CN116774587A - Photoelectric tracking system control method based on self-adaptive error observer - Google Patents
Photoelectric tracking system control method based on self-adaptive error observer Download PDFInfo
- Publication number
- CN116774587A CN116774587A CN202310815933.5A CN202310815933A CN116774587A CN 116774587 A CN116774587 A CN 116774587A CN 202310815933 A CN202310815933 A CN 202310815933A CN 116774587 A CN116774587 A CN 116774587A
- Authority
- CN
- China
- Prior art keywords
- tracking system
- loop
- filter
- disturbance
- signal
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 57
- 230000008859 change Effects 0.000 claims abstract description 12
- 230000001629 suppression Effects 0.000 claims abstract description 7
- 230000003044 adaptive effect Effects 0.000 claims description 22
- 238000001914 filtration Methods 0.000 claims description 10
- 230000003287 optical effect Effects 0.000 claims description 10
- 230000004044 response Effects 0.000 claims description 8
- 230000008569 process Effects 0.000 claims description 6
- 238000005070 sampling Methods 0.000 claims description 5
- 230000000007 visual effect Effects 0.000 claims description 5
- 230000010355 oscillation Effects 0.000 claims description 3
- 238000001228 spectrum Methods 0.000 claims description 2
- 230000007613 environmental effect Effects 0.000 abstract 1
- 230000002401 inhibitory effect Effects 0.000 abstract 1
- 238000010586 diagram Methods 0.000 description 8
- 230000000694 effects Effects 0.000 description 4
- 230000010485 coping Effects 0.000 description 3
- 238000013461 design Methods 0.000 description 2
- 238000004088 simulation Methods 0.000 description 2
- 230000001133 acceleration Effects 0.000 description 1
- 238000013459 approach Methods 0.000 description 1
- 230000006399 behavior Effects 0.000 description 1
- 230000015556 catabolic process Effects 0.000 description 1
- 238000011217 control strategy Methods 0.000 description 1
- 230000007423 decrease Effects 0.000 description 1
- 238000006731 degradation reaction Methods 0.000 description 1
- 238000012938 design process Methods 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 230000005764 inhibitory process Effects 0.000 description 1
- 230000001788 irregular Effects 0.000 description 1
- 238000013178 mathematical model Methods 0.000 description 1
- 238000005259 measurement Methods 0.000 description 1
- 230000005693 optoelectronics Effects 0.000 description 1
- 230000009467 reduction Effects 0.000 description 1
- 230000001105 regulatory effect Effects 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 230000009466 transformation Effects 0.000 description 1
Landscapes
- Feedback Control In General (AREA)
Abstract
The invention discloses a photoelectric tracking system control method based on a self-adaptive error observer, which is mainly used for improving the tracking capacity of a system to unknown change input signals and the inhibiting capacity of the system to unknown time-varying narrow-band disturbance and improving the tracking precision of a photoelectric tracking system. The invention firstly establishes the error observer structure to observe the input and disturbance sum signals, then identifies the observation signals from the frequency domain, and finally adjusts the parameters of the controller in real time and on line, thereby reducing the tracking error of the system. The invention can solve the tracking problem and the disturbance rejection problem of the system at the same time, and performs frequency domain identification analysis on the observed signal under the condition of unknown and variable input and disturbance, thereby adaptively changing the parameters of the controller and improving the tracking capability of the system on a moving target and the suppression capability of the system on complex environmental disturbance.
Description
Technical Field
The invention belongs to the field of tracking control, and particularly relates to a photoelectric tracking system control method based on a self-adaptive error observer, which is mainly used for coping with unknown change input and unknown time-varying narrow-band disturbance and improving the tracking precision of a photoelectric tracking system.
Background
In the photoelectric tracking system, tracking accuracy is susceptible to degradation due to the motion characteristics of the target and external disturbances. On one hand, the target object movement is irregular, the target track is not easy to acquire, and the improvement of the tracking capacity of the system is limited; on the other hand, the carrier of the photoelectric tracking equipment arranged on the motion platform of an airplane, a ship and the like can also transmit low-frequency broadband disturbance and narrow-band disturbance to the equipment, so that the tracking precision of the system is affected. In previous studies, tracking problems and anti-interference problems were also generally discussed separately. The A Modified Disturbance Observer Structure Based on Acceleration Measurement for Disturbance Suppression in Tracking Control System utilizes the disturbance observer structure to compensate the external disturbance of the photoelectric tracking system, so that the anti-disturbance capability of the system can be effectively improved, but the tracking performance cannot be improved. The document Error-Based Observer ofa Charge Couple Device Tracking Loop for Fast Steering Mirror proposes an Error observer structure, and utilizes Error information to observe the input and disturbance of a system, so that the tracking and anti-interference problems can be simultaneously considered; however, the control parameters proposed by the method are fixed, and the unknown variable input and the unknown time-varying narrow-band disturbance cannot be effectively responded, so that the tracking precision is limited. In order to be able to cope with varying inputs and disturbances, a real-time, online adaptive error observer approach is required.
