Moving base airborne photoelectric tracking system frame deep coupling dynamics modeling method

Abstract

The invention provides a dynamic base airborne photoelectric tracking system frame deep coupling dynamics modeling method, and belongs to the technical field of automatic control, and the method comprises the steps: building a machine body coordinate system, an outer frame coordinate system and an inner frame coordinate system, and building a conversion relation between the coordinate systems through the rotation around a shaft; the space-time mapping relation of the multi-stage motion of the machine body, the outer frame and the inner frame under different coordinate systems is constructed, and an airborne photoelectric tracking system kinematics model is established by representing the angular rates and the angular acceleration rates of the inner and outer frames; on the basis of a Newton-Euler equation, representing a stress motion law of the inner and outer frames, and establishing an airborne photoelectric tracking system dynamics model; and finally, distinguishing known items and unknown items of multi-source interference according to sensor measurement information, and obtaining a deep coupling frame model of the airborne photoelectric tracking system under the movable base through coordinate transformation. According to the invention, precise visual axis control of a photoelectric tracking system carried by a high-dynamic aircraft under multi-stage motion coupling is facilitated.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of automatic control, and particularly relates to a dynamic base airborne photoelectric tracking system frame deep coupling dynamics modeling method. BACKGROUND

[0002] As an integrated precision electromechanical system integrating photoelectric sensing, servo control, image processing and other technologies, the airborne photoelectric tracking system has the advantages of high-precision capture, tracking and aiming capability for dynamic targets, and has become a vital load for fixed-wing aircraft, unmanned aerial vehicles, missiles and other aircraft to complete tasks such as wide-area search, long-range detection, accurate positioning, rapid destruction and real-time evaluation.

[0003] However, to achieve stable maintenance of the detection load's view axis pointing, it is necessary to isolate the influence of external environment and internal uncertainty through a complex frame mechanical structure. Under the high dynamic motion of the carrier, the carrier attitude changes and the internal and external frame pointing motion are deeply coupled, which brings new challenges to the modeling of the frame dynamics of the airborne photoelectric tracking system.

[0004] In the existing frame system modeling, the authorized patent CN104217097B only considers the coupling of friction and base angular motion under frame imbalance, ignoring the motion coupling between the base and the frame; the system modeling part of the authorized patent CN107894713B only considers the cross-coupling torque of the shaft system, ignoring the dynamic base characteristics of the carrier. When the photoelectric tracking system is carried on a high-speed aircraft to perform a long-distance detection task, the above modeling methods are difficult to accurately describe the frame motion law and serve precise pointing control. SUMMARY

[0005] In view of the precise pointing requirements of the photoelectric tracking system in the high-altitude flight, fast dynamic platform and long-distance detection, the application provides a dynamic base airborne photoelectric tracking system frame deep coupling dynamics modeling method, establishes the body, outer frame and inner frame fixed coordinate systems, describes the change law of the inner and outer frame angular velocity and angular acceleration under the carrier attitude change, and uses the Newton-Euler equation to establish the inner and outer frame dynamics model under the dynamic base, thereby helping the precise view axis control of the photoelectric tracking system carried by the high dynamic aircraft under the multi-stage motion coupling.

[0006] To achieve the above purpose, the application adopts the following technical solutions:

[0007] A dynamic base airborne photoelectric tracking system frame deep coupling dynamics modeling method comprises the following steps:

[0008] Firstly, to describe the observation load view axis motion fixed to the inner frame, the conversion relationship among the body coordinate system, the outer frame coordinate system and the inner frame coordinate system is established;

[0009] The second step is to establish a kinematic model of the airborne photoelectric tracking system frame based on the transformation relationship between the coordinate systems established in the first step, which is used to characterize the angular velocity and angular acceleration of the inner and outer frames.

[0010] The third step is to establish a dynamic model of the airborne photoelectric tracking system frame based on the angular velocities and angular accelerations of the inner and outer frames established in the second step, according to the Newton-Euler equations.

