High-Linear Frequency-Swept Lasers with Data-Driven Control
The frequency-swept laser (FSL) is applied widely in various sensing systems in the scientific and industrial fields, especially in the light detection and ranging (Lidar) area. However, the inherent nonlinearity limits its performance in application systems, especially in the broadband frequency-sw...
| Main Authors: | , , , , , |
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| Format: | Article |
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MDPI AG
2023-09-01
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| Series: | Photonics |
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| Online Access: | https://www.mdpi.com/2304-6732/10/9/1056 |
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| author | Haohao Zhao Dachao Xu Zihan Wu Liang Sun Guohui Yuan Zhuoran Wang |
| author_facet | Haohao Zhao Dachao Xu Zihan Wu Liang Sun Guohui Yuan Zhuoran Wang |
| author_sort | Haohao Zhao |
| collection | DOAJ |
| description | The frequency-swept laser (FSL) is applied widely in various sensing systems in the scientific and industrial fields, especially in the light detection and ranging (Lidar) area. However, the inherent nonlinearity limits its performance in application systems, especially in the broadband frequency-swept condition. In this work, from the perspective of data-driven control, we adopt the reinforcement learning-based broadband frequency-swept linearization method (RL-FSL) to optimize the control policy and generate the modulation signals. The nonlinearity measurement system and the system simulator are established. Since the powerful learning ability of the reinforcement learning algorithm, the linearization policy is optimized off-line and the generated modulation signals reduce the nonlinearity almost 20 times, compared to the case without control. In the long-term operation, the regular updated modulation signals perform better than the traditional iteration results, demonstrating the efficiency of the proposed data-driven control method in application systems. Therefore, the RL-FSL method has the potential to be the candidate of optical system control. |
| first_indexed | 2024-03-10T22:14:00Z |
| format | Article |
| id | doaj.art-1b6b183245bc4ebfb12f00979f9691b9 |
| institution | Directory Open Access Journal |
| issn | 2304-6732 |
| language | English |
| last_indexed | 2024-03-10T22:14:00Z |
| publishDate | 2023-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Photonics |
| spelling | doaj.art-1b6b183245bc4ebfb12f00979f9691b92023-11-19T12:30:27ZengMDPI AGPhotonics2304-67322023-09-01109105610.3390/photonics10091056High-Linear Frequency-Swept Lasers with Data-Driven ControlHaohao Zhao0Dachao Xu1Zihan Wu2Liang Sun3Guohui Yuan4Zhuoran Wang5School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu 611731, ChinaSchool of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu 611731, ChinaSchool of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu 611731, ChinaSchool of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu 611731, ChinaYangtze Delta Region Institute (Quzhou), University of Electronic Science and Technology of China, Quzhou 324000, ChinaYangtze Delta Region Institute (Quzhou), University of Electronic Science and Technology of China, Quzhou 324000, ChinaThe frequency-swept laser (FSL) is applied widely in various sensing systems in the scientific and industrial fields, especially in the light detection and ranging (Lidar) area. However, the inherent nonlinearity limits its performance in application systems, especially in the broadband frequency-swept condition. In this work, from the perspective of data-driven control, we adopt the reinforcement learning-based broadband frequency-swept linearization method (RL-FSL) to optimize the control policy and generate the modulation signals. The nonlinearity measurement system and the system simulator are established. Since the powerful learning ability of the reinforcement learning algorithm, the linearization policy is optimized off-line and the generated modulation signals reduce the nonlinearity almost 20 times, compared to the case without control. In the long-term operation, the regular updated modulation signals perform better than the traditional iteration results, demonstrating the efficiency of the proposed data-driven control method in application systems. Therefore, the RL-FSL method has the potential to be the candidate of optical system control.https://www.mdpi.com/2304-6732/10/9/1056frequency-swept lasersreinforcement learningnonlinearitydata-driven control |
| spellingShingle | Haohao Zhao Dachao Xu Zihan Wu Liang Sun Guohui Yuan Zhuoran Wang