Disclosure of Invention
In order to improve the tracking capability of a photoelectric tracking system on an unknown change input signal and the suppression capability of the photoelectric tracking system on unknown time-varying narrow-band disturbance, the invention provides a photoelectric tracking system control method based on an adaptive error observer. In the position closed loop, firstly, an error observer structure is established, then, an input and disturbance sum observation signal is identified by using a fast Fourier transform method, main frequency components of the input and disturbance sum observation signal are obtained and observed in real time, then, according to an identification analysis result, a Q filter formed by a low-pass filter and a plurality of wave traps in series is subjected to parameter adjustment, and finally, the observation signal is filtered and fed into a control loop, so that the whole process of the self-adaptive disturbance observer is realized. While Q filter parameter adjustment is constrained by the stability of the small gain theorem. The invention can break through the limitation of the traditional method, and effectively improve the capability of the photoelectric tracking system for the change input and disturbance response, thereby leading the system to have higher tracking precision.
In order to achieve the purpose of the invention, the invention provides a photoelectric tracking system control method based on an adaptive error observer, which comprises the following steps:
step (1): the CCD is used as a position sensor of a photoelectric tracking system, and the relative angular position between the target visual axis and the center of the sensor is calculated, so that a position closed loop is formed;
step (2): in the position loop, the object characteristics of the position loop are obtained by using a frequency response tester and are expressed as an object model G p (s) wherein the input signal of the frequency response tester is the driving voltage input, and the output signal is the sampling output value of the CCD;
step (3): object model G according to position loop p (s) designing a position controller C(s) to complete closed-loop control;
step (4): after the position closed loop is completed, the object model G is established p (s) nominal inverse modelInputting error signal E(s) to nominal inverse model +.>For->Summing the output signal of (a) with the motor drive signal U(s) to obtain a sum estimate H(s) of the input signal R(s) and the disturbance signal D(s) in the position loop;
step (5): identifying and analyzing main frequency components in H(s) by using a fast Fourier transform method;
step (6): constructing a Q filter, designing the Q filter into a structure of a low-pass filter and a plurality of wave traps which are connected in series, wherein the filtering parameters are variable;
step (7): according to the frequency domain identification analysis result of the sum estimation quantity H(s), adjusting Q filter parameters to filter H(s), and filtering the filtered signalOutput U of feed-forward controller C(s) C (s)；
Step (8): repeating the steps (4) to (7), and circularly completing the whole process of the adaptive error observer until the system operation is finished.
Further, in the step (1), a CCD is used as a closed-loop sensor of the position loop to obtain the relative angular position of the target visual axis and the center of the sensor, so as to realize a position feedback closed loop.
Further, in the step (2), the object characteristic of the position loop is approximated to the second-order oscillation link, and the object model G p (s) is expressed as follows:
where a, b and K are model parameters.
Further, in the step (3), the position controller C(s) is designed by using a pole-zero cancellation method.
Further, in the step (4), in order to obtain and estimate the quantity H(s), an error observer is established, and an error signal E(s) is input into a nominal inverse modelAnd the sum estimate H(s) is made up of +.>Is summed with the motor drive signal U(s).
Further, in the step (5), a fast fourier transform method is adopted to obtain a power spectrum of H(s), so as to identify and analyze main frequency components in H(s).
Further, in the step (6), the Q filter is formed by connecting a low-pass filter and a plurality of traps in series, and the Q filter is formed by:
wherein beta is i ，ε i T is a filter parameter, f i For the main frequency of the ith trap, beta is required to meet the stability condition i ε i < 1, and beta i ＞1。
Further, in the step (7), the stability of the Q filter is constrained by the small gain theorem:
further, the step (8) includes the steps of: firstly, constructing an error observer structure to obtain a sum estimator H(s) of an input signal R(s) and a disturbance signal D(s) in a loop, then obtaining a main frequency component of the H(s) by a fast Fourier transform method, further adaptively adjusting a trap parameter of a Q filter, and finally filtering the filtered signalAnd the feed-forward is fed into a loop, so that the tracking capability of the photoelectric tracking system on unknown change input signals and the suppression capability of the system on unknown time-varying narrow-band disturbance are improved.
