling coefficient, a reference state estimation value of the system state parameter in a non-interference state, and a reference estimation error covariance matrix according to the initial dynamic disturbance torque and the initial estimation error covariance matrix;

[0012] A target state estimation value and a target estimation error state matrix are determined based on the coupling coefficient, the target dynamic disturbance torque, the intermediate estimation error covariance matrix, the reference state estimation value and the reference estimation error covariance matrix.

[0013] In some examples, establishing a relevant coordinate system of the flat-panel satellite and determining a system state equation including system state parameters of the flat-panel satellite based on the relevant coordinate system includes:

[0014] Establishing a body coordinate system, an inertial coordinate system, and a target coordinate system of the flat-panel satellite, wherein when the flat-panel satellite is in a desired posture, the target coordinate system coincides with the body coordinate system;

[0015] Determine the attitude kinematic equation and the attitude dynamic equation based on the attitude of the target coordinate system and the body coordinate system;

[0016] According to the posture kinematic equation and the posture dynamic equation, a state equation including system state parameters is constructed.

[0017] In some examples, the system state equation is discretized to obtain a discretized state equation;

[0018] Separating the angular velocity channel in the discretized state equation to obtain an angular velocity state equation, and designing a nonlinear sliding mode observer based on the angular velocity state equation;

[0019] The nonlinear angular velocity observation value is obtained based on the nonlinear sliding mode observer.

[0020] In some examples, determining a local linearization equation according to the nonlinear angular velocity observation value and the system state equation includes:

[0021] The discretized state equation is expanded using the nonlinear angular velocity observation value as a Taylor expansion point to obtain the local linearized equation.

[0022] In some examples, determining a target dynamic disturbance torque, an intermediate estimation error covariance matrix, a coupling coefficient, a reference state estimation value of the system state parameter in a non-interference state, and a reference estimation error covariance matrix according to the initial dynamic disturbance torque and the initial estimation error covariance matrix includes:

[0023] Based on the initial dynamic disturbance torque and the initial estimation error covariance matrix, determining the target dynamic disturbance torque and the intermediate estimation error covariance matrix using a dynamic disturbance algorithm;

[0024] Based on the local linearization equation and the non-interference state estimation algorithm, the reference state estimation value and the reference estimation error covariance matrix are calculated using the initial dynamic interference torque and the initial estimation error covariance matrix;

[0025] Based on the local linearization equation, the coupling coefficient is determined using the initial dynamic disturbance torque and an initial estimation error covariance matrix.

[0026] In some examples, determining a target state estimate value and a target estimation error state matrix based on the coupling coefficient, the target dynamic disturbance torque, the intermediate estimation error covariance matrix, the reference state estimate value, and the reference estimation error covariance matrix includes:

[0027] Determine a first mapping relationship between the coupling coefficient, the reference state estimation value, the target dynamic interference torque and the target state estimation value, and determine the target state estimation value based on the first mapping relationship by using the coupling coefficient, the target dynamic interference torque and the reference state estimation value;

[0028] Determine a second mapping relationship among the coupling coefficient, the reference estimation error covariance matrix, the intermediate estimation error covariance matrix and the target estimation error state matrix, and based on the second mapping relationship, determine the target estimation error state matrix using the coupling coefficient and the reference estimation error covariance matrix.

[0029] In some examples, the calculating the initial dynamic disturbance torque and the initial estimation error covariance matrix based on the disturbance transfer equation in the local linearization equation includes:

[0030] extracting a disturbance transfer equation from the local linearized equation;

[0031] Under the Bayesian filtering framework, the interference transfer equation is recursively deduced in one step to obtain the interference integral calculation equation of the initial dynamic interference torque and the matrix integral calculation equation corresponding to the initial estimation error covariance matrix;

[0032] The interference integral calculation equation and the matrix integral calculation equation are solved to obtain the initial dynamic interference torque and the initial estimation error covariance matrix.

[0033] In a second aspect, an embodiment of the present disclosure provides a state estimation device for a flat-panel satellite, including:

[0034] An establishing module, used for establishing a relevant coordinate system of the flat-panel satellite, and determining a system state equation including system state parameters of the flat-panel satellite based on the relevant coordinate system;

[0035] An observation module, used for separating the angular velocity channel in the system state equation to obtain the angular velocity state equation, and obtaining a nonlinear angular velocity observation value corresponding to the angular velocity based on the angular velocity state equation;

[0036] An equation determination module, used for determining a local linearization equation according to the nonlinear angular velocity observation value and the system state equation;

[0037] A calculation module, used for calculating an initial dynamic disturbance torque and an initial estimation error covariance matrix based on a disturbance transfer equation in the local linearization equation;

[0038] A parameter determination module, used to determine a coupling coefficient, a reference state estimation value of the system state parameter in a non-interference state, and a reference estimation error covariance matrix according to the initial dynamic interference torque and the initial estimation error covariance matrix;

[0039] An estimation module is used to determine a target state estimation value, a target estimation error state matrix and a target dynamic disturbance torque based on the coupling coefficient, the reference state estimation value and a reference estimation error covariance matrix.

[0040] In a third aspect, an embodiment of the present disclosure provides an electronic device, comprising: a processor and a memory; the processor is used to execute instructions stored in the memory to implement the state estimation method of the flat-panel satellite described in the first aspect.

[0041] In a fourth aspect, an embodiment of the present disclosure provides a computer storage medium, wherein the storage medium stores at least one instruction, and the at least one instruction is used to be executed by a processor to implement the state estimation method of the flat-panel satellite as described in the first aspect.

