CN112504269B - Shaft angular speed estimation method applied to semi-strapdown stable platform - Google Patents
Shaft angular speed estimation method applied to semi-strapdown stable platform Download PDFInfo
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- CN112504269B CN112504269B CN202011081091.8A CN202011081091A CN112504269B CN 112504269 B CN112504269 B CN 112504269B CN 202011081091 A CN202011081091 A CN 202011081091A CN 112504269 B CN112504269 B CN 112504269B
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Classifications
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/10—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration
- G01C21/12—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning
- G01C21/16—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning by integrating acceleration or speed, i.e. inertial navigation
- G01C21/165—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning by integrating acceleration or speed, i.e. inertial navigation combined with non-inertial navigation instruments
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/20—Instruments for performing navigational calculations
Abstract
The invention relates to a shaft angular velocity estimation method applied to a semi-strapdown stable platform, which is used for obtaining the shaft angular velocity with high data update rate, independent channels and high algorithm convergence rate by parallel high-speed sampling of each frame angle of the stable platform on an FPGA and realizing a tracking differential algorithm by adopting hardware language for the small stable platform which is difficult to install an inertial measurement sensor on a universal joint load. The visual axis inertial angular velocity is obtained through fusion and reconstruction of the axis angular estimated velocity and the base inertial angular velocity, and the visual axis inertial angular velocity is used as feedback information to realize the inertial stabilization of the visual axis. The sampling interval, the convergence factor and the output noise of the shaft angle estimation algorithm are optimized, so that the shaft angle estimation speed matched with the frequency and the time delay of the output signal of the inertia measurement element is obtained, the inhibition capability of the stabilized platform to the disturbance of the base is enhanced, and the pointing accuracy of the optical axis is improved.
Description
Technical Field
The invention relates to a shaft angular velocity estimation method applied to a semi-strapdown stable platform, and belongs to the technical field of photoelectric detection.
Background
The main task of the airborne photoelectric stabilized platform is to isolate disturbance of a carrier base and ensure stable pointing of an optical axis in an inertial space. However, in a miniaturized photoelectric stabilization platform, the space is compact, the load on the universal joint is light, and it is difficult to install an inertial measurement element with higher accuracy to directly measure the angular velocity of the viewing axis. Because of the limitation of the size and weight of the load, the miniaturized stabilized platform is difficult to install an inertial measurement element with enough precision on a frame, and the measurement of the visual axis inertial angular velocity cannot be directly realized, so that the inertial measurement element needs to be installed on a base except a universal joint, and the semi-strapdown stabilized platform is formed by combining the base inertial angular velocity with the frame angular velocity information, performing coordinate conversion, and then reconstructing to obtain the visual axis inertial angular velocity. Therefore, the shaft angular velocity sensor cannot be mounted due to the size limitation of the universal joint, and only the angular velocity can be estimated from the shaft angular position. The level of shaft angular velocity estimation directly affects the stability performance of the stabilized platform's visual axis. The key to semi-strapdown stabilization is the frequency response and accuracy of the shaft angular velocity. The photoelectric stable platform is used for realizing the indication and tracking of the maneuvering target, the speed range is wide, and the shaft angular speed obtained through the traditional position difference is difficult to meet the requirements on both precision and frequency response. Therefore, the shaft angular velocity must be estimated effectively to meet the requirements of frequency response and precision of velocity information in a larger range, key information is provided for reconstructing the visual shaft angular velocity of the semi-strapdown stable platform, and the control performance of the stable platform is improved.
Disclosure of Invention
Technical problem to be solved
In order to solve the defect that the shaft angular speed obtained by the traditional position difference is difficult to meet the requirements on both precision and frequency response, the invention provides a shaft angular speed estimation method applied to a half strapdown stable platform. Based on the existing stabilized platform shaft angle sensor, the shaft angle speed is estimated by a tracking differential algorithm.
Technical proposal
The shaft angular speed estimation method applied to the semi-strapdown stable platform is characterized by comprising the following steps of:
step 1: determining the execution frequency, the data bit width and the integration step length;
step 2: determining parameters of a tracking differentiator: a speed factor r;
step 3: the nonlinear differential tracking method is executed as follows:
3-1: initializing nonlinear tracking differentiator parameters: tracking position x 1 (k) Estimated speed x 2 (k) Intermediate variables e (k), d 0 、y、a 0 All initialized to 0;
3-2: judging whether an execution starting signal is received, if yes, sending a synchronous clock signal, reading an encoder position value in a register, converting the encoder position value into a single-precision floating point type, and entering a step 3-3, and if not, continuing to execute the step 3-2;
3-3: sequentially calculating variables e (k), d in formula (1) 0 、y、a 0 Values and stored in registers;
wherein h is 0 Is a filtering factor;
3-4: calculating the value of variable a: judging whether |y| is greater than d 0 If yes, executing the calculation of the formula (2), otherwise, executing the calculation of the formula (3);
3-5: calculating the value of the variable fhan: judging whether the absolute value a is larger than d, if so, executing the calculation of the formula (4), otherwise, executing the calculation of the formula (5);
fhan＝-r·sign(a) (4)
3-6: calculating tracking position x 1 (k+1), estimated speed x 2 (k+1) value:
3-7: the calculated tracking position signal x 1 (k+1) and the estimated speed signal x 2 (k+1) converting into integer data and storing the integer data into a corresponding register;
3-8: the cycle is performed 3-2 to 3-7.