Compared with the prior art, the invention has the following advantages:
(1) Compared with the position closed-loop control, the invention adopts an observer structure, does not add an additional sensor, and can improve the tracking performance and disturbance suppression performance of the photoelectric tracking system by utilizing an algorithm.
(2) Compared with the traditional control method, the method solves the discrete tracking problem and the anti-interference problem simultaneously, and provides a new thought for the control strategy research of the photoelectric tracking system.
(3) Compared with the traditional error observer method, the method can adjust the control parameters in real time and on line, thereby improving the coping capability of the system to unknown change input and unknown time-varying disturbance.
(4) Compared with the traditional design method of the Q filter, the invention adopts a mode of connecting the low-pass filter and the plurality of wave traps in series, thereby ensuring stability and simultaneously having better filtering performance.
Drawings
Fig. 1 is a control block diagram of a control method of an optical tracking system based on an adaptive error observer according to the present invention.
Fig. 2 is a diagram of the simulation effect of the adaptive error observer method for an electro-optical tracking system.
Detailed Description
The following detailed description and the accompanying drawings illustrate specific embodiments of the invention.
FIG. 1 is a control block diagram of a control method of an optical tracking system based on an adaptive error observer, wherein the control block diagram comprises a CCD position closed loop, the error observer and a sampling, identifying and analyzing part of an estimated quantity. The method adopts an error observer method, a fast Fourier transform method, a novel Q filter design method and the like, can autonomously estimate the sum signal of input and disturbance in real time, and further adaptively adjusts Q filter parameters through sampling and frequency domain identification analysis of the sum estimation, and performs targeted feedforward on main frequency components, so that the tracking capacity of a system on unknown change input and the inhibition capacity of the system on unknown time-varying disturbance are improved. The method comprises the following specific implementation steps:
and (1) taking the CCD as a position sensor of the photoelectric tracking system, and calculating the relative angular position of the target visual axis and the center of the sensor, so as to form a position closed loop.
In the step (2), the object characteristic of the position loop is obtained by using a frequency response tester and is expressed as an object model G p (s) the input signal of the frequency response tester is the driving voltage input, and the output signal is the sampling output value of the CCD. The object characteristics of the position loop can be approximated as a second order oscillation link, and the model is expressed as follows:
where a, b and K are model parameters.
Step (3) according to the object model G of the position loop p (s) designing the position controller C(s) to complete the closed-loop control.
After the step (4) is completed, a position loop object model G is established p (s) nominal inverse modelInputting error signal E(s) to nominal inverse model +.>For->The sum of the output signal of (a) and the motor drive signal U(s) results in a sum estimate H(s) of the input signal R(s) and the disturbance signal D(s) in the position loop.
And (5) identifying and analyzing the main frequency components in the H(s) by using a fast Fourier transform method.
And (6) constructing a Q filter, designing the Q filter into a structure of connecting a low-pass filter and a plurality of wave traps in series, wherein the filtering parameters are variable. The Q filter is formed by connecting a low-pass filter and a plurality of wave traps in series, and the form is as follows:
wherein beta is i ，ε i T is a filter parameter, f i Is the dominant frequency of the ith trap. To meet stability conditions, beta is required i ε i < 1, and beta i ＞1。
Step (7) according to the frequency domain identification analysis result of the sum estimation amount H(s), adjusting Q filter parameters to filter H(s), and then filtering the filtered signalOutput U of feed-forward controller C(s) C (s) due to stability constraints, resulting in a filter parameterThe number is not arbitrarily changed. The stability of the Q filter is constrained by the small gain theorem:
and (8) repeating the steps (4) to (7) to finish the whole process of the adaptive error observer.
In a position loop formed by CCD, an error observer structure is constructed, the main frequency component of the analysis and estimation quantity H(s) is identified and analyzed on line by utilizing a fast Fourier transform method, then the main frequency of the notch of the Q filter is regulated in real time according to the analysis result, and finally the filtered signal is obtainedThe feed-forward is fed into a loop, so that the tracking capability of an optoelectronic tracking system on an unknown change input signal and the suppression capability of the system on unknown time-varying narrow-band disturbance are improved, and the tracking error is reduced.
The following describes the design process and effect of the present invention in detail using an actual photoelectric tracking system as an example:
(1) An adaptive error observer structure was constructed using the control block diagram shown in fig. 1, and the CCD was a position sensor.
