A SAKF-Based Composed Control Method for Improving Low-Speed Performance and Stability Accuracy of Opto-Electric Servomechanism
Source abstract
Abstract
The opto-electric servomechanism (OES) plays an important role in obtaining clear and stable images from airborne infrared detectors. However, the inherent torque disturbance and the noisy speed signal cause a significant decline in the inertial stability accuracy and low-speed performances of OESs. Traditional linear control schemes cannot deal with the nonlinear torque disturbance well, and the speed obtained by the finite difference (FD) method cannot effectively balance the tradeoff between the noise filtering and phase delay. Therefore, this paper proposes a strap-down stability control scheme, in the combination of a proportional-integral(PI) controller and a state-augmented Kalman filter (SAKF), where the PI is used to regulate the linear part of the servomechanism, and with the SAKF performing torque disturbance observation and speed estimation simultaneously. The principle and the implementation of the controller are introduced, and the tuning guidelines for the controller parameters are presented as well. Finally, the experimental verifications based on OESs with three transmission types (i.e., the direct-driving, the harmonic-driving, and the rotate vector-driving(RV-driving) OESs) are carried out respectively. The experimental results show that the proposed control scheme can perform better speed observation and torque disturbance compensation for various types of OESs, thus effectively improving the low-speed performance and stability accuracy of the mechanism.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Adaptive Control of Nonlinear Systems · Gaze Tracking and Assistive Technology · Extremum Seeking Control Systems
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
College of Intelligence Science and Technology, National University of Defense Technology, Changsha 410073, China
Funding
National Basic Research Program of China (973 Program)
References (17)
Show source-provided references
1. LuGre model-based friction compensation and positioning control for a pneumatic actuator using multi-objective output-feedback control via LMI optimization10.1016/j.mechatronics.2008.12.006 ↗
2. Adaptive robust control of linear motors with dynamic friction compensation using modified LuGre model10.1016/j.automatica.2009.09.007 ↗
3. Two-state GMS-based friction model for precise control applications10.1007/s12541-016-0068-y ↗
4. Disturbance observer based control for nonlinear systems10.1109/TMECH.2004.839034 ↗
5. Zhou, Z., Zhang, B., and Mao, D. (2018). Robust Sliding Mode Control of PMSM Based on a Rapid Nonlinear Tracking Differentiator and Disturbance Observer. Sensors, 18.10.3390/s18041031 ↗
6. A new digital speed transducer10.1109/TIECI.1978.351543 ↗
7. Discrete-time adaptive windowing for velocity estimation10.1109/87.880606 ↗
8. Shademan, A., and Janabi-Sharifi, F. (2003, January 20–24). Adaptive velocity estimation for disk drive head positioning. Proceedings of the 2003 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM 2003), Kobe, Japan.
9. Real-Time Quadratic Sliding Mode Filter for Removing Noise10.1163/156855312X633011 ↗
10. Improving velocity feedback for position control by using a discrete-time sliding mode filtering with adaptive windowing10.1080/01691864.2014.899161 ↗
11. Jin, S., Jin, Y., Wang, X., and Xiong, X. (2016). Discrete-Time Sliding Mode Filter with Adaptive Gain. Appl. Sci., 6.10.3390/app6120400 ↗
12. Enhanced Discrete-Time Sliding Mode Filter for Removing Noise
13. Aung, M.T.S., Shi, Z., and Kikuuwe, R. (2014, January 8–10). A new noise-reduction filter with sliding mode and low-pass filtering. Proceedings of the 2014 IEEE Conference on Control Applications (CCA), Antibes, France.10.1109/CCA.2014.6981470 ↗
14. Paing, S.L., Aung, M.T.S., and Kikuuwe, R. (2017). Adaptive gain parabolic sliding mode filter augmented with vibration observer. Control Technol. Appl., 602–607.10.1109/CCTA.2017.8062528 ↗
15. A New Parabolic Sliding Mode Filter Augmented by a Linear Low-Pass Filter and Its Application to Position Control
16. Liao, H. (2016). Research on Performance Analysis and Control for Weapon Station Servo Device. [Ph.D. Thesis, National University of Defence Technology].
17. (2019, October 11). DS1104 R&D Controller Board: Cost-effective System for Controller Development. Available online: https://www.dspace.com/shared/data/pdf/2019/dSPACE_DS1104_Catalog2019.pdf.