The technical scheme of the invention is as follows: the determination method of the step 1 is as follows: the execution frequency is less than or equal to the data reading frequency of the encoder and less than or equal to the updating frequency of the encoder; the data bit width is more than or equal to the data bit width of the shaft encoder; the integration step h is initially set to the execution period.
The technical scheme of the invention is as follows: the initial value of the speed factor r in step 2 is chosen to be any value greater than 0 and less than 1/(2 h), wherein is the integration step size.
The technical scheme of the invention is as follows: filtering factor h in step 3-3 0 Set to the integral step value.
The technical scheme of the invention is as follows: the method described in step 3 operates in parallel in the FPGA.
A method for performance adjustment of shaft angular velocity is characterized in that: executing an axle angular speed estimation method, collecting an estimated speed signal, and comparing and checking with data collected by a standard speed estimation device; if the phase lag is found to be too large, the speed factor is increased; if the speed measuring noise is found to be too large, increasing a filtering factor; until the requirements are met.
The technical scheme of the invention is as follows: the standard speed estimation device is a gyroscope and a velocimeter.
Advantageous effects
The invention provides a shaft angular velocity estimation method applied to a semi-strapdown stable platform. The method introduces a tracking differentiator technology into the shaft angular speed estimation, replaces differentiation by an integral method, overcomes the defect of noise amplification caused by the traditional angular position differentiation, and can reasonably extract differential signals from discrete signals with random noise. An angular position signal is input to the tracking differentiator, an angular position tracking signal and an angular speed estimation signal are output, and an algorithm implementation mode is a key of whether the angular speed estimation effect is excellent. By means of flexible interfaces, powerful parallel operation and high-precision counting capability of the FPGA, the parallel high-speed sampling of each frame angle of the stable platform on the FPGA and the synchronous output of the shaft angle estimation speed by using a hardware description language, the shaft angle speed estimation method with high data update rate, independent channels and high algorithm convergence speed is obtained, high-quality feedback information is provided for the semi-strapdown stable platform, the accuracy of optical axis pointing is improved, and the method has wide application prospect.
Drawings
FIG. 1A flow chart of the invention
Detailed Description
The shaft angular velocity estimation method applied to the semi-strapdown stable platform is designed to realize high-speed parallel acquisition of shaft angular positions, realize tracking differential algorithm by hardware description language and synchronously output shaft angular velocity estimation rate by virtue of flexible interfaces, powerful parallel operation and timing functions of the FPGA, so that the shaft angular velocity with high data update rate, independent channels and high algorithm convergence rate is obtained. The shaft angular speed obtained by the method has higher precision in a wider range, provides high-quality feedback information for the semi-strapdown stable platform, enhances the anti-interference capability of the stable platform, and improves the accuracy of optical axis pointing. Mainly involves two aspects:
1. shaft angular velocity estimation algorithm. The method mainly comprises the following steps:
the first step, determining the execution frequency, the data width and the integral step length of an axle angle estimation algorithm, wherein the determining method comprises the following steps: the execution frequency of the shaft angle estimation algorithm is less than or equal to the data reading frequency of the encoder and less than or equal to the updating frequency of the encoder; the algorithm data bit width is more than or equal to the data bit width of the shaft encoder; the integration step h is initialized to be set as an algorithm execution period (in s).
Second, the parameters of the tracking differentiator are preliminarily determined: a speed factor r, the initial value of which is chosen to be any value greater than 0 and less than 1/(2 h), wherein the speed factor r is the integral step length and the filter factor h 0 Set to the integral step value.
Third, a nonlinear differential tracking algorithm is executed, see fig. 1, specifically as follows:
1) Initializing nonlinear tracking differentiator parameters. Tracking position x 1 (k) Estimated speed x 2 (k) Intermediate variables e (k), d 0 、y、a 0 All initialized to 0;
2) Judging whether an algorithm start executing signal is received, if yes, sending a synchronous clock signal, reading an encoder position value in a register, converting the encoder position value into a single-precision floating point type, and entering the step 3), and if not, continuing to execute the step 2);
3) Sequential calculation formula(1) And stores variables e (k), d in registers 0 、y、a 0 A value;
4) The value of variable a is calculated. Judging whether |y| is greater than d 0 If yes, executing the calculation of the formula (2), otherwise, executing the calculation of the formula (3);
5) The value of the variable fhan is calculated. Judging whether the absolute value a is larger than d, if so, executing the calculation of the formula (4), otherwise
Performing the calculation of equation (5);
fhan＝-r·sign(a) (4)
6) Calculating tracking position x 1 (k+1), estimated speed x 2 (k+1) value.
7) The calculated tracking position signal x 1 (k+1) and the estimated speed signal x 2 (k+1) converting into integer data and storing the integer data into a corresponding register;
8) Periodically executing the steps 2) to 7).
2. A shaft angular velocity estimation method performance debugging method. The method for debugging the performance of the shaft angular velocity estimation method is also one of the contents of the invention. The periodic cycle execution of the shaft angular velocity estimation algorithm will be estimatedAngular velocity is measured. Changing the speed factor r and the filtering factor h in the second step 0 The initial value can change the estimation effect of the shaft angular speed estimation method, gradually adjust the speed factor and the filter factor, and realize the speed estimation performance with different effects. The speed factor and filtering factor parameter debugging method comprises the following steps: increasing the speed factor r increases the speed estimation bandwidth, increases the estimation noise, decreases the speed factor r, decreases the estimation noise, but decreases the speed estimation bandwidth. Increasing the filtering factor h 0 The speed estimation noise may be reduced but the estimation bandwidth may also be reduced.
In order to make the technical scheme and the advantages of the invention clearer, an axial angular velocity estimation method applied to a half strapdown stable platform is illustrated by an example aiming at an encoder with 2 paths of data, the maximum refresh frequency of which is 5 KHz and the data bit width of which is 16 bits. The detailed steps are as follows:
1. shaft angular velocity estimation algorithm. The method mainly comprises the following steps:
the method comprises the steps that firstly, the maximum data refresh rate of an encoder is 5k Hz, the data bit width is 16 bits, the data reading frequency of the encoder is smaller than or equal to the data updating frequency of the encoder according to the frequency smaller than or equal to the encoder updating frequency method executed by an axis angle estimation algorithm, the data reading frequency of the encoder is 4k Hz, and the frequency executed by the axis angle estimation algorithm is 2k Hz; according to the data bit width method that the algorithm data bit width is more than or equal to the shaft encoder, the data bit width in the FPGA estimation algorithm is selected to be 32 bits, and the integration step h is initialized and set to be 0.0005s of the algorithm execution period.
Step two, the initial value of the speed factor is selected to be 500, and the filtering factor h 0 Set to an integral step value of 0.0005.
And thirdly, executing a nonlinear differential tracking algorithm, which specifically comprises the following steps:
1) Initializing nonlinear tracking differentiator parameters. Tracking position x 1 (k) Estimated speed x 2 (k) Intermediate variables e (k), d 0 、y、a 0 All initialized to 0;
2) Judging whether an algorithm start executing signal is received, if yes, sending a synchronous clock signal, reading an encoder position value in a register, converting the encoder position value into a single-precision floating point type, and entering the step 3), and if not, continuing to execute the step 2);
3) The variables e (k), d and d are calculated in the sequential calculation formula (1) and stored in registers 0 、y、a 0 A value;
4) Calculating the value of the variable a, and judging whether the value of the absolute value y is larger than d 0 If yes, executing a formula (2), otherwise executing a formula (3);
5) Judging whether the absolute a is larger than d, if so, executing the formula (4), otherwise, executing the formula (5);
6) Calculating the tracking position x according to formula (6) 1 (k+1), estimated speed x 2 (k+1) value.
7) The calculated position signal x 1 (k+1) and the estimated speed signal x 2 (k+1) converting into integer data and storing the integer data into a corresponding register;
8) The steps 2) to 7) are cyclically executed.
2. And (5) debugging the performance of the shaft angular speed estimation method. The specific debugging steps are as follows:
1) Executing an axle angular speed estimation algorithm, acquiring an estimated speed signal, and comparing and checking with data acquired by a standard speed estimation device (such as a gyroscope, a velocimeter and the like);
2) If the phase lag is found to be too large, increasing the speed factor r in the second step to be 1000 according to the requirement;
3) Re-executing the step 1), collecting speed data, comparing the speed measurement noise with the standard speed estimation device to increase the filter factor to 0.0008;
4) Re-executing the step 1), collecting speed data, comparing the speed data with a standard speed estimation device, and finding that the speed data meets the requirement;
5) And (5) debugging the speed estimation algorithm.
The tracking differential algorithm is realized through FPGA parallel operation, the speed is high, the updating frequency is high, and the convergence speed and noise of the tracking differential algorithm can be flexibly adjusted. The estimated shaft angle speed realized by the FPGA is equivalent to the bandwidth and delay of the inertial measurement unit, and can be effectively information fused, so that the visual shaft angle speed of the stabilized platform is obtained by reconstruction, the disturbance inhibition capability of the photoelectric stabilized platform is enhanced, the visual shaft pointing accuracy is improved, and the method has wide application prospect.
Claims (7)
1. The shaft angular speed estimation method applied to the semi-strapdown stable platform is characterized by comprising the following steps of:
step 1: determining the execution frequency, the data bit width and the integration step length;
step 2: determining parameters of a tracking differentiator: a speed factor r;
step 3: the nonlinear differential tracking method is executed as follows:
3-1: initializing nonlinear tracking differentiator parameters: tracking position x 1 (k) Estimated speed x 2 (k) Intermediate variables e (k), d 0 、y、a 0 All initialized to 0;
3-2: judging whether an execution starting signal is received, if yes, sending a synchronous clock signal, reading an encoder position value in a register, converting the encoder position value into a single-precision floating point type, and entering a step 3-3, and if not, continuing to execute the step 3-2;
3-3: sequentially calculating variables e (k), d in formula (1) 0 、y、a 0 Values and stored in registers;
wherein h is 0 Is a filtering factor;
3-4: calculating the value of variable a: judging whether |y| is greater than d 0 If yes, executing the calculation of the formula (2), otherwise, executing the calculation of the formula (3);
3-5: calculating the value of the variable fhan: judging whether the absolute value a is larger than d, if so, executing the calculation of the formula (4), otherwise, executing the calculation of the formula (5);
fhan＝-r·sign(a) (4)
3-6: calculating tracking position x 1 (k+1), estimated speed x 2 (k+1) value:
x 1 (k+1)＝x 1 (k)+h·x 2 (k)
x 2 (k+1)＝x 2 (k)+h·fhan(e(k),x 2 (k),r,h 0 ) (6)
3-7: the calculated tracking position signal x 1 (k+1) and the estimated speed signal x 2 (k+1) converting into integer data and storing the integer data into a corresponding register;
3-8: the cycle is performed 3-2 to 3-7.
2. The method for estimating the shaft angular velocity applied to the semi-strapdown stabilization platform according to claim 1, wherein the determining method in the step 1 is as follows: the execution frequency is less than or equal to the data reading frequency of the encoder and less than or equal to the updating frequency of the encoder; the data bit width is more than or equal to the data bit width of the shaft encoder; the integration step h is initially set to the execution period.
3. The method for estimating the angular velocity of the shaft applied to the semi-strapdown stabilization platform according to claim 1, wherein the initial value of the velocity factor r in the step 2 is selected to be any value greater than 0 and less than 1/(2 h), where h is an integration step size.
4. The method for estimating the axial angular velocity applied to the semi-strapdown stabilization platform according to claim 1, wherein the filtering factor h in the step 3-3 0 Set to the integral step value.
5. The method for estimating the angular velocity of the shaft applied to the semi-strapdown stabilization platform according to claim 1, wherein the method in the step 3 is operated in parallel in the FPGA.
6. A method of performance tuning of the angular shaft speed obtained in claim 1, characterized by: executing an axle angular speed estimation method, collecting an estimated speed signal, and comparing and checking with data collected by a standard speed estimation device; if the phase lag is found to be too large, the speed factor is increased; if the speed measuring noise is found to be too large, increasing a filtering factor; until the requirements are met.
7. The method for performing performance tuning of angular velocity of shaft of claim 6, wherein said standard velocity estimation device is a gyroscope or a velocimeter.
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| CN102679979A (en) * | 2012-05-18 | 2012-09-19 | 北京航空航天大学 | Method for monitoring working mode of aerial remote sensing triaxial inertia stabilization platform |
| CN110658839A (en) * | 2019-10-08 | 2020-01-07 | 西北工业大学 | Virtual optical axis-based strapdown seeker guidance information extraction method |
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| US8825435B2 (en) * | 2010-02-19 | 2014-09-02 | Itrack, Llc | Intertial tracking system with provision for position correction |
| CN109341679A (en) * | 2018-09-30 | 2019-02-15 | 华中科技大学 | A kind of smart machine air navigation aid and navigation system |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN102679979A (en) * | 2012-05-18 | 2012-09-19 | 北京航空航天大学 | Method for monitoring working mode of aerial remote sensing triaxial inertia stabilization platform |
| CN110658839A (en) * | 2019-10-08 | 2020-01-07 | 西北工业大学 | Virtual optical axis-based strapdown seeker guidance information extraction method |
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| 跟踪微分算法在半捷联稳定平台中的应用研究;刘伟;朱斌;樊键;尹彦东;;弹箭与制导学报(第02期);41-44 * |
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