(2) Mathematical model G for measuring system position loop controlled object by frequency response tester p (s)：
(3) According to object model G p (s) designing a position controller C(s) by adopting a pole-zero cancellation method, and realizing the tracking function:
(4) To ensure thatPhysically realizable, adding two inertial links +.>And->Post-addition +.>And->The values are almost the same within 50Hz, with no impact on the system:
(5) In the error observer structure, the sum signal of input and disturbance is estimated, and then the frequency domain identification analysis is carried out on the sum estimation by fast Fourier transformation, so as to obtain the main frequency component.
(6) According to the frequency domain identification analysis result, the notch parameters of the Q filter are adaptively adjusted, targeted filtering reduction is carried out on a plurality of main frequency components, and the main frequency components are fed forward to a position loop, so that the whole process of the adaptive error observer is realized. The Q filter structure is:
wherein f i The main frequency of the ith trap is given, and the other parameters are as follows:
α i ＝5,η i ＝0.01,T＝1/(2π·5)。
(7) Fig. 2 is a diagram showing the simulation operation effect of the present invention. The diagram shows a position error comparison diagram of the self-adaptive error observer method and the traditional method when the system input is an unknown change multi-frequency component signal and the disturbance is an unknown time-varying multi-frequency component signal. The dotted lines represent the inputs and disturbances and signals to show the true behavior of the inputs and disturbances handled by the system. The dashed line represents the error signal of the error observer method and the solid line represents the error signal of the adaptive error observer method. It can be seen that during the initial phase (15 s) the effect of both methods is the same. When the input and disturbance change (15 s), the tracking error of the system increases suddenly, and the tracking accuracy decreases. When the input and disturbance and the signal are kept unchanged for a period of time (after 15 s), the tracking error of the adaptive error observer method is gradually reduced after the signal identification and analysis and the Q filter parameter adjustment process are completed, and the tracking error of the traditional method is unchanged. Therefore, compared with the traditional error observer method, the method has stronger coping capability for the input and disturbance of the change and higher tracking precision.
Claims (9)
1. An adaptive error observer-based photoelectric tracking system control method is characterized by comprising the following steps:
step (1): the CCD is used as a position sensor of a photoelectric tracking system, and the relative angular position between the target visual axis and the center of the sensor is calculated, so that a position closed loop is formed;
step (2): in the position loop, the object characteristics of the position loop are obtained by using a frequency response tester and are expressed as an object model G p (s) wherein the input signal of the frequency response tester is the driving voltage input, and the output signal is the sampling output value of the CCD;
step (3): object model G according to position loop p (s) designing a position controller C(s) to complete closed-loop control;
step (4): after the position closed loop is completed, the object model G is established p (s) nominal inverse modelInputting error signal E(s) to nominal inverse model +.>For->Summing the output signal of (a) with the motor drive signal U(s) to obtain a sum estimate H(s) of the input signal R(s) and the disturbance signal D(s) in the position loop;
step (5): identifying and analyzing main frequency components in H(s) by using a fast Fourier transform method;
step (6): constructing a Q filter, designing the Q filter into a structure of a low-pass filter and a plurality of wave traps which are connected in series, wherein the filtering parameters are variable;
step (7): according to the frequency domain identification analysis result of the sum estimation quantity H(s), adjusting Q filter parameters to filter H(s), and filtering the filtered signalOutput U of feed-forward controller C(s) C (s)；
Step (8): repeating the steps (4) to (7), and circularly completing the whole process of the adaptive error observer until the system operation is finished.
2. The method for controlling an optical tracking system based on an adaptive error observer according to claim 1, wherein: in the step (1), a CCD is used as a closed-loop sensor of a position loop to acquire the relative angular position of the target visual axis and the center of the sensor, so that a position feedback closed loop is realized.
3. The method for controlling an optical tracking system based on an adaptive error observer according to claim 1, wherein: in the step (2), the object characteristic of the position loop is approximated to a second-order oscillation link, and then the object model G p (s) is expressed as follows:
where a, b and K are model parameters.
4. The method for controlling an optical tracking system based on an adaptive error observer according to claim 1, wherein: in the step (3), the position controller C(s) is designed by using a pole-zero cancellation method.
5. The method for controlling an optical tracking system based on an adaptive error observer according to claim 1, wherein: in the step (4), in order to obtain and estimate the quantity H(s), an error observer is established, and an error signal E(s) is input into a nominal inverse modelAnd the sum estimate H(s) is made up of +.>Is summed with the motor drive signal U(s).
