Adaptive control method for two-axis semi-strapdown aviation remote sensing stabilized platform

Abstract

The present invention provides an adaptive control method for a two-axis semi-strapdown aviation remote sensing stable platform, comprising the following steps: step S1: establishing a disturbance analysis based on the kinematic model of the two-axis semi-strapdown aviation remote sensing stable platform, and building a dynamic model; step S2: a conversion module converts a three-axis disturbance of the body coupled in the visual axis direction into a two-axis disturbance; step S3: superimposing the converted disturbance with the platform motor deflection to obtain the influence on the visual axis; step S4: designing an adaptive controller to achieve stable control of the constructed dynamic model of the two-axis semi-strapdown aviation remote sensing stable platform. The application of this technical solution can ensure the stable pointing of the load visual axis on the two-axis semi-strapdown aviation remote sensing stable platform.

Description

Technical Field

[0001] The invention relates to the technical field of aviation remote sensing stabilized platform, in particular to an adaptive control method of a two-axis semi-strapdown aviation remote sensing stabilized platform. Background Art

[0002] The two-axis semi-strapdown aviation remote sensing stabilized platform is a device designed to eliminate aircraft interference and ensure sensor pointing stability. The traditional airborne two-axis semi-strapdown aviation remote sensing stabilized platform can effectively control the disturbances in the pitch and yaw channels, but cannot achieve ideal roll channel disturbance control. Summary of the invention

[0003] In view of this, an object of the present invention is to provide an adaptive control method for a two-axis semi-strapdown aviation remote sensing stabilized platform to ensure the pointing stability of the payload visual axis on the two-axis semi-strapdown aviation remote sensing stabilized platform.

[0004] To achieve the above object, the present invention adopts the following technical solution: a two-axis semi-strapdown aviation remote sensing stable platform adaptive control method, comprising the following steps:

[0005] Step S1: Establish a disturbance analysis based on the kinematic model of the two-axis semi-strapdown aviation remote sensing stable platform and build a dynamic model;

[0006] Step S2: The conversion module converts the three-axis disturbance of the body coupled in the visual axis direction into a two-axis disturbance;

[0007] Step S3: The converted disturbance is superimposed on the platform motor deflection to obtain the influence on the visual axis;

[0008] Step S4: designing an adaptive controller to achieve stable control of the dynamic model of the constructed two-axis semi-strapdown aviation remote sensing stable platform;

[0009] The two-axis semi-strapdown aviation remote sensing stabilized platform Represents the body coordinate system, where x is positive when pointing in the direction of the aircraft head. represents the heading platform coordinate system, It is the pitch platform coordinate system. Since the load is mechanically fixed on the pitch platform, the load's visual axis coordinate system is equivalent to the pitch platform coordinate system.

[0010] The perturbation angular velocity of the visual axis coordinate system is:

[0011]

[0012] is the disturbance angular velocity of the pitch platform coordinate system, , They represent the disturbance angular velocity components of the pitch platform coordinate system along the x-axis, y-axis, and z-axis directions, respectively. , They represent the disturbance angular velocity components of the body coordinate system along the x-axis, y-axis, and z-axis directions, respectively. is the heading angle of the heading platform coordinate system relative to the body coordinate system, is the derivative of the heading angle of the heading platform coordinate system relative to the body coordinate system, is the pitch angle of the pitch platform coordinate system relative to the heading platform coordinate system, is the derivative of the pitch angle of the pitch platform coordinate system relative to the heading platform coordinate system;

[0013] The above formula consists of two parts, namely

[0014]

[0015] represents the projection of the aircraft angular velocity disturbance on the pitch platform coordinate system; , They respectively represent the angular velocity components of the aircraft angular velocity disturbance along the x-axis, y-axis, and z-axis in the pitch platform coordinate system;

[0016]

[0017] represents the angular velocity disturbance caused by the motion of the stable platform itself; , They respectively represent the disturbance angular velocity components of the stable platform rotation along the x-axis, y-axis, and z-axis in the pitch platform coordinate system;

[0018] From the above formula, we can see that , should meet the following requirements: ;when is a constant, and are all 0. In this case, if If the requirement is met, the roll axis disturbance is eliminated.