[0042] The disclosed embodiments provide a state estimation method, device, equipment and medium for a flat-panel satellite; on the one hand, the initial dynamic interference torque and the initial estimation error covariance matrix are calculated based on the interference transfer equation in the local linearization equation; the coupling coefficient, the reference state estimation value of the system state parameter in the interference-free state and the reference estimation error covariance matrix are determined according to the initial dynamic interference torque and the initial estimation error covariance matrix; the target state estimation value, the target estimation error state matrix and the target dynamic interference torque are determined based on the coupling coefficient, the reference state estimation value and the reference estimation error covariance matrix. The state and interference torque of the flat-panel satellite can be estimated at the same time. On the other hand, the angular velocity channel in the system state equation is separated to obtain the angular velocity state equation, and the nonlinear angular velocity observation value is obtained based on the angular velocity state equation; the local linearization equation is determined according to the nonlinear angular velocity observation value and the system state equation. When the local linearization equation is obtained, the nonlinear factor is taken into account, which can improve the estimation accuracy of the interference torque. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 A flowchart of a state estimation method for a flat-panel satellite provided in an embodiment of the present disclosure.

[0044] Figure 2 A flowchart for obtaining a system state equation is provided in an embodiment of the present disclosure.

[0045] Figure 3 A flowchart for obtaining nonlinear angular velocity observation values ​​is provided in an embodiment of the present disclosure.

[0046] Figure 4 A flowchart for determining a reference state estimate and a reference estimation error covariance matrix is ​​provided in an embodiment of the present disclosure.

[0047] Figure 5 A flowchart of determining a target estimation error state matrix is ​​provided in an embodiment of the present disclosure.

[0048] Figure 6 It is a schematic diagram of an angular velocity simulation curve in the related art.

[0049] Figure 7 An angular velocity simulation curve diagram provided in an embodiment of the present disclosure.

[0050] Figure 8 It is a schematic diagram of a simulation curve of the attitude angle in the related art.

[0051] Fig. 9 A schematic diagram of a simulation curve of an attitude angle provided in an embodiment of the present disclosure.

[0052] Fig.10 It is a schematic diagram of a simulation curve of interference in the related art.

[0053] Fig.11 A schematic diagram of a simulation curve of interference provided in an embodiment of the present disclosure.

[0054] Fig.12 A framework diagram of a state estimation device for a flat-panel satellite provided in an embodiment of the present disclosure.

[0055] Fig.13 A schematic diagram of the structure of an electronic device provided in an embodiment of the present disclosure.

[0056] The above drawings show clear embodiments of the present disclosure, which will be described in more detail below. These drawings and text descriptions are not intended to limit the scope of the present disclosure in any way, but to illustrate the concepts of the present disclosure to those skilled in the art by referring to specific embodiments. DETAILED DESCRIPTION

[0057] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present disclosure. Instead, they are merely examples of devices and methods consistent with some aspects of the present disclosure as detailed in the appended claims.

[0058] Flat-panel satellites, due to their high-density stacking on the fairing, can meet the demand for launching small satellites in a "multiple satellites in one rocket" manner with a smaller volume, and can carry out multi-person simultaneous operations in the small satellite assembly process, achieving rapid assembly and mass production.

[0059] There are two design ideas for flat-panel satellites in related technologies: one is a satellite platform composed of an integrally molded load-bearing frame with a hollow structure, and the equipment load is dispersedly carried on the load-bearing frame; the other is a flat-panel satellite composed of a plate-type main structure and a foldable solar sail panel.

[0060] Flat-plate satellites are mainly used for low-orbit communications and are greatly affected by environmental torques. For the attitude estimation of flat-plate satellites, the main problem is the interference of aerodynamic torques. Most existing methods obtain interference estimation results by establishing interference observers, and cannot achieve simultaneous estimation of flat-plate satellite attitude and interference. In addition, since the interference caused by environmental torques has the characteristics of dynamic changes during the satellite attitude maneuvers, the established interference model has strong nonlinearity. Conventional nonlinear filtering methods, such as extended Kalman filtering, have large truncation errors, which leads to a decrease in interference estimation accuracy and affects the satellite attitude estimation results.

[0061] Based on this, the present disclosure first provides a state estimation method for a flat-panel satellite, referring to Figure 1 , which can be applied to the above-mentioned electronic device, wherein the state estimation method of the above-mentioned flat-panel satellite may include steps S110 to S160.

[0062] In step S110, a relevant coordinate system of the flat-panel satellite is established, and a system state equation including system state parameters of the flat-panel satellite is determined based on the relevant coordinate system.

[0063] In step S120, the angular velocity channel in the system state equation is separated to obtain the angular velocity state equation, and the nonlinear angular velocity observation value is obtained based on the angular velocity state equation.

[0064] In step S130, a local linearization equation is determined based on the nonlinear angular velocity observation value and the system state equation.

[0065] In step S140, an initial dynamic disturbance torque and an initial estimation error covariance matrix are calculated based on the disturbance transfer equation in the local linearization equation.

[0066] In step S150, the target dynamic disturbance torque, the intermediate estimation error covariance matrix, the coupling coefficient, the reference state estimation value of the system state parameters in the interference-free state and the reference estimation error covariance matrix are determined according to the initial dynamic disturbance torque and the initial estimation error covariance matrix.

[0067] In step S160, a target state estimation value and a target estimation error state matrix are determined based on the coupling coefficient, the target dynamic disturbance torque, the intermediate estimation error covariance matrix, the reference state estimation value and the reference estimation error covariance matrix.