6. The method for controlling an optical tracking system based on an adaptive error observer according to claim 1, wherein: in the step (5), a fast fourier transform method is adopted to obtain the power spectrum of the H(s), so as to identify and analyze the main frequency components in the H(s).
7. The method for controlling an optical tracking system based on an adaptive error observer according to claim 1, wherein: in the step (6), the Q filter is formed by connecting a low-pass filter and a plurality of traps in series, and the form is as follows:
wherein beta is i ，ε i T is a filter parameter, f i Is the main frequency of the ith trapTo meet stability conditions, beta is required i ε i < 1, and beta i ＞1。
8. The method for controlling an optical tracking system based on an adaptive error observer according to claim 1, wherein: in the step (7), the stability of the Q filter is constrained by the small gain theorem:
9. the method for controlling an optical tracking system based on an adaptive error observer according to claim 1, wherein: the step (8) comprises the following steps: firstly, constructing an error observer structure to obtain a sum estimator H(s) of an input signal R(s) and a disturbance signal D(s) in a loop, then obtaining a main frequency component of the H(s) by a fast Fourier transform method, further adaptively adjusting a trap parameter of a Q filter, and finally filtering the filtered signalAnd the feed-forward is fed into a loop, so that the tracking capability of the photoelectric tracking system on unknown change input signals and the suppression capability of the system on unknown time-varying narrow-band disturbance are improved.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310815933.5A CN116774587A (en) | 2023-07-05 | 2023-07-05 | Photoelectric tracking system control method based on self-adaptive error observer |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310815933.5A CN116774587A (en) | 2023-07-05 | 2023-07-05 | Photoelectric tracking system control method based on self-adaptive error observer |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN116774587A true CN116774587A (en) | 2023-09-19 |
Family
ID=87992869
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202310815933.5A Pending CN116774587A (en) | 2023-07-05 | 2023-07-05 | Photoelectric tracking system control method based on self-adaptive error observer |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN116774587A (en) |
-
2023
- 2023-07-05 CN CN202310815933.5A patent/CN116774587A/en active Pending
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN108762083B (en) | Automatic control system based on acceleration observer | |
| Borisagar et al. | Simulation and comparative analysis of LMS and RLS algorithms using real time speech input signal | |
| CN108777556B (en) | Model-free adaptive robust decoupling control method for two-motor speed regulation system | |
| CN111510026B (en) | Output torque estimation method and system for permanent magnet synchronous motor | |
| CN111474922B (en) | Method for constructing controller of continuous nonlinear system | |
| CN111258220B (en) | Flexible mechanical arm cascade control method and system based on disturbance observer | |
| Popovici et al. | Dual extended kalman filter for the identification of time-varying human manual control behavior | |
| CN113467236B (en) | Method for time lag compensation of error signal | |
| CN114710081B (en) | Online resonance suppression method based on extended state observer and improved wave trap | |
| CN110712201B (en) | Robot multi-joint self-adaptive compensation method based on perceptron model and stabilizer | |
| CN116774587A (en) | Photoelectric tracking system control method based on self-adaptive error observer | |
| Lee et al. | Speed estimation and control of induction motor drive using hybrid intelligent control | |
| Tang et al. | Robust fuzzy control of mechanical systems | |
| Tzes et al. | Adaptive precompensators for flexible-link manipulator control | |
| CN108646568B (en) | Tilting mirror vibration suppression method based on improved disturbance observer | |
| CN115685757A (en) | Active disturbance rejection pre-estimation control method based on filtering in pure time lag system | |
| CN113867155B (en) | Disturbance identification and self-adaptive compensation method suitable for photoelectric tracking system | |
| Dróżdż et al. | Filtered integral sliding mode control in a two-mass drive system | |
| Hu et al. | AUDE-based model reference adaptive dynamic sliding mode control for overhead cranes | |
| Hazaz et al. | Disturbance observer for DC motor based on savitzky-golay filters and application to bilateral control | |
| CN112859587B (en) | PID target tracking control method based on additional integrated module | |
| CN112910348A (en) | Parallel structure frequency spectrum optimization method and system based on model predictive control | |
| Wang et al. | Spectral distribution and implications of feedback regulation beyond nyquist frequency | |
| Gupta et al. | Adaptive filters algorithms: a performance comparison | |
| Maniarski et al. | Application of iterative learning methods to control of a LEGO wheeled mobile robot |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |