CN113189956A - Servo system online debugging method of two-axis two-frame photoelectric image stabilization platform - Google Patents

Servo system online debugging method of two-axis two-frame photoelectric image stabilization platform Download PDF

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CN113189956A
CN113189956A CN202110380882.9A CN202110380882A CN113189956A CN 113189956 A CN113189956 A CN 113189956A CN 202110380882 A CN202110380882 A CN 202110380882A CN 113189956 A CN113189956 A CN 113189956A
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曲正
徐晓睿
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Changchun Tongshi Optoelectronic Technology Co ltd
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Abstract

The invention relates to an online debugging method for a servo system of a two-axis two-frame photoelectric image stabilization platform, which comprises the following steps: calibrating an open loop transfer model of each loop; setting the expected design bandwidth of the loop as the loop controller gain parameter at the initial moment aiming at any loop, and recursively obtaining the expected gain parameter estimation value and the bandwidth error of the loop controller; discrete transformation is carried out on the gain parameter estimation value and the preset zero position parameter to obtain a discretization control parameter, and closed-loop test is carried out on the set of discretization control parameters to obtain a corresponding test curve; and curing the discretization control parameters corresponding to the ideal test curve as ideal discretization control parameters to the servo control board to complete the debugging of the platform servo system. The invention can carry out real-time and visual servo system regulation and control on the platform, has simple and convenient operation and saves labor and time cost.

Description

Servo system online debugging method of two-axis two-frame photoelectric image stabilization platform
Technical Field
The invention belongs to the technical field of automatic control, and relates to an online debugging method for a servo system of a two-axis two-frame photoelectric image stabilization platform.
Background
The photoelectric platform is used as a packaging device and an integrated carrier of a high-precision sensor, and is widely applied to important fields of industry, aviation, military and the like along with the development of photoelectric information technology and sensor technology in recent years. In the application of a military unmanned system, the main functions of the photoelectric platform are to utilize a high-precision image and a remote sensing detection sensor to realize important functions of reconnaissance search, tracking, positioning and the like of a small-field target.
The servo control system of the platform is an important subsystem for realizing the follow-up of various modes of the platform and ensuring the stability of the visual axis, taking the application of a moving carrier as an example, the platform is rigidly connected with the carrier, and when the carrier moves in space, the platform is subjected to a series of relative disturbances including random vibration of the carrier, attitude disturbance, airflow impact, wind resistance and the like. The servo control system of the platform needs to effectively isolate the relative disturbance and ensure the effective response of the platform to the operation instruction.
From the viewpoint of photoelectric platform system integration, the design of a servo system is not only related to the image stabilization index and the motion index of the platform, but also related to index margin analysis of subsequent system integration. At present, a common debugging method for each loop of the photoelectric platform is as follows: the simulator is connected with a platform servo program, data sampling analysis is carried out in a debug process, data are input into mathematic software such as matlab and the like for model analysis and parameter design, parameters are brought into a driving program for closed loop test, and finally servo program logic is adjusted to enable the platform to have a complete machine function state. The debugging mode of the intervention debug sampling and matlab analysis is complex to operate, has high professional requirements on operators, and needs to be repeatedly switched between embedded software and mathematical software when the debugging is not ideal until an ideal debugging result is obtained, so that the time and labor cost are increased.
Disclosure of Invention
The invention aims to provide an online debugging method for a servo system of a two-axis two-frame photoelectric image stabilization platform, which is convenient to use and can be used for online debugging of a servo control system of the photoelectric platform in real time, high efficiency and intuition.