[0011] The fourth step involves using the frame dynamics model established in the third step to distinguish between known and unknown torque terms based on the gyroscope measurement signals, thereby obtaining a deeply coupled frame model of the airborne photoelectric tracking system under the moving base.

[0012] Beneficial effects:

[0013] (1) This invention highlights the characteristics of the dynamic base, that is, when establishing the dynamic model of the airborne photoelectric tracking system frame, it considers the influence of the aircraft attitude change on the line of sight, and can describe the motion law of the high dynamic aircraft frame.

[0014] (2) This invention highlights the deep coupling characteristics, that is, when establishing the dynamic model of the airborne photoelectric tracking system framework, it considers the changes in the attitude of the carrier aircraft and the part of the interference received by the carrier aircraft transmitted to the pod. Attached Figure Description

[0015] Figure 1 This is a flowchart illustrating a method for deep coupling dynamic modeling of the frame of a dynamic base airborne photoelectric tracking system according to an embodiment of the present invention;

[0016] Figure 2 This is a diagram showing the structure and coordinate system of a two-axis airborne photoelectric tracking system. Detailed Implementation

[0017] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only for explaining the invention and are not intended to limit the invention. Furthermore, the technical features involved in the various embodiments of the invention described below can be combined with each other as long as they do not conflict with each other. The technical solutions in the embodiments of the invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the invention, not all of them. All other embodiments obtained by those skilled in the art based on the embodiments of the invention without creative effort are within the protection scope of the invention.

[0018] like Figure 1 As shown, the deep coupling dynamic modeling method for the frame of a dynamic base airborne photoelectric tracking system of the present invention includes the following steps:

[0019] The first step, to describe the motion of the observation load's line of sight fixed to the inner frame, is to establish the transformation relationships between the body coordinate system, the outer frame coordinate system, and the inner frame coordinate system, including:

[0020] Define the body coordinate system {B}, the outer frame coordinate system {O}, and the inner frame coordinate system {I}, where (x b , y b , z b ), (x o , y o , z o ), (x i , y i , z i ) are the coordinate axes of coordinate systems {B}, {O}, and {I}, respectively. b , q b , r b ), (p o , q o ,r o ), (p i , q i , r i The ω values ​​represent the inertial angular velocities of coordinate systems {B}, {O}, and {I}, respectively. B =(p b , q b , r b ) T ω O =(p o , q o , r o ) T ω I =(p i , q i , r i ) T , where the superscript T indicates transpose.

[0021] Assuming the origin of all coordinate systems is at the same location, the x-axis... b and coordinate axis x o Coincident, the body coordinate system {B} revolves around the coordinate axis x b Rotation The angle is used to obtain the outer frame coordinate system {O}; the coordinate axis z o and coordinate axis z i Coincident, the outer frame coordinate system {O} revolves around the coordinate axis z o Rotate by an angle ψ to obtain the inner frame coordinate system. Define the angular velocities of the inner and outer frames as follows: , ,in and They represent the rotation angles respectively. and The derivative of . The transformation matrix T from coordinate system {B} to coordinate system {O}. B O The transformation matrix T from coordinate system {O} to coordinate system {I} O I They are respectively:

[0022] .

[0023] The second step involves establishing a kinematic model of the airborne electro-optical tracking system frame based on the coordinate system transformation relationships established in the first step. This model characterizes the angular velocities and angular accelerations of the inner and outer frames, including:

[0024] The angular velocity of the outer frame consists of two parts: the motion of the carrier aircraft and the motion of the outer frame itself.

[0025] ;

[0026] in, The kinematic model of the inertial angular rate of the outer frame is represented as follows: It is determined by the body's inertial angular rate After coordinate transformation The transmitted angular velocity, and the angular velocity of the outer frame relative to the body. It is formed by stacking.

[0027] The angular rate of the inner frame consists of three parts: the motion of the carrier aircraft, the motion of the outer frame, and the motion of the inner frame itself.