[0068] The state estimation method of the flat-panel satellite provided by the embodiment of the present disclosure, on the one hand, calculates the initial dynamic interference torque and the initial estimation error covariance matrix based on the interference transfer equation in the local linearization equation; determines the coupling coefficient, the reference state estimation value of the system state parameter in the interference-free state and the reference estimation error covariance matrix based on the initial dynamic interference torque and the initial estimation error covariance matrix; determines the target state estimation value, the target estimation error state matrix and the target dynamic interference torque based on the coupling coefficient, the reference state estimation value and the reference estimation error covariance matrix. The state and interference torque of the flat-panel satellite can be estimated at the same time. On the other hand, the angular velocity channel in the system state equation is separated to obtain the angular velocity state equation, and the nonlinear angular velocity observation value is obtained based on the angular velocity state equation; the local linearization equation is determined based on the nonlinear angular velocity observation value and the system state equation. When obtaining the local linearization equation, the nonlinear factor is taken into account, which can improve the estimation accuracy of the interference torque.

[0069] The above steps are described in detail below.

[0070] In step S110, a relevant coordinate system of the flat-panel satellite is established, and a system state equation including system state parameters of the flat-panel satellite is determined based on the relevant coordinate system.

[0071] In some examples, reference Figure 2 When obtaining the above system state equation, steps S210 to S230 may be included.

[0072] In step S210, a body coordinate system, an inertial coordinate system, and a target coordinate system of the flat-panel satellite are established, wherein when the flat-panel satellite processes a desired attitude, the target coordinate system coincides with the body coordinate system.

[0073] In an exemplary embodiment of the present disclosure, the above-mentioned related coordinate system may include a flat-panel satellite body coordinate system. b Xb Y b Z b , inertial coordinate system O i X i Y i Z i And the target coordinate system O t X t Y t Z t , where the body coordinate system O b X b Y b Z b The coordinate origin is located at the satellite's center of mass when the flat plate is X b The Y axis points to the direction of the satellite velocity. b The axis is perpendicular to the longitudinal symmetry plane, and the three axes form a right-handed system; the inertial coordinate system O i X i Y i Z i The origin of the coordinate system is located at a characteristic point in the inertial space, X i The axis is the inertial orientation direction, and the three axes are orthogonal to form a right-hand system; the target coordinate system O t X t Y t Z t The origin of the coordinate system is located at the center of mass of the flat-panel satellite. When the flat-panel satellite reaches the desired target attitude, the target coordinate system coincides with the body coordinate system.

[0074] In step S220, the posture kinematic equation and the posture dynamic equation are determined based on the postures of the target coordinate system and the body coordinate system.

[0075] The angle between the target coordinate system and the body coordinate system, that is, the Euler angle, is used as the posture parameter to determine the coordinate transformation matrix of the body coordinate system relative to the target coordinate system. Specifically, the Euler angle is recorded as , the coordinate transformation matrix of the body coordinate system relative to the target coordinate system under the zxy conversion order is:

[0076]

[0077] Where:

[0078]

[0079]

[0080]

[0081] Then, the attitude kinematics equation of the flat-panel satellite body coordinate system relative to the target coordinate system can be established based on the above coordinate transformation matrix. The attitude kinematics equation is as follows:

[0082]

[0083] Where: It is the angular velocity of the flat-panel satellite body coordinate system relative to the target coordinate system.

[0084] Next, the attitude dynamics model of the flat-panel satellite can be obtained from the rigid spacecraft Euler equation as follows:

[0085]

[0086] Where: is the moment of inertia of the flat-panel satellite; is the angular velocity of the flat-panel satellite body coordinate system relative to the inertial coordinate system; is the angular momentum of the actuator such as the flywheel; is the torque of the actuator acting on the satellite body, ; is the angular velocity of the target coordinate system relative to the inertial coordinate system, is the disturbance torque on the satellite body.

[0087] In step S230, a state equation including system state parameters is constructed according to the posture kinematic equation and the posture dynamic equation.

[0088] In some examples, when the flat-panel satellite unfolds its solar sails in the low-orbit working phase, the satellite has a large surface-to-mass ratio and the aerodynamic drag it is subject to is much greater than other environmental forces. Therefore, the environmental interference force is approximately simplified to aerodynamic drag, and only the influence of aerodynamic torque on the satellite attitude estimation result during the attitude control process of the flat-panel satellite is considered, that is,

[0089]

[0090] Where: is the disturbance torque, is the gravitational gradient force, is the solar pressure, is the geomagnetic force, For pneumatic power, It is the interference force arm.

[0091] The calculation expression of aerodynamic force is:

[0092]

[0093] Where: is the drag coefficient; is the atmospheric density; is the headwater area; is the velocity vector of the oncoming surface relative to the incident flow; is the normal vector of the atmospheric frontal surface, For gas power.

[0094] From the above analysis, it can be seen that the disturbance torque on the satellite body is mainly aerodynamic torque, which is dynamic.

[0095] In some example implementations of the present disclosure, a state equation including system state parameters may be obtained based on the above-mentioned posture kinematics equation and posture dynamics equation. Specifically, first, the above-mentioned posture kinematics equation and posture dynamics equation may be integrated to obtain the following equation:

[0096]

[0097] Then, the system state is defined based on the above integrated equation. Specifically, the system state can be:

[0098]

[0099] Then, the system state equation of the flat-panel satellite attitude control system can be obtained by derivation of the above system state with respect to time. Specifically, the system state equation is expressed as:

[0100]

[0101] Where: , , , represents the dynamic disturbance of the flat-panel satellite, that is, the aerodynamic moment , For control input.

[0102] Among them, the control input coefficient matrix and the interference coefficient matrix are:

[0103] ,

[0104] In step S120, the angular velocity channel in the system state equation is separated to obtain the angular velocity state equation, and the nonlinear angular velocity observation value is obtained based on the angular velocity state equation.

[0105] In some example embodiments, reference Figure 3 When the angular velocity channel in the system state equation is separated to obtain the angular velocity state equation, and the nonlinear angular velocity observation value is obtained based on the angular velocity state equation, steps S310 to S330 may be included.

[0106] In step S310, the system state equation is discretized to obtain a discretized state equation.

[0107] In this example implementation, the system state equation is discretized to obtain a discretized state equation at time k, which is:

[0108]

[0109] Where: is the system process noise; To measure noise; is a nonlinear dynamic disturbance function; is the interference process noise; is the attitude measurement value; measurement matrix , represents the 6-dimensional identity matrix, express The amount of control at the moment, express The control matrix of the moment, express The interference matrix at the moment.

[0110] In step S320, the angular velocity channel in the discretized state equation is separated to obtain the angular velocity state equation, and a nonlinear sliding mode observer is designed based on the angular velocity state equation.

[0111] In step S330, a nonlinear angular velocity observation value is obtained based on a nonlinear sliding mode observer.

[0112] remember , , the angular velocity channel in the flat-panel satellite attitude control system model with dynamic interference is separated and written in component form as follows:

[0113]

[0114] Where: is the i-th row of the control input coefficient matrix B; satisfy .

[0115] The nonlinear sliding mode observer of the angular velocity channel is designed for the flat-panel satellite attitude control system with dynamic interference as follows:

[0116]

[0117]

[0118]

[0119] in, . is the observed value of angular velocity.

[0120] parameter The design of depends on the second-order derivative of the unknown dynamic disturbance , if the second-order derivative is bounded, then take , so that it converges in a finite time.

[0121] In step S130, a local linearization equation is determined based on the nonlinear angular velocity observation value and the system state equation.

[0122] The angular velocity observation value obtained by the above observer As the Taylor expansion point of the flat-plate satellite attitude control system,

[0123]

[0124] In the formula, is the Euler angle estimate of the filter at the previous moment.

[0125] Will exist Taylor expansion is performed at the local linearization model:

[0126]

[0127] Where: ; for exist The remainder of the Taylor expansion; satisfy:

[0128]

[0129] express The state transfer matrix at time step one.

[0130] In step S140, an initial dynamic disturbance torque and an initial estimation error covariance matrix are calculated based on the disturbance transfer equation in the local linearization equation.

[0131] In an exemplary implementation of the present disclosure, the interference transfer equation may be first extracted from the local linearization equation. Specifically, the extracted interference transfer equation is:

[0132]

[0133] Then, the disturbance transfer equation can be recursively deduced in one step under the Bayesian filtering framework to obtain the disturbance integral calculation equation of the initial dynamic disturbance torque and the matrix integral calculation equation corresponding to the initial estimation error covariance matrix; specifically:

[0134] In the Bayesian filtering framework, the interference integral calculation equation and the matrix integral calculation equation are obtained after one step of recursion, where the interference integral calculation equation is:

[0135]

[0136] The matrix integral calculation equation is:

[0137]

[0138] in, is the initial dynamic disturbance torque, is the initial estimation error covariance matrix, for The corresponding covariance matrix.

[0139] Finally, the disturbance integral calculation equation and the matrix integral calculation equation can be solved to obtain the initial dynamic disturbance torque and the initial estimation error covariance matrix.

[0140] Specifically, set it as:

[0141]

[0142] For the components of the disturbance torque Abbreviated as , It can be expressed as a polynomial function through Taylor expansion, that is,

[0143]

[0144] Where: , n is the number of state quantities, is any non-negative integer representing the order.

[0145] For any polynomial function , the integral is as follows:

[0146]

[0147]

[0148] Where: is a non-negative integer; is satisfied all possible combinations of; is the i-th eigenvalue of the covariance matrix P; is satisfied The orthogonal matrix of yes of element; are polynomial coefficients that satisfy , I represents the integral result.

[0149] In step S150, the target dynamic disturbance torque, the intermediate estimation error covariance matrix, the coupling coefficient, the reference state estimation value of the system state parameters in the interference-free state and the reference estimation error covariance matrix are determined according to the initial dynamic disturbance torque and the initial estimation error covariance matrix.

[0150] In some example embodiments of the present disclosure, reference is made to Figure 4 , the above steps may include step S410 to step S430.

[0151] In step S410, based on the initial dynamic disturbance torque and the initial estimation error covariance matrix, a target dynamic disturbance torque and an intermediate estimation error covariance matrix are determined using a dynamic disturbance algorithm.

[0152] In some example implementations, after obtaining the above initial dynamic interference moment and the initial estimation error covariance matrix, a dynamic interference algorithm may be used to calculate a target dynamic interference moment and an intermediate estimation error covariance matrix based on the above dynamic interference moment and the initial estimation error covariance matrix. Specifically, the dynamic interference algorithm is as follows:

[0153]

[0154]

[0155]

[0156]

[0157]

[0158]

[0159]

[0160]

[0161]

[0162]

[0163]

[0164]

[0165]

[0166] in: is the initial dynamic disturbance torque, is the initial estimation error covariance matrix; Need to assign initial value ; Need to assign initial value ; Calculated by coupling relationship , , Obtained by locally linearizing the equation; Need to assign initial value , the specific value can be customized based on experience or user needs, and will not be described in detail in this example implementation; is the process noise covariance matrix, which is a known quantity. The specific value can be obtained based on user requirements or experimental data, so it will not be described here. , Determined by the sensor measurement principle, it is a known quantity; is the measurement noise covariance matrix, which is a known quantity; Need to assign initial value ; is the controlled quantity, which depends on the controller design. Need to assign initial value ; The locally linearized equation is obtained. is the target disturbance torque, is the intermediate estimation error covariance matrix. is the n-dimensional identity matrix.