In order to solve the technical problem, the online debugging method of the servo system of the two-axis two-frame photoelectric image stabilization platform comprises the following steps:
calibrating to obtain an open loop transfer model of each loop of the platform;
for either loop, the following method is used to obtain the desired controller gain parameter and the desired designed bandwidth error:
setting the expected design bandwidth of the loop to BWr and the gain parameter of the loop controller at the initial time to Kg0Calculating the estimated value of the gain parameter of the loop controller at the time k according to the following formula
Figure BDA0003012932770000021
Figure BDA0003012932770000022
Figure BDA0003012932770000023
Wherein K is 1,2, … K, and K is the set iteration number; rk-1The convergence factor at time k-1; qk,k-1Is a set single step quality factor; BW (Bandwidth)k-1The bandwidth at the moment of k-1 is obtained according to the following closed-loop bandwidth expression;
Figure BDA0003012932770000024
σk-1the zero position parameter of the loop controller at the preset k-1 moment is obtained;
calculating the bandwidth error delta BW at the k moment according to the following formulak；
ΔBWk＝BWr-BWk
Wherein, BWkDesigning a bandwidth for the loop at the moment k;
Figure BDA0003012932770000025
σkthe zero position parameter of the loop controller at the preset k moment is obtained;
analyzing the bandwidth error at the moment when K is equal to K, and modifying the value K to carry out iterative estimation again if the bandwidth error is larger; if the bandwidth error is smaller than a set value, calling matlab to carry out discrete transformation on the estimated value of the gain parameter of the controller at the moment when K is equal to K and a preset zero position parameter of the controller to obtain a discretization control parameter of the loop controller, and carrying out closed-loop test on the discretization control parameter set to obtain a corresponding test curve;
the expected design bandwidth BWr of the loop is adjusted repeatedly until an ideal test curve is obtained, and the gain parameter at that time is estimated
Figure BDA0003012932770000031
And a preset zero position parameter sigmaKAs an ideal controller parameter, taking the discretization control parameter at the moment as an ideal discretization control parameter;
and the discretization control parameters of the loop controllers of the pitch axis and the azimuth axis are solidified to the servo control board, so that the debugging of the platform servo system is completed.
The platform comprises three loops of a speed loop, a position loop and a current loop of a pitching axis and three loops of a speed loop, a position loop and a current loop of an azimuth axis.
Furthermore, the open loop transfer model of each loop of the platform can be obtained by using a direct current calibration and sine calibration mode;
furthermore, an open loop transfer model of each loop of the platform can be obtained by utilizing a pseudo-random frequency sweep identification mode.
Furthermore, an open loop transfer model of each loop of the platform can be obtained by a sine frequency sweep identification mode.
The invention can carry out real-time and visual servo system regulation and control on the platform, has simple and convenient operation and saves labor and time cost.
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The present invention will be described in further detail with reference to the accompanying drawings and specific embodiments.
FIG. 1 is a block diagram of a servo system of an opto-electronic platform.
Fig. 2 a-2 d are schematic diagrams of calibration windows of directions of current sensing quantity, gyro speed sensing quantity, encoder sensing quantity and roll speed sensing quantity, respectively.
Fig. 3a and fig. 3b are schematic diagrams of sinusoidal calibration windows of current sensing quantity and acceleration sensing quantity, respectively.
FIG. 4 is a drawing showing
Figure BDA0003012932770000032
At different Qk,k-1The change curves under the action of the values are compared with the graph.
FIG. 5 shows Δ BWkAt different Qk,k-1The change curves under the action of the values are compared with the graph.
FIG. 6 shows σk＝σk-1＝...＝σ1≠σ0Time of flight
Figure BDA0003012932770000033
Schematic diagram of the variation curve of (2).
FIG. 7 shows σk＝σk-1＝...＝σ1≠σ0Time delta BWkSchematic diagram of the variation curve of (2).
Fig. 8 is a schematic diagram of a speed step curve.
FIG. 9 is a schematic view of a position step curve.
FIG. 10 is a flowchart of debug system operation.
The specific implementation mode is as follows:
as shown in fig. 1, the two-axis two-frame photoelectric image stabilization platform servo system includes: the device comprises a three-axis gyroscope, an azimuth motor, a pitching motor, a servo control panel, an azimuth shaft position encoder, a pitching shaft position encoder, an azimuth driving current sensor, a pitching driving current sensor, an upper computer and the like.
In the servo system, the azimuth motor and the pitching motor can adopt direct current torque motors and are respectively responsible for the respective loaded rotary motion of the two shafts of the platform, and the direct excitation signal is a PWM power amplification signal generated by the servo control board.
The servo control board MCU is STM32F4 series chips based on Cortex-M4 framework, can accomplish digital closed-loop control in platform motion, including the analysis and the integration of azimuth axis position encoder, every single move axis position encoder, azimuth drive current sensor, every single move drive current sensor output signal, the loop controller servo control discretization parameter according to the solidification produces azimuth drive signal and every single move drive signal, and realize the digital processing of signal and the closed-loop control of each loop of platform through the mathematical operation, including the closed-loop control of the speed of azimuth axis, angle, three loops of electric current, and the closed-loop control of the speed of every single move axis, angle, three loops of electric current.
The azimuth axis position encoder and the pitch axis position encoder can feed back the azimuth axis angle and the pitch axis angle of the platform in real time, and can also obtain the relative motion angular velocity between the platform and the base through iterative differentiation; the three-axis gyroscope can analyze to obtain the space velocity vector components of the platform in the pitching, azimuth and rolling directions, and can also obtain the acceleration magnitude values of the azimuth axis and the pitching axis of the platform through iterative differentiation; the azimuth driving current sensor and the pitching driving current sensor can feed back the driving currents of the azimuth motor and the pitching motor in real time.
The upper computer is in charge of flow control of system debugging in the debugging process, and is in charge of receiving and analyzing feedback data of the servo control panel in real time, design and operation of parameters of the loop ideal controller and parameters of the ideal discretization control are carried out on the basis, and finally the parameters of the ideal discretization control are transmitted to the servo control panel to realize solidification.
The basic principle of the debugging method is as follows: and (2) on the platform, under the condition of ensuring the communication between the upper computer and the servo control board, carrying out open-loop excitation on the platform, and calculating to obtain each loop open-loop transfer model of the platform by using direct current calibration and sine calibration, wherein the direct current calibration is used for determining feedback symbols of each-step sensing quantity (including current sensing quantity of an azimuth axis motor and a pitch axis motor, encoder sensing quantity of an azimuth axis and a pitch axis, and speed sensing quantity of pitching, azimuth and roll of a gyroscope), and the sine calibration is used for determining a physical scale factor and a time delay constant of the open-loop transfer model in the transfer process, so as to obtain the open-loop model of each loop of the platform. The schematic diagrams of the direction calibration window are shown in fig. 2 a-2 d (wherein fig. 2b is the calibration window switchable to the gyro pitch rate sensing amount or the gyro azimuth rate sensing amount).
The upper computer debugging software is communicated with the servo control board in a full-duplex serial port communication mode, the upper computer undertakes to send debugging flow instructions and discretization of servo control parameters of the loop controller at regular time, and analyzes servo driving states and sensor feedback data in real time, and visual display in each state bar is achieved. The default debugging sequence of the two-axis two-frame platform is that the pitching debugging is carried out firstly and then the azimuth debugging is carried out, it needs to be explained that an operator can only manually switch to a corresponding debugging process of the azimuth axis after the zero point calibration (correction) of the pitching encoder is completed because of the constraint of the orthogonal decoupling of the gyro sensitive coordinate system, otherwise, the servo debugging of the azimuth axis cannot be carried out.
The invention discloses an online debugging method for a servo system of a two-axis two-frame photoelectric image stabilization platform, which comprises the following steps:
step one, obtaining an open loop transfer model of each loop of the platform by using a direct current calibration and sine calibration mode, or obtaining an open loop transfer model of each loop of the platform by using a pseudo-random frequency sweep identification mode or a sine frequency sweep identification mode.
Debugging three loops of a current loop, a speed loop and a position loop of the pitch axis, and debugging three loops of the current loop, the speed loop and the position loop of the azimuth axis; the debugging method of each loop is the same, taking the speed loop of the pitch axis as an example, the specific debugging method is as follows:
let BW be fb{ Kg, σ, g(s) } is a closed-loop bandwidth expression, where g(s) is an open-loop transfer function, Kg is a loop controller gain parameter, and σ is a loop controller zero position parameter. Setting the expected design bandwidth of the loop as BWr, bandwidth BW at moment k-1k-1To obtain K from equation (1), K is 1,2, … K, K is a set number of iterations, and the value is set according to the analysis result of the bandwidth error;
Figure BDA0003012932770000051
wherein
Figure BDA0003012932770000052
The loop controller gain parameter at the time k-1; sigmak-1The zero point position parameter of the loop controller at the moment of k-1;
let the convergence factor at time k-1 be Rk-1；
Figure BDA0003012932770000061
Wherein Qk,k-1For a set single step quality factor, the error statistics of the actual bandwidth can be combined to design Qk,k-1A variation trajectory of the values. Calculating the gain parameter estimation value of the loop controller at the k moment according to the formula (3)
Figure BDA0003012932770000062
Figure BDA0003012932770000063
Setting the gain parameter of the loop controller at the initial time to Kg0Then recursion can be obtained from the above formula
Figure BDA0003012932770000064
Further, the design bandwidth BW of the loop at the current time (i.e. k time) can be calculated according to the formula (5)k；
Figure BDA0003012932770000065
In the recursive process, the bandwidth error at time k is
ΔBWk＝BWr-BWk (6)
The performance analysis and error analysis of the above recursive estimation method can be divided into two cases:
1)σk＝σk-1＝...＝σ1＝σ0in the case of
That is, the zero point of the loop controller is kept at the initial position in the recursion process, and the expected design bandwidth of the loop and the gain parameter Kg of the loop controller at the initial moment are utilized0To obtainAnd obtaining the dynamic change of the gain parameter estimated value of the loop controller and the bandwidth of the k time corresponding to the dynamic change of the gain parameter estimated value of the loop controller.
Taking the experimental platform used herein as an example, if the sine calibration is performed to obtain the transfer function of the open loop of the current loop as
Figure BDA0003012932770000066
Loop controller gain parameter Kg at initial time0＝231.14，σ0Calculating to obtain the initial bandwidth BW of the current closed loop according to the formula (1) — 666.70Q is given by the formulae (1) to (7) in the case of BW γ of 200Hz, 63.924Hzk,k-11 and Qk,k-1When 2 is true
Figure BDA0003012932770000067
And Δ BWkAs shown in fig. 5 and 6, respectively.
It can be seen that σk＝σk-1＝...＝σ1＝σ0While the recursion curve has a smooth convergence trend in the convergence region, Qk,k-1The selection of the bandwidth has certain influence on the convergence speed and the convergence static difference of the bandwidth to a certain extent.
2)σk≠σ0In the case of
I.e. the final zero position of the controller changes compared to the initial zero position, since sigma can be set during recursion1,σ2,...,σk-1Regarded as process variables, σ for simplicity of designk≠σ0Can be equivalent to sigmak＝σk-1＝...＝σ1≠σ0While keeping g(s) in 1) and initial parameters of the controller (including initial loop controller gain parameter Kg0And zero position parameter σ0) Do not change, let σk＝σk-1＝...＝σ1＝-100， Q k,k-12 to obtain
Figure BDA0003012932770000072
And Δ BWkThe variation curves of (a) are shown in fig. 7 and fig. 8, respectively.
It can be seen that the curve jumps to some extent when the zero point position of the loop controller changes, but finally converges, which indicates that the equations (1) - (7) have better stability in the recursive convergence process.
Analyzing the bandwidth error at the moment when K is equal to K, and modifying the value K to carry out iterative estimation again if the error is larger; if the error is ideal (namely smaller than a set value), calling matlab to carry out discrete transformation on the controller gain parameter at the moment when K is equal to K and a preset controller zero position parameter to obtain a discretization control parameter of the loop controller, and carrying out closed-loop test on the discretization control parameter to obtain a test curve of the loop; during the debugging process, the loop expected design bandwidth BWr of each loop may be iteratively adjusted until an ideal test curve is obtained, giving a set of ideal test curves as shown in fig. 9 and 10. Estimate of gain parameter considered at that time
Figure BDA0003012932770000071
And a preset zero position parameter sigmaKThe ideal controller parameters are considered to be the discretization control parameters of the expected controller at the moment;
and executing a parameter curing instruction in the upper computer debugging system, and curing ideal discrete control parameters of each loop of the pitch axis and the azimuth axis to the servo control board to finish the debugging of the platform servo system. The debugging system overall debugging flow is shown in fig. 10.
First step pitching encoder zero point standardization: in the pitching debugging process, firstly, a platform pitching shaft system is manually rotated, a visual axis of the pitching shaft is made to be parallel to a horizontal plane where the platform is placed, a pitching installation zero point key is clicked to obtain, an upper computer intercepts original data of a pitching shaft position encoder reported by a servo control program at the current moment, the data is analyzed and cached, and the data is used as an encoder zero point compensation value and is transmitted back to the servo control program, so that the calibration of the platform pitching shaft installation zero point is realized.
And secondly, calibrating the pitching direction: pressing down click direction calibration and debugging process start keys one by one, executing direct-current open-loop motion by a pitching axis, and simultaneously carrying out data acquisition on pitching current, gyro speed and encoder linear position returned by a servo system by an upper computer; and pressing a debugging process stop key, stopping data acquisition by the upper computer, and drawing the change of each-step sensing quantity of the pitching axis in the motion process. The direction signs of the sensing quantities of all steps are obtained by observing the change trend of the curve, and are transmitted to a servo control program in the form of positive and negative coefficients to realize the calibration of the direction of the sensor.
Thirdly, sine calibration: the sine calibration and debugging process start keys are pressed one by one, the pitching shaft executes open-loop sine single-frequency motion, the upper computer simultaneously acquires data of pitching current and acceleration returned by the servo, the execution logic of the upper computer is the same as that of the second step, after the debugging process stop keys are pressed, data acquisition is stopped, and the upper computer draws sine waveforms of current and acceleration sensing quantities corresponding to the platform in the motion process. The two sensing quantities are subjected to phase matching processing in the servo control program, so that the upper computer can acquire peak data corresponding to the two sinusoidal curves in the same period, and the peak data is processed as follows to finally obtain physical quantities required in the process of establishing each loop model.
Kt＝|imax|/|Apwm|·…………………………………(8)
Km＝|amax|/|imax|…………………………………(9)
Kc＝|imax|/|amax|…………………………………(10)
K in formulae 8-10tFor the amplitude calibration coefficient of the current model, KmScale factor, K, for current closed loop integration to velocity loopcIs a feed forward compensation coefficient. ImaxL is the peak current value, | amaxI is the peak value of acceleration, ApwmAnd | is the sinusoidal amplitude for a given PWM.
Fourthly, generating servo control parameters: according to the system index requirements of the platform, the loop bandwidth is subjected to specific combined design, and the expected design bandwidth of each loop of the pitch axis is respectively input into a column input by the controller. BW (Bandwidth)i、BW1、BW2、BWpAnd respectively designing the expected design bandwidth of a current loop, the expected design bandwidth of a speed inner loop, the expected design bandwidth of a speed outer loop and the expected design bandwidth of a position loop. And pressing a key for generating the servo parameters to enable the upper computer to call matlab packaging, calculating by combining input quantities generated in the third step and the fourth step by the matlab, obtaining discretization control parameters of each loop controller, and sending the discretization control parameters to a servo control program through a serial port.
And a fifth step of parameter testing: in order to verify whether the sensor symbol configuration in the step two is correct and whether the control parameters generated in the step four are ideal, a platform steady state test, a speed step test and a position test are specially designed, and the tests are executed one by one to obtain an evaluation result.
Sixthly, azimuth debugging: if the loop performance is ideal after the parameters are corrected, the method can enter the azimuth debugging process to continue the relevant debugging of the azimuth axis, otherwise, the method returns to the fourth step, and the bandwidth combination is analyzed and adjusted again according to the test result. The debugging process of the azimuth axis is approximately the same as that of the pitching debugging process, only the change trends of the azimuth gyro speed component and the roll gyro speed component need to be simultaneously observed when the direction of the azimuth axis sensing quantity is calibrated in the second step, and the gyro signs of the azimuth and the roll are simultaneously configured, so that the stability of the platform in the over-top area is ensured. Accordingly, the first to sixth steps are repeatedly performed on the azimuth axis to obtain the loop correction result of the azimuth axis.
And seventhly, curing the parameters, namely pressing down a parameter curing key to enable the servo control program to enter a flash curing process to cure the control parameters, and after the parameters are cured, switching the platform from a debugging response mode to a complete machine working mode through logic control by the servo control program, so that the whole process of online debugging of the upper computer of the two-axis two-frame platform is completed. In addition, the upper computer debugging software also has a parameter storage function. And after debugging is finished, pressing a parameter storage key to store the serial numbers of all servo related variables. Therefore, on one hand, the debugging platform can be used as an archive backup, on the other hand, when the same type of platform or other operators are debugged again, a file loading function can be selected, and the loading control parameters are used as references, so that the debugging efficiency is improved.
And the servo system debugging and platform related motion functions of the photoelectric platform are realized by utilizing system model calibration, controller parameter correction and logic functions.

Claims (5)

1. A servo system online debugging method of a two-axis two-frame photoelectric image stabilization platform is characterized by comprising the following steps:
calibrating to obtain an open loop transfer model of each loop;
for either loop, the following method is used to obtain the desired controller gain parameter and the desired designed bandwidth error:
setting the expected design bandwidth of the loop to BWr and the gain parameter of the loop controller at the initial time to Kg0Calculating the estimated value of the gain parameter of the loop controller at the time k according to the following formula
Figure FDA0003012932760000011
Figure FDA0003012932760000012
Figure FDA0003012932760000013
Wherein K is 1,2, … K, and K is the set iteration number; rk-1The convergence factor at time k-1; qk,k-1Is a set single step quality factor; BW (Bandwidth)k-1The bandwidth at the moment of k-1 is obtained according to the following closed-loop bandwidth expression;
Figure FDA0003012932760000014
σk-1the zero position parameter of the loop controller at the preset k-1 moment is obtained;
calculating the bandwidth error delta BW at the k moment according to the following formulak；
ΔBWk＝BWr-BWk
Wherein, BWkDesigning a bandwidth for the loop at the moment k;
Figure FDA0003012932760000015
σksetting a zero position parameter of a loop controller at a preset k moment;
analyzing the bandwidth error at the moment when K is equal to K, and modifying the value K to carry out iterative estimation again if the bandwidth error is greater than a set value; if the bandwidth error is smaller than a set value, calling matlab to carry out discrete transformation on the estimated value of the gain parameter of the controller at the moment when K is equal to K and a preset zero position parameter of the controller to obtain a discretization control parameter of the loop controller, and carrying out closed-loop test on the discretization control parameter set to obtain a corresponding test curve;
the expected design bandwidth BWr of the loop is adjusted repeatedly until an ideal test curve is obtained, and the gain parameter estimation value is obtained at the moment
Figure FDA0003012932760000021
And a preset zero position parameter sigmaKAs an ideal controller parameter, taking the discretization control parameter at the moment as an ideal discretization control parameter;
and (4) solidifying the discretization control parameters of the loop controllers of the pitch axis and the azimuth axis to the servo control board to finish the debugging of the platform servo system.
2. The online debugging method for the servo system of the two-axis two-frame photoelectric image stabilization platform according to claim 1, wherein the platform comprises three loops of a pitch axis speed loop, a position loop and a current loop, and three loops of an azimuth axis speed loop, a position loop and a current loop.
3. The online debugging method for the servo system of the two-axis two-frame photoelectric image stabilization platform according to claim 1, wherein an open-loop transfer model of each loop of the platform is obtained by using a direct-current calibration and a sine calibration mode.
4. The online debugging method for the servo system of the two-axis two-frame photoelectric image stabilization platform according to claim 1, wherein an open-loop transfer model of each loop of the platform is obtained by using a pseudorandom frequency sweep identification mode.
5. The online debugging method for the servo system of the two-axis two-frame photoelectric image stabilization platform according to claim 1, wherein an open-loop transfer model of each loop of the platform is obtained by a sine frequency sweep identification method.
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