[0019] In a preferred embodiment, the conversion module is designed to use subscripts 0, 1, 2... to represent the time t0, t1, t2..., and the three-axis disturbance , and The pitch, roll, and heading disturbances coincide with the x0, y0, and z0 axes in the line of sight coordinate system, respectively, and the coordinate system at time t0 is also the stable time coordinate system;

[0020] and The resultant perturbation in the xoz plane is denoted by , with an angle , at time t0 and The disturbance is eliminated by the corresponding control motors; the corresponding roll angle generated at time t1 is recorded as , which will cause the visual axis coordinate system at time t1 to deflect around the y axis Angle, causing instability of the visual axis;

[0021] At t1 and The resultant perturbation in the xoz plane is denoted by , but affected by the roll axis disturbance at time t0, deflection Angle, here recorded as ,Will Decoupling calculation is performed in the coordinate system at time t0, and stable control is performed through the pitch and heading control motors, so as to eliminate the pitch and heading disturbances at time t1 and the rolling disturbances at time t0;

[0022] In continuous time, the roll disturbance at time t0 is compensated at time t1, and the roll disturbance at time t1 is compensated at time t2, so as to achieve a hysteresis compensation and eliminate the roll axis disturbance;

[0023] First, calculate the angular velocity of the body at time t0 and couple it to the line of sight coordinate system and The value of is calculated by integration Corresponding angle , then calculate the time t1;

[0024]

[0025] They represent the disturbance components along the x-axis and z-axis in the visual axis coordinate system at time t1 respectively; At time t1 and The combined perturbation in the xoz plane of the visual axis coordinate system; at time t1, in the xoz plane of the visual axis coordinate system and The angle between ; is the disturbance component along the y-axis in the visual axis coordinate system at time t0; for The roll angle generated at time t1; the upper and lower limits of the integral are the interval between two samples, which should be as short as possible; is the actual deflection angle of the roll axis of the visual axis coordinate system;

[0026] At this point, the effect of the rolling disturbance at time t0 is introduced at time t1

[0027]

[0028] and They are respectively the disturbance components along the x-axis and z-axis of the visual axis coordinate system at time t1 after decoupling.

[0029] In a preferred embodiment, the whale optimization algorithm of Latin hypercube sampling is used to adjust the PID control parameters in real time; assuming that the position of the current best individual is the best foraging position, other individuals will surround the position of the prey according to this best foraging position; the calculation of this process is as follows:

[0030]

[0031] D is the distance between the individual and the optimal foraging location; is the current iteration number; is the optimal foraging position currently obtained; is the current personal location; A and C is the control coefficient; and and is a random number in the range [0, 1]; is a decay variable that decreases from 2 to 0; the calculation formula is as follows:

[0032]

[0033] Represents the maximum number of iterations; the whale optimization algorithm updates the position by creating a spiral equation to calculate the distance between the individual and the optimal position; the position update calculation formula is as follows

[0034]

[0035] is the updated personal location; is the distance between the current individual and the current best foraging position; is the base of natural number logarithm; b is a constant that changes the shape of the spiral; is a random number in the range of [-1, 1]; Used to control the contraction of the spiral and the shape of the spiral; contraction, encirclement and advancement along the spiral path occur simultaneously with equal probability; the calculation formula is as follows;

[0036]

[0037] is a random number in the range of [0, 1], used to control the choice of foraging method; when |A|>1, the peripheral individuals are far away from the prey; different from the bubble net feeding stage, the bubble net feeding stage updates the position according to the best foraging position, and the position of the random individual is selected as the reference for the next position update; the calculation formula is as follows:

[0038]

[0039] is the position of a random individual; the integral of the time-weighted absolute error ITAE function is selected as the fitness function

[0040]

[0041] The general form of a PID controller is as follows:

[0042]

[0043] Indicates the controller output signal, represents the system error, are the control parameters of the PID controller respectively.

[0044] Compared with the prior art, the present invention has the following beneficial effects:

[0045] (1) Compared with the existing two-axis semi-strapdown aviation remote sensing stabilized platform control method, the present invention takes into account the disturbance of the roll axis in the platform.

[0046] (2) The adaptive control method proposed in the present invention can automatically adjust the control parameters of the controller according to the specific working environment, thereby enhancing the adaptability of the controller and the stability of the two-axis semi-strapdown aerial remote sensing stable platform. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1 It is a schematic diagram of a two-axis semi-strapdown aviation remote sensing stabilized platform according to a preferred embodiment of the present invention;

[0048] Figure 2 Schematic diagram of the relationship between conversion modules in a preferred embodiment of the present invention, wherein (a) is time t0, and (b) is time t1;

[0049] Figure 3 An adaptive control diagram for a preferred embodiment of the present invention;

[0050] Figure 4 It is a flow chart of the operation of the adaptive controller according to the preferred embodiment of the present invention;

[0051] Figure 5 A schematic diagram of system control of a preferred embodiment of the present invention;

[0052] Figure 6 The simulation results of the conversion module of the preferred embodiment of the present invention are shown in FIG. 1 , where (a) is without the conversion module and (b) is with the conversion module.

[0053] Figure 7 Schematic diagram of the effect of a single controller of a preferred embodiment of the present invention, wherein (a) is the step angle of the adaptive controller, (b) is the sine angle of the adaptive controller; (c) is the step angle of the traditional controller, and (d) is the sine angle of the traditional controller;

[0054] Figure 8 Schematic diagram of different desired deflection angles of a preferred embodiment of the present invention, wherein (a) is a step deflection angle and (b) is a sinusoidal deflection angle. DETAILED DESCRIPTION

[0055] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0056] It should be noted that the following detailed descriptions are illustrative and are intended to provide further explanation of the present application. Unless otherwise specified, all technical and scientific terms used herein have the same meanings as those commonly understood by those skilled in the art to which the present application belongs.

[0057] It should be noted that the terms used herein are only for describing specific embodiments and are not intended to limit the exemplary embodiments according to the present application; as used herein, unless the context clearly indicates otherwise, the singular form is also intended to include the plural form. In addition, it should be understood that when the terms "comprise" and / or "include" are used in this specification, they indicate the presence of features, steps, operations, devices, components and / or their combinations.

[0058] Adaptive control method for two-axis semi-strapdown aviation remote sensing stabilized platform, reference Figure 1-8 , including the following steps:

[0059] Step S1: Establish a disturbance analysis based on the kinematic model of the two-axis semi-strapdown aviation remote sensing stable platform and build a dynamic model;

[0060] Step S2: The conversion module converts the three-axis disturbance of the body coupled in the visual axis direction into a two-axis disturbance;

[0061] Step S3: The converted disturbance is superimposed on the platform motor deflection to obtain the influence on the visual axis;

[0062] Step S4: Design an adaptive controller to achieve stable control of the dynamic model of the constructed two-axis semi-strapdown aviation remote sensing stable platform.

[0063] Implementation process:

[0064] (1) Model establishment

[0065] Consider a two-axis semi-strapdown stabilized platform system such as Figure 1 As shown in Figure 1, the figure shows the yaw and pitch platforms. Three reference frames are introduced: the frame fixed to the aircraft body (b), the frame fixed to the heading platform (o), and the frame fixed to the pitch platform (i).

[0066] Represents the body coordinate system, where x is positive in the direction of the aircraft's head. Represents the heading platform coordinate system, and the rotation angle around the z-axis is . is the pitch platform coordinate system, and the rotation angle around the y-axis is Since the load is mechanically fixed on the pitch platform, the load's visual axis coordinate system is equivalent to the pitch platform coordinate system.

[0067] The perturbation angular velocity of the visual axis coordinate system is:

[0068]

[0069] The above formula can be analyzed by two parts, namely

[0070]

[0071]

[0072] Apparently , represents the projection of the aircraft angular velocity on the (i) coordinate system, represents the angular velocity caused by the motion of the stabilizing platform itself. In order to stabilize the visual axis, the following conditions should be met: .when is a constant, and are all 0. In this case, if The roll axis disturbance can be eliminated if the requirement is met. Based on this idea, a conversion module is designed.

[0073] (2) Conversion module design

[0074] Use subscripts 0, 1, 2, etc. to represent the times t0, t1, t2, etc. Figure 2 As shown in (a), the three-axis perturbation , and The pitch, roll, and heading disturbances coincide with the x0, y0, and z0 axes in the line of sight coordinate system, and the coordinate system at time t0 is also a stable time coordinate system.

[0075] and The resultant perturbation in the xoz plane is denoted by , with an angle , at time t0 and The disturbance can be eliminated by controlling the corresponding motors. The control cannot be eliminated, and the corresponding rolling angle will be generated at time t1, which is recorded as , which will cause the visual axis coordinate system at time t1 to deflect around the y axis Angle, causing instability of the visual axis.

[0076] At t1 and The resultant perturbation in the xoz plane is denoted by , but affected by the roll axis disturbance at time t0, deflection Angle, here recorded as ,Will Decoupling calculation is performed in the coordinate system at time t0, and stable control is performed through the pitch and heading control motors, so that the pitch and heading disturbances at time t1 and the roll disturbance at time t0 can be eliminated.

[0077] In continuous time, the roll disturbance at t0 is compensated at t1, and the roll disturbance at t1 is compensated at t2, achieving a hysteresis compensation to eliminate the roll axis disturbance. However, if the roll axis deflection angle at t0 is too large and exceeds the roll axis deflection angle at t1, the roll axis deflection angle at t1 is compensated at t2. The angle, after compensation, will give one of the control motors feedback of incorrect information, making it impossible for the conversion module to accurately compensate for the disturbance of the roll axis.

[0078] First, calculate the angular velocity of the body at time t0 and couple it to the line of sight coordinate system and The value of is calculated by integration Corresponding angle , and then calculate the time t1.

[0079]

[0080] At this point, the effect of the rolling disturbance at time t0 is introduced at time t1

[0081]

[0082] The algorithm flow is shown in Table 1:

[0083] Table 1 Conversion module algorithm flow

[0084]

[0085] (3) Adaptive controller design

[0086] Real-time adjustment of PID control parameters can enhance the adaptability of the PID controller and achieve the purpose of adaptive control.

[0087] The present invention adopts the whale optimization algorithm of Latin hypercube sampling to adjust PID control parameters in real time to achieve the purpose of adaptive control.

[0088] Latin hypercube sampling is a multidimensional stratified sampling technique. Its principle is to divide the interval [0, 1] into N equally spaced, non-overlapping subintervals, and perform independent and possibly equal sampling in each subinterval, so as to effectively sample in the variable distribution interval to ensure that the sampling points are evenly distributed in the entire distribution interval. The algorithm flow of Latin hypercube sampling is shown in Table 2:

[0089] Table 2 Latin hypercube sampling algorithm process

[0090] Latin Hypercube Sampling Algorithm 1. Determine the population size N and population dimension D 2. Set the interval of variable x to [xmin, xmax], where xmin and xmax are the lower and upper limits of the population. 3. Divide the interval [xmin, xmax] into N equal subintervals 4. Randomly select a point in each subinterval of each dimension 5. Combine the points in each dimension to form an initial population

[0091] Assuming that the position of the current best individual is the best foraging position, other individuals will surround the position of the prey based on this best foraging position. The calculation of this process is as follows.

[0092]

[0093] D is the distance between the individual and the optimal foraging location; is the current iteration number; is the optimal foraging position currently obtained; is the current personal location; A and C is the control coefficient; and and is a random number in the range [0, 1]; is a decay variable that decreases from 2 to 0. The calculation formula is shown below.

[0094]

[0095] Represents the maximum number of iterations. The whale optimization algorithm updates the position by creating a spiral equation to calculate the distance between the individual and the optimal position. The position update calculation formula is as follows

[0096]

[0097] is the distance between the current individual and the current best foraging position; b is a constant that changes the shape of the spiral; is a random number in the range [-1, 1]. Contraction, encirclement, and advancement along the spiral path occur simultaneously with equal probability. The calculation formula is shown below.