[0028] ;

[0029] in, Inertial angular rate of the inner frame The kinematic model represents It is determined by the inertial angular rate of the outer frame. After coordinate transformation The transmitted angular rate, and the angular rate of the inner frame relative to the outer frame. It is formed by stacking;

[0030] Differentiating Σ1 yields Σ3:

[0031] ;

[0032] This formula represents the angular acceleration of the external frame. The expression, through the We obtain the product rule by differentiation;

[0033] in, It is the angular velocity ω O The derivative, It is the angular velocity ω B The derivative, It is the angular velocity ω o The derivative of, where Indicates the rotation angle The second derivative, Indicates rotation angle The first derivative, It is a transformation matrix The derivative:

[0034] ;

[0035] Similarly, differentiating Σ2 yields Σ4:

[0036] ;

[0037] This formula represents the angular acceleration of the inner frame. The expression, through the We obtain the product rule by differentiation;

[0038] in, It is the angular velocity ω I The derivative, It is the angular velocity ω i The derivative of, where Indicates the rotation angle The second derivative, Indicates the rotation angle The first derivative, It is a transformation matrix The derivative:

[0039] .

[0040] The third step, based on the angular velocities and angular accelerations of the inner and outer frames established in the second step, is to establish a dynamic model of the airborne electro-optical tracking system frame according to the Newton-Euler equations, including:

[0041] Due to limitations in manufacturing and assembly processes, dynamic mass imbalance always exists in actual frame systems. The inertia matrices of the inner and outer frames are established as follows:

[0042] ;

[0043] Among them, J xx J yy J zz and R xx , R yy , R zz These are the moments of inertia of the inner and outer frames about the x, y, and z axes, respectively; J xy J xz Jyz and R xy , R xz , R yz These are the inertia products at corresponding positions on the inner and outer frames, respectively.

[0044] Based on the Newton-Euler equations, the dynamic model of the inner frame is established as follows:

[0045] ;

[0046] Among them, M I =(M ix M iy M iz ) T It is the torque vector acting on the inner frame, represented in the {I} system; These are the moment vectors about the inner frame coordinate system {I}. Torque components of the shaft.

[0047] Similarly, the dynamic model of the outer frame is established as follows:

[0048] ;

[0049] Among them, L O It is the angular momentum of the outer frame:

[0050] ;

[0051] in, These are the outer frame inertia matrix and the inner frame inertia matrix defined at the beginning of this step (step 3), respectively.

[0052] The derivative of the angular momentum of the outer frame is:

[0053] ;

[0054] in,

[0055] ;

[0056] in, These are the moments of inertia, product of inertia, and angles of rotation of the inner frame about the x, y, and z axes. The function.

[0057] The second term of Σ5 is:

[0058] ;

[0059] in,

[0060] ;

[0061] in, These are the moments of inertia, product of inertia, and angular velocity ω of the outer frame about the x, y, and z axes. O The function.

[0062] In summary, the outer frame dynamic model Σ5 expands to:

[0063] .

[0064] Step 4: Based on the framework dynamics model established in Step 3, and by distinguishing known and unknown torque terms according to the gyroscope measurement signals, a deeply coupled framework model of the airborne photoelectric tracking system under the moving base is obtained, including:

[0065] The inner frame has only rotational degrees of freedom along the z-axis; therefore, the dynamic model Σ6 of the inner frame along its rotational axis is:

[0066] ;

[0067] in, To act on the inner frame Control torque of the shaft; and This represents the cross-coupling term caused by coordinate system rotation, based on gyroscope measurement information, where... Given the torque term, For unknown torque terms;

[0068] Among them, M ie M represents the frictional interference on the inner frame, the cable flexibility interference torque, and the model uncertainty. ik and M iu This represents the cross-coupling term caused by coordinate system rotation, based on gyroscope measurement information, where M ik Given the torque term, M iu For unknown torque terms:

[0069] ;

[0070] Similarly, the outer frame only has rotational degrees of freedom along the x-axis, therefore the dynamic model of the outer frame in its rotational axis direction is... for:

[0071] ;in, To act on the outer frame Control torque of the shaft; For the unmodeled external disturbance moment applied to the outer frame;

[0072] Among them, M oe M represents the frictional interference on the outer frame, the cable flexibility interference torque, and the model uncertainty. ok and Mou This represents the cross-coupling term caused by coordinate system rotation, where M ok Given the torque term, M ou For unknown torque terms:

[0073] ;

[0074] Combining Σ6 and Σ7, we obtain the coupled dynamic model of the two-axis photoelectric tracking system:

[0075] ;in, The equivalent inertia matrix of the system, This is the equivalent gyro torque matrix of the system; The external disturbance torque vector. For unmodeled external disturbances applied to the outer frame, ; Let be a vector of concentrated unknown coupled moments and uncertainties, where This is the sum of the unknown coupling terms and perturbations of the outer frame. It is the sum of the unknown coupling terms and perturbations of the inner frame.

[0076] in, to as well as to These are all intermediate parameters, which are based on the inertia parameters of the inner and outer frames defined in step three and the frame rotation angles defined in step one. The exported function is used here to simplify the matrix. and The expression:

[0077] ;

[0078] Figure 2 This demonstrates the structure of a two-axis airborne electro-optical tracking system and the transformation relationships between coordinate systems. The outer frame has rotational freedom along the x-axis, and the inner frame has rotational freedom along the z-axis. The origins of all coordinate systems are at the same location, and the x-axis... b and x o Coincident, the body coordinate system {B} revolves around x b Axis rotation The angle is used to obtain the outer frame coordinate system {O}; the coordinate axis z o and z i Coincident, outer frame coordinate system {O} revolves around z o Rotating the axis by an angle ψ yields the outer frame coordinate system {I}. For example... Figure 2 As shown, the carrier inertial navigation system is typically fixed to the body coordinate system {B} and is used to measure the inertial angular rate of the body. The two-axis gyroscopes are respectively mounted on the rotation axes of the outer frame and the inner frame. shaft and (axis), used to measure the relative angular rate of the frame. and The observation payload (such as a camera) is fixed to the inner frame {I}, and its line of sight points along the coordinate system {I} of the inner frame. axis.

[0079] The above embodiments are preferred implementations of the present invention. The implementation of the present invention is not limited to the above embodiments. Any changes, modifications, substitutions, combinations, or simplifications made without departing from the spirit and basic principles of the present invention shall be considered equivalent substitutions and shall be included within the protection scope of the present invention.

Claims

1. A method for deep coupling dynamic modeling of the frame of a dynamic base airborne photoelectric tracking system, characterized in that, The method comprises the following steps: A first step is to establish a conversion relationship among a body coordinate system, an outer frame coordinate system and an inner frame coordinate system for describing the visual axis movement of an observation load fixed to the inner frame; A second step is to establish a kinematics model of a frame of the airborne optoelectronic tracking system according to the conversion relationship among the coordinate systems established in the first step, for representing the angular velocity and the angular acceleration of the inner frame and the outer frame; A third step is to establish a dynamics model of the frame of the airborne optoelectronic tracking system according to Newton-Euler equation based on the angular velocity and the angular acceleration of the inner frame and the outer frame established in the second step; A fourth step is to obtain a deep coupling frame model of the airborne optoelectronic tracking system under a moving base according to the known torque and the unknown torque by distinguishing the known torque and the unknown torque from the gyro measurement signal based on the frame dynamics model established in the third step.

2. The method for deep coupling dynamic modeling of a dynamic base airborne photoelectric tracking system frame as described in claim 1, characterized in that: In the first step, the origins of the body coordinate system, the outer frame coordinate system and the inner frame coordinate system are defined to coincide and the conversion is completed by twice rotations around the body transverse axis and the outer frame vertical axis in sequence, so that the subsequent kinematics and dynamics derivation are progressive under the condition of the same origin, and the coordinate reference of the deep coupling model is consistent.