[0167] In step S420, based on the local linearization equation and the non-interference state estimation algorithm, the reference state estimation value and the reference estimation error covariance matrix are calculated using the initial dynamic disturbance torque and the initial estimation error covariance matrix.

[0168] Specific:

[0169]

[0170]

[0171] in; is the reference state estimate, is the reference estimation error covariance matrix;

[0172] It should be noted that the assigned values ​​and known quantities can be obtained according to user needs or experimental data, and the specific values ​​are not described here.

[0173] In step S430, based on the local linearization equation, the coupling coefficient is determined using the initial dynamic disturbance torque and the initial estimation error covariance matrix.

[0174] In some examples, the coupling coefficient may be determined based on the local linearization equation using the initial dynamic disturbance torque and the initial estimation error covariance matrix. Specifically, the coupling coefficient may be calculated using the following formula:

[0175]

[0176]

[0177] in: is the coupling coefficient.

[0178] In step S160, a target state estimation value and a target estimation error state matrix are determined based on the coupling coefficient, the target dynamic disturbance torque, the intermediate estimation error covariance matrix, the reference state estimation value and the reference estimation error covariance matrix.

[0179] In some example embodiments, reference Figure 5 , the above steps may include step S510 to step S520.

[0180] In step S510, a first mapping relationship among the coupling coefficient, the reference state estimation value, the target dynamic interference torque and the target state estimation value is determined, and based on the first mapping relationship, the target state estimation value is determined using the coupling coefficient, the target dynamic interference torque and the reference state estimation value.

[0181] In this example implementation, a first mapping relationship between the coupling coefficient, the target dynamic disturbance torque reference state estimation value, and the target state estimation value may be determined first, where the first mapping relationship may be:

[0182]

[0183] in, is the estimated value of the target state.

[0184] After obtaining the first mapping relationship, the target state estimation value can be calculated based on the first mapping relationship. , as well as It has been calculated as above, so the target state estimation value can be obtained through the first mapping relationship.

[0185] In step S520, a second mapping relationship among the coupling coefficient, the reference estimation error covariance matrix and the target estimation error state matrix is ​​determined, and based on the second mapping relationship, the target estimation error state matrix is ​​determined using the coupling coefficient and the reference estimation error covariance matrix.

[0186] In this example implementation, a second mapping relationship between the coupling coefficient, the reference estimation error covariance matrix, the intermediate estimation error covariance matrix, and the target estimation error state matrix may be determined first, where the second mapping relationship may be:

[0187]

[0188] in, is the target estimation error state matrix, is the intermediate estimation error covariance matrix.

[0189] After the second mapping relationship is obtained, the target estimation error state matrix may be determined based on the second mapping relationship.

[0190] in, , , The above has been calculated, therefore, the target estimation error state matrix can be obtained based on the above second mapping relationship.

[0191] The following is an explanation of a specific implementation method to make the technical effect of the present disclosure more intuitive. Specifically, assuming that the attitude angular velocity of the above-mentioned target coordinate system relative to the inertial coordinate system is for:

[0192]

[0193] The initial state values ​​are as follows.

[0194] Initial angular velocity: rad / s

[0195] Initial attitude angle: rad

[0196] Initial value of state estimation error covariance matrix

[0197] The filtering parameters are as follows.

[0198] Process noise error covariance matrix

[0199]

[0200] Observation noise error covariance matrix

[0201]

[0202] The specific assignment of dynamic interference is as follows.

[0203] when hour,

[0204] when hour,

[0205] Disturbance transmission error covariance matrix

[0206] Initial value of interference estimation error covariance matrix

[0207] The controller configuration is as follows.

[0208]

[0209] Where: , , , , is the three-dimensional identity matrix.

[0210] The moment of inertia is:

[0211] kg m2

[0212] The nonlinear sliding mode observer parameter configuration is as follows:

[0213] , ,

[0214] Perform attitude angular velocity simulation with the above parameter configuration. Figure 6 is a schematic diagram of an angular velocity simulation curve in the related art, Figure 7 A schematic diagram of an angular velocity simulation curve provided by an embodiment of the present disclosure, comprising Figure 6 and Figure 7 It can be seen that the difference between the estimated value and the actual value in the state estimation method of the flat-panel satellite provided by the embodiment of the present disclosure is smaller, that is, the state estimation accuracy of the present disclosure is higher.

[0215] Figure 8 is a schematic diagram of a simulation curve of an attitude angle in the related art, Fig. 9 A schematic diagram of a simulation curve of an attitude angle provided by an embodiment of the present disclosure, compared with Figure 8 and Fig. 9 It can be seen that the simulation effect of the attitude angle provided by the method provided in the embodiment of the present disclosure is also better than that of the related art.

[0216] Further, see Fig.10 and Fig.11 , Fig.10 is a schematic diagram of a simulation curve of interference in the related art, Fig.11 A schematic diagram of a simulation curve of interference provided by an embodiment of the present disclosure, compared with Fig.10 and Fig.11 It can be obtained that the state estimation method of the flat-panel satellite provided by the embodiment of the present disclosure has a higher interference estimation accuracy than the related art.

[0217] The state estimation method of the flat-panel satellite provided by the embodiment of the present disclosure, on the one hand, calculates the initial dynamic interference torque and the initial estimation error covariance matrix based on the interference transfer equation in the local linearization equation; determines the coupling coefficient, the reference state estimation value of the system state parameter in the interference-free state and the reference estimation error covariance matrix based on the initial dynamic interference torque and the initial estimation error covariance matrix; determines the target state estimation value, the target estimation error state matrix and the target dynamic interference torque based on the coupling coefficient, the reference state estimation value and the reference estimation error covariance matrix. The state and interference torque of the flat-panel satellite can be estimated at the same time. On the other hand, the angular velocity channel in the system state equation is separated to obtain the angular velocity state equation, and the nonlinear angular velocity observation value is obtained based on the angular velocity state equation; the local linearization equation is determined based on the nonlinear angular velocity observation value and the system state equation. When obtaining the local linearization equation, the nonlinear factor is taken into account, which can improve the estimation accuracy of the interference torque.

[0218] Furthermore, the present disclosure also provides a state estimation device for a flat-panel satellite, referring to Fig.12 As shown, the state estimation device 1200 of the flat-panel satellite may include a building module 1210, an observation module 1220, an equation determination module 1230, a calculation module 1240, a parameter determination module 1250, and an estimation module 1260. Among them:

[0219] The establishing module 1210 may be used to establish a relevant coordinate system of the flat-panel satellite, and determine a system state equation including system state parameters of the flat-panel satellite based on the relevant coordinate system.

[0220] The observation module 1220 can be used to separate the angular velocity channel in the system state equation to obtain the angular velocity state equation, and obtain nonlinear angular velocity observation values ​​based on the angular velocity state equation.

[0221] The equation determination module 1230 may be configured to determine a local linearization equation based on nonlinear angular velocity observations and a system state equation.

[0222] The calculation module 1240 may be configured to calculate an initial dynamic disturbance torque and an initial estimation error covariance matrix based on a disturbance transfer equation in the local linearization equation.

[0223] The parameter determination module 1250 can be used to determine the target dynamic disturbance torque, the intermediate estimation error covariance matrix, the coupling coefficient, the reference state estimation value of the system state parameters in the interference-free state and the reference estimation error covariance matrix based on the initial dynamic disturbance torque and the initial estimation error covariance matrix.

[0224] The estimation module 1260 may be configured to determine a target state estimation value and a target estimation error state matrix based on the coupling coefficient, the target dynamic disturbance torque, the intermediate estimation error covariance matrix, the reference state estimation value and the reference estimation error covariance matrix.

[0225] In some examples, establishment module 1210 can also be used to establish a body coordinate system, an inertial coordinate system, and a target coordinate system of the flat-panel satellite, wherein when the flat-panel satellite processes a desired attitude, the target coordinate system coincides with the body coordinate system; attitude kinematic equations and attitude dynamic equations are determined based on the attitudes of the target coordinate system and the body coordinate system; and state equations including system state parameters are constructed based on the attitude kinematic equations and the attitude dynamic equations.

[0226] In some examples, the observation module 1220 can also be used to discretize the system state equation to obtain a discretized state equation; separate the angular velocity channel in the discretized state equation to obtain the angular velocity state equation, and design a nonlinear sliding mode observer based on the angular velocity state equation; and obtain nonlinear angular velocity observation values ​​based on the nonlinear sliding mode observer.

[0227] In some examples, the equation determination module 1230 may also be used to expand the discretized state equation using nonlinear angular velocity observations as Taylor expansion points to obtain a local linearized equation.

[0228] In some examples, the calculation module 1240 can also be used to extract the interference transfer equation from the local linearization equation; recursively perform a step on the interference transfer equation under the Bayesian filtering framework to obtain the interference integral calculation equation of the initial dynamic interference torque and the matrix integral calculation equation corresponding to the initial estimated error covariance matrix; solve the interference integral calculation equation and the matrix integral calculation equation to obtain the initial dynamic interference torque and the initial estimated error covariance matrix.

[0229] In some examples, the parameter determination module 1250 can also be used to determine the target dynamic disturbance torque and the intermediate estimation error covariance matrix based on the initial dynamic disturbance torque and the initial estimation error covariance matrix using a dynamic interference algorithm; calculate the reference state estimation value and the reference estimation error covariance matrix based on the local linearization equation and the non-interference state estimation algorithm using the initial dynamic disturbance torque and the initial estimation error covariance matrix; and determine the coupling coefficient based on the local linearization equation using the initial dynamic disturbance torque and the initial estimation error covariance matrix.

[0230] In some examples, the estimation module 1260 can also be used to determine a first mapping relationship between the coupling coefficient, the reference state estimate, the target dynamic interference torque and the target state estimate, and based on the first mapping relationship, determine the target state estimate using the coupling coefficient, the target dynamic interference torque and the reference state estimate; determine a second mapping relationship between the coupling coefficient, the reference estimation error covariance matrix, the intermediate estimation error covariance matrix and the target estimation error state matrix, and based on the second mapping relationship, determine the target estimation error state matrix using the coupling coefficient and the reference estimation error covariance matrix.

[0231] Please refer to Fig.13 , Fig.13 A schematic diagram of the structure of an electronic device provided for an embodiment of the present disclosure. In some examples, the electronic device may be at least one of a smart phone, a smart watch, a desktop computer, a laptop, a virtual reality terminal, an augmented reality terminal, a wireless terminal, and a laptop computer. The electronic device has a communication function and can access a wired network or a wireless network. An electronic device may generally refer to one of a plurality of terminals, and those skilled in the art may know that the number of the above terminals may be more or less. It is understandable that the electronic device undertakes the calculation and processing work of the technical solution of the present disclosure, and the embodiments of the present disclosure do not limit this.

[0232] It should be understood that the above-mentioned device embodiments are only illustrative, and the device of the present disclosure can also be implemented in other ways. For example, the division of units / modules in the above-mentioned embodiments is only a logical function division, and there may be other division methods in actual implementation. For example, multiple units, modules or components can be combined, or can be integrated into another system, or some features can be ignored or not executed.

[0233] In addition, unless otherwise specified, each functional unit / module in each embodiment of the present disclosure may be integrated into one unit / module, or each unit / module may exist physically separately, or two or more units / modules may be integrated together. The above-mentioned integrated unit / module may be implemented in the form of hardware or in the form of a software program module.

[0234] If the integrated unit / module is implemented in the form of hardware, the hardware may be a digital circuit, an analog circuit, etc. The physical implementation of the hardware structure includes but is not limited to transistors, memristors, etc. Unless otherwise specified, the processor may be any appropriate hardware processor, such as a CPU, a GPU, an FPGA, a DSP, an ASIC, etc. Unless otherwise specified, the storage unit may be any appropriate magnetic storage medium or magneto-optical storage medium, such as a resistive random access memory (RRAM), a dynamic random access memory (DRAM), a static random access memory (SRAM), an enhanced dynamic random access memory (EDRAM), a high-bandwidth memory (HBM), a hybrid memory cube (HMC), etc.

[0235] If the integrated unit / module is implemented in the form of a software program module and sold or used as an independent product, it can be stored in a computer-readable memory. Based on this understanding, the technical solution of the present disclosure, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, which is stored in a memory and includes several instructions for a computer device (which can be a personal computer, server or network device, etc.) to perform all or part of the steps of the various embodiments of the present disclosure. The aforementioned memory includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, disk or optical disk, etc. Various media that can store program codes.

[0236] like Fig.13 As shown, the electronic device 1300 may include: at least one processor 1310 , a memory 1320 , and a communication interface 1330 .

[0237] The memory 1320 is used to store programs. Specifically, the programs may include program codes, and the program codes include computer operation instructions.

[0238] The memory 1320 may include a high-speed RAM memory, and may also include a non-volatile memory (non-volatile memory), such as at least one disk memory.

[0239] The processor 1310 is used to execute the computer-executable instructions stored in the memory 1320 to implement the state estimation method of the flat-panel satellite described in the above method embodiment. The processor 1310 may be a central processing unit (CPU), or an application specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of the present disclosure.

[0240] The electronic device 1300 may also include a communication interface 1330, so that it can communicate and interact with external devices through the communication interface 1330. In a specific implementation, if the communication interface 1330, the memory 1320 and the processor 1310 are implemented independently, the communication interface 1330, the memory 1320 and the processor 1310 can be connected to each other through a bus and complete the communication between each other. The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. The bus can be divided into an address bus, a data bus, a control bus, etc., but it does not mean that there is only one bus or one type of bus.

[0241] Optionally, in a specific implementation, if the communication interface 1330, the memory 1320 and the processor 1310 are integrated on a chip, the communication interface 1330, the memory 1320 and the processor 1310 can complete communication through an internal interface.

[0242] The present disclosure also provides a computer-readable storage medium, which may include: a USB flash drive, a mobile hard disk, a read-only memory, a random access memory, a disk or an optical disk, and other media that can store program codes. Specifically, the computer-readable storage medium stores program instructions, and the program instructions are used in the state estimation method of the flat-panel satellite in the above embodiment.

[0243] The embodiments of the present disclosure also provide a computer program product, which includes computer instructions, which are stored in a computer-readable storage medium; a processor of an electronic device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the electronic device executes to implement the state estimation method of the flat-panel satellite in each of the above embodiments.

[0244] Those skilled in the art should be aware that in one or more of the above examples, the functions described in the embodiments of the present disclosure can be implemented using hardware, software, firmware, or any combination thereof. When implemented using software, these functions can be stored in a computer-readable medium or transmitted as one or more instructions or codes on a computer-readable medium. Computer-readable media include computer storage media and communication media, wherein communication media include any media that facilitates the transmission of computer programs from one place to another. Storage media can be any available media that can be accessed by general or special-purpose computers.

[0245] In the above embodiments, the description of each embodiment has its own emphasis. For the part not described in detail in a certain embodiment, please refer to the relevant description of other embodiments. The technical features of the above embodiments can be combined arbitrarily. In order to make the description concise, all possible combinations of the technical features in the above embodiments are not described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0246] Those skilled in the art will readily appreciate other embodiments of the present disclosure after considering the specification and practicing the inventions claimed herein. The present disclosure is intended to cover any variations, uses or adaptations of the present disclosure that follow the general principles of the present disclosure and include common knowledge or customary technical means in the art that are not claimed in the present disclosure.

[0247] It should be understood that the present disclosure is not limited to the exact structures that have been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.

Claims

1. A method for estimating the state of a flat-panel satellite, characterized in that: include: Establishing a relevant coordinate system of the flat-panel satellite, and determining a system state equation including system state parameters of the flat-panel satellite based on the relevant coordinate system; Separating the angular velocity channel in the system state equation to obtain an angular velocity state equation, and acquiring a nonlinear angular velocity observation value based on the angular velocity state equation; Determine a local linearization equation according to the nonlinear angular velocity observation value and the system state equation; Calculate the initial dynamic disturbance torque and the initial estimation error covariance matrix based on the disturbance transfer equation in the local linearization equation; Determine a target dynamic disturbance torque, an intermediate estimation error covariance matrix, a coupling coefficient, a reference state estimation value of the system state parameter in a non-interference state, and a reference estimation error covariance matrix according to the initial dynamic disturbance torque and the initial estimation error covariance matrix; Determine a target state estimation value and a target estimation error state matrix based on the coupling coefficient, the target dynamic disturbance torque, the intermediate estimation error covariance matrix, the reference state estimation value and the reference estimation error covariance matrix; The calculation of the initial dynamic disturbance torque and the initial estimation error covariance matrix based on the disturbance transfer equation in the local linearization equation includes: extracting a disturbance transfer equation from the local linearized equation; Under the Bayesian filtering framework, the interference transfer equation is recursively deduced in one step to obtain the interference integral calculation equation of the initial dynamic interference torque and the matrix integral calculation equation corresponding to the initial estimation error covariance matrix; Performing Taylor expansion on each component of the interference moment vector in the interference integral calculation equation and the matrix integral calculation equation to obtain a polynomial function, and integrating and solving the polynomial function to obtain an integral result; The interference integral calculation equation and the matrix integral calculation equation are solved according to the integration result to obtain the initial dynamic interference torque and the initial estimation error covariance matrix.