[0098]

[0099] is a random number in the range [0, 1], used to control the choice of foraging method. When |A|>1, the peripheral individuals are far away from the prey. Unlike the bubble net feeding stage, the bubble net feeding stage updates the position according to the best foraging position, and the position of the random individual is selected as the reference for the next position update. The calculation formula is as follows:

[0100]

[0101] is the position of a random individual. The integral of the time-weighted absolute error (ITAE) function is selected as the fitness function

[0102]

[0103] The general form of a PID controller is as follows:

[0104]

[0105] Indicates the controller output signal, represents the system error, are the control parameters of the PID controller respectively. The control principle diagram of the controller is as follows Figure 3 As shown:

[0106] The flowchart of the adaptive controller is as follows: Figure 4 As shown;

[0107] The control diagram of the combination of the conversion module and the adaptive controller is shown in Figure 5 As shown;

[0108] (4) Simulation analysis

[0109] In order to verify the effectiveness of the proposed adaptive control of the two-axis semi-strapdown aerial remote sensing stabilized platform, a line-of-sight (LOS) deflection angle tracking simulation experiment of the two-axis semi-strapdown aerial remote sensing stabilized platform was designed. The experimental results are shown below.

[0110] Depend on Figure 6 It can be seen that the conversion module can stabilize the disturbance of the roll axis;

[0111] Single controller effects:

[0112] Figure 7It can be seen that when the roll axis disturbance is not controlled, the deflection angle of the LOS keeps fluctuating around the desired angle and cannot be stabilized. The adaptive controller is more suitable for complex task requirements than the traditional single controller.

[0113] The control effect of the combination of conversion module and adaptive controller is as follows: Figure 8 As shown;

[0114] According to the above analysis, the designed adaptive control of the two-axis semi-strapdown aviation remote sensing stabilized platform is effective. The conversion module can eliminate the impact of roll disturbance on the LOS of the payload in the two-axis semi-strapdown aviation remote sensing stabilized platform. The adaptive controller can adjust the control parameters adaptively according to different mission requirements. Combining the two can further improve the LOS axis pointing accuracy of the payload.

[0115] Application of the present invention:

[0116] (1) Used for the control of other two-axis semi-strapdown stabilized platforms to improve the line-of-sight stabilization accuracy. Based on the Links UAV-Testbench, a quadrotor test bench system developed by Links, the present invention is used to improve the line-of-sight stabilization accuracy of a two-axis semi-strapdown stabilized platform.

[0117] (2) Latin hypercube sampling can be used in other swarm intelligence optimization algorithms to improve the optimization efficiency of the algorithms and achieve better adaptive control effects.

Claims

1. The adaptive control method of a two-axis semi-strapdown aviation remote sensing stabilized platform is characterized by: The following steps are involved: Step S1: Establish a disturbance analysis based on the kinematic model of the two-axis semi-strapdown aviation remote sensing stable platform and build a dynamic model; Step S2: The conversion module converts the three-axis disturbance of the body coupled in the visual axis direction into a two-axis disturbance; Step S3: The converted disturbance is superimposed on the platform motor deflection to obtain the influence on the visual axis; Step S4: designing an adaptive controller to achieve stable control of the dynamic model of the constructed two-axis semi-strapdown aviation remote sensing stable platform; The two-axis semi-strapdown aviation remote sensing stabilized platform Represents the body coordinate system, where x is positive when pointing in the direction of the aircraft head. represents the heading platform coordinate system, It is the pitch platform coordinate system. Since the load is mechanically fixed on the pitch platform, the load's visual axis coordinate system is equivalent to the pitch platform coordinate system. The perturbation angular velocity of the visual axis coordinate system is: is the disturbance angular velocity of the pitch platform coordinate system, , They represent the disturbance angular velocity components of the pitch platform coordinate system along the x-axis, y-axis, and z-axis directions, respectively. , They represent the disturbance angular velocity components of the body coordinate system along the x-axis, y-axis, and z-axis directions, respectively. is the heading angle of the heading platform coordinate system relative to the body coordinate system, is the derivative of the heading angle of the heading platform coordinate system relative to the body coordinate system, is the pitch angle of the pitch platform coordinate system relative to the heading platform coordinate system, is the derivative of the pitch angle of the pitch platform coordinate system relative to the heading platform coordinate system; The above formula consists of two parts, namely represents the projection of the aircraft angular velocity disturbance on the pitch platform coordinate system; , They respectively represent the angular velocity components of the aircraft angular velocity disturbance along the x-axis, y-axis, and z-axis in the pitch platform coordinate system; represents the angular velocity disturbance caused by the motion of the stable platform itself; , They respectively represent the disturbance angular velocity components of the stable platform rotation along the x-axis, y-axis, and z-axis in the pitch platform coordinate system; From the above formula, we can see that , should meet the following requirements: ;when is a constant, and are all 0. In this case, if If the requirement is met, the roll axis disturbance is eliminated.

2. The adaptive control method of the two-axis semi-strapdown aviation remote sensing stable platform according to claim 1 is characterized in that: Design the conversion module, use the subscripts 0, 1, 2... to represent the time t0, t1, t2..., and the three-axis disturbance , and The pitch, roll, and heading disturbances coincide with the x0, y0, and z0 axes in the line of sight coordinate system, respectively, and the coordinate system at time t0 is also the stable time coordinate system; and The resultant perturbation in the xoz plane is denoted by , with an angle , at time t0 and The disturbance is eliminated by the corresponding control motors; The corresponding rolling angle generated at time t1 is recorded as , which will cause the visual axis coordinate system at time t1 to deflect around the y axis Angle, causing instability of the visual axis; At t1 and The resultant perturbation in the xoz plane is denoted by , but affected by the roll axis disturbance at time t0, deflection Angle, here recorded as ,Will Decoupling calculation is performed in the coordinate system at time t0, and stable control is performed through the pitch and heading control motors, so as to eliminate the pitch and heading disturbances at time t1 and the rolling disturbances at time t0; In continuous time, the roll disturbance at time t0 is compensated at time t1, and the roll disturbance at time t1 is compensated at time t2, so as to achieve a hysteresis compensation and eliminate the roll axis disturbance; First, calculate the angular velocity of the body at time t0 and couple it to the line of sight coordinate system and The value of is calculated by integration Corresponding angle , then calculate the time t1; They represent the disturbance components along the x-axis and z-axis in the visual axis coordinate system at time t1 respectively; At time t1 and The resultant perturbation in the xoz plane of the visual axis coordinate system; At time t1, it is in the xoz plane of the visual axis coordinate system and The angle between ; is the disturbance component along the y-axis in the visual axis coordinate system at time t0; for The roll angle generated at time t1; the upper and lower limits of the integral are the interval between two samples, which should be as short as possible; is the actual deflection angle of the roll axis of the visual axis coordinate system; At this point, the effect of the rolling disturbance at time t0 is introduced at time t1 and They are respectively the disturbance components along the x-axis and z-axis of the visual axis coordinate system at time t1 after decoupling.

3. The adaptive control method of the two-axis semi-strapdown aviation remote sensing stable platform according to claim 1 is characterized in that: The whale optimization algorithm of Latin hypercube sampling is used to adjust the PID control parameters in real time; assuming that the position of the current best individual is the best foraging position, other individuals will surround the position of the prey based on this best foraging position; the calculation of this process is as follows: D is the distance between the individual and the optimal foraging location; is the current iteration number; is the optimal foraging position currently obtained; is the current personal location; A and C is the control coefficient; and and is a random number in the range [0, 1]; is a decay variable that decreases from 2 to 0; the calculation formula is as follows: Represents the maximum number of iterations; the whale optimization algorithm updates the position by creating a spiral equation to calculate the distance between the individual and the optimal position; the position update calculation formula is as follows is the updated personal location; is the distance between the current individual and the current best foraging position; is the base of natural number logarithm; b is a constant that changes the shape of the spiral; is a random number in the range of [-1, 1]; Used to control the contraction of the spiral and the shape of the spiral; contraction, encirclement and advancement along the spiral path occur simultaneously with equal probability; the calculation formula is as follows; is a random number in the range of [0, 1], used to control the choice of foraging method; when |A|>1, the peripheral individuals are far away from the prey; different from the bubble net feeding stage, the bubble net feeding stage updates the position according to the best foraging position, and the position of the random individual is selected as the reference for the next position update; the calculation formula is as follows: is the position of a random individual; the integral of the time-weighted absolute error ITAE function is selected as the fitness function The general form of a PID controller is as follows: Indicates the controller output signal, represents the system error, are the control parameters of the PID controller respectively.

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