3. The method for deep coupling dynamic modeling of a dynamic base airborne photoelectric tracking system frame as described in claim 2, characterized in that: In the second step, the outer frame angular velocity is decomposed into two parts of carrier motion transmission and frame relative rotation based on the rotation sequence in the first step, and then the inner frame angular velocity is further superimposed with the outer frame motion contribution, so that the complete mapping of the inner frame angular velocity and the outer frame angular velocity is obtained by progressive derivation, and the necessary angular acceleration input is provided for the Newton-Euler equation in the third step.

4. The method of claim 3, wherein: When the outer frame angular velocity is derived in the second step, the carrier angular acceleration, the frame angular acceleration and the Coriolis cross term are retained; when the inner frame angular velocity is derived, the outer frame angular acceleration, the inner frame angular acceleration and the second-order Coriolis cross term are retained; and the obtained angular acceleration expression is directly used as the calculation basis of the inertia coupling term in the third step, so that the seamless connection from kinematics to dynamics is realized.

5. A framework for deep-coupled dynamic modeling of a shipboard electro-optical tracking system, as claimed in claim 4, wherein: In the third step, the non-diagonal inertia product is introduced into the Newton-Euler equation, so that the inertia principal axis coupling term appears in the dynamics equations of the inner frame and the outer frame, the coupling term is updated in real time with the frame rotation angle, and the deep coupling model reflects the actual unbalanced mass distribution.

6. A framework for deep-coupled dynamics modeling of a shipboard electro-optical tracking system, as claimed in claim 5, wherein: In the third step, the inner frame inertia matrix is mapped to the outer frame coordinate system in real time through coordinate transformation when the outer frame angular momentum is established, so that the outer frame equation automatically contains the additional inertia effect generated by the inner frame motion, and the two-stage frame inertia is deeply nested in the same equation.

7. A framework for deep-coupled dynamics modeling of a shipboard electro-optical tracking system, as claimed in claim 6, wherein: In the fourth step, the inner frame dynamics equation is reduced to the z-axis and the outer frame equation is reduced to the x-axis according to the characteristics that the gyro only measures the rotational axis degree of freedom, so that the model dimension is matched with the sensor dimension, and the axis alignment condition is provided for the separation of the known torque and the unknown torque.

8. A framework for deep-coupled dynamics modeling of a shipboard electro-optical tracking system, as in claim 7, wherein: In the fourth step, in the single-axis equation after the reduction, the cross term composed of the carrier angular motion and the frame angular velocity product is marked as the known torque, the friction, the cable flexibility and the uncertain part of the model are included in the unknown torque, and the synchronous separation of the calculable part and the non-calculable part is realized through the identification of the parts in the same equation.

9. A framework for deep-coupled dynamics modeling of a shipboard electro-optical tracking system, as claimed in claim 8, wherein: The fourth step is to combine the single-axis equations of the inner and outer frames to obtain a combined model. The known cross moment is added to the left side of the equation as the control moment, and the unknown moment is concentrated on the right side of the equation as the total disturbance, forming a three-module coupling structure of equivalent inertia, equivalent gyro moment and total disturbance, so that the subsequent control law design can directly use the structure for compensation.

10. A method of frame deep-coupled dynamics modeling of a shipboard electro-optical tracking system according to claim 9, characterized in that: In the combined model given in the fourth step, the elements of the equivalent inertia matrix and the equivalent gyro moment matrix only depend on the frame rotation angle in the first step and the inertia parameters in the third step, and are updated in real time through the angular rate and angular acceleration recursive relationship in the second step. Thus, the kinematics, dynamics and disturbance are separated in the three-step logic, which is closed in the same parameter update chain, and the final solidification of the deep-coupled frame model of the moving base is completed.

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