2. The method according to claim 1, characterized in that The establishing of a related coordinate system of the flat-panel satellite and determining a system state equation including system state parameters of the flat-panel satellite based on the related coordinate system include: Establishing a body coordinate system, an inertial coordinate system, and a target coordinate system of the flat-panel satellite, wherein when the flat-panel satellite is in a desired posture, the target coordinate system coincides with the body coordinate system; Determine the attitude kinematic equation and the attitude dynamic equation based on the attitude of the target coordinate system and the body coordinate system; According to the posture kinematic equation and the posture dynamic equation, a system state equation including the system state parameters is constructed.

3. The method according to claim 1, characterized in that The step of separating the angular velocity channel in the system state equation to obtain the angular velocity state equation, and acquiring the nonlinear angular velocity observation value based on the angular velocity state equation includes: Discretizing the system state equation to obtain a discretized state equation; Separating the angular velocity channel in the discretized state equation to obtain an angular velocity state equation, and designing a nonlinear sliding mode observer based on the angular velocity state equation; The nonlinear angular velocity observation value is obtained based on the nonlinear sliding mode observer.

4. The method according to claim 3, characterized in that The determining of the local linearization equation according to the nonlinear angular velocity observation value and the system state equation comprises: The discretized state equation is expanded using the nonlinear angular velocity observation value as a Taylor expansion point to obtain the local linearized equation.

5. The method according to claim 1, characterized in that: Determining a target dynamic disturbance torque, an intermediate estimation error covariance matrix, a coupling coefficient, a reference state estimation value of the system state parameter in a non-interference state, and a reference estimation error covariance matrix according to the initial dynamic disturbance torque and the initial estimation error covariance matrix, including: Based on the initial dynamic disturbance torque and the initial estimation error covariance matrix, determining the target dynamic disturbance torque and the intermediate estimation error covariance matrix using a dynamic disturbance algorithm; Based on the local linearization equation and the non-interference state estimation algorithm, the reference state estimation value and the reference estimation error covariance matrix are calculated using the initial dynamic interference torque and the initial estimation error covariance matrix; Based on the local linearization equation, the coupling coefficient is determined using the initial dynamic disturbance torque and an initial estimation error covariance matrix.

6. The method according to claim 1, characterized in that The determining of the target state estimation value and the target estimation error state matrix based on the coupling coefficient, the target dynamic disturbance torque, the intermediate estimation error covariance matrix, the reference state estimation value and the reference estimation error covariance matrix comprises: Determine a first mapping relationship between the coupling coefficient, the reference state estimation value, the target dynamic interference torque and the target state estimation value, and determine the target state estimation value based on the first mapping relationship by using the coupling coefficient, the target dynamic interference torque and the reference state estimation value; Determine a second mapping relationship among the coupling coefficient, the reference estimation error covariance matrix, the intermediate estimation error covariance matrix and the target estimation error state matrix, and based on the second mapping relationship, determine the target estimation error state matrix using the coupling coefficient and the reference estimation error covariance matrix.

7. A state estimation device for a flat-panel satellite, characterized in that: include: An establishing module, used for establishing a relevant coordinate system of the flat-panel satellite, and determining a system state equation including system state parameters of the flat-panel satellite based on the relevant coordinate system; An observation module, used for separating the angular velocity channel in the system state equation to obtain the angular velocity state equation, and obtaining a nonlinear angular velocity observation value based on the angular velocity state equation; An equation determination module, used for determining a local linearization equation according to the nonlinear angular velocity observation value and the system state equation; A calculation module, used for calculating an initial dynamic disturbance torque and an initial estimation error covariance matrix based on a disturbance transfer equation in the local linearization equation; A parameter determination module, used to determine a target dynamic disturbance torque, an intermediate estimation error covariance matrix, a coupling coefficient, a reference state estimation value of the system state parameter in a non-interference state, and a reference estimation error covariance matrix according to the initial dynamic disturbance torque and the initial estimation error covariance matrix; An estimation module, configured to determine a target state estimation value and a target estimation error state matrix based on the coupling coefficient, the target dynamic disturbance torque, the intermediate estimation error covariance matrix, the reference state estimation value and the reference estimation error covariance matrix; The calculation of the initial dynamic disturbance torque and the initial estimation error covariance matrix based on the disturbance transfer equation in the local linearization equation includes: extracting a disturbance transfer equation from the local linearized equation; Under the Bayesian filtering framework, the interference transfer equation is recursively deduced in one step to obtain the interference integral calculation equation of the initial dynamic interference torque and the matrix integral calculation equation corresponding to the initial estimation error covariance matrix; Performing Taylor expansion on each component of the interference moment vector in the interference integral calculation equation and the matrix integral calculation equation to obtain a polynomial function, and integrating and solving the polynomial function to obtain an integral result; The interference integral calculation equation and the matrix integral calculation equation are solved according to the integration result to obtain the initial dynamic interference torque and the initial estimation error covariance matrix.

8. An electronic device, characterized in that: The electronic device comprises: a processor and a memory; the processor is used to execute instructions stored in the memory to implement the state estimation method of the flat-panel satellite according to any one of claims 1 to 6.

9. A computer storage medium, characterized in that: The storage medium stores at least one instruction, and the at least one instruction is used to be executed by a processor to implement the state estimation method of a flat-panel satellite according to any one of claims 1 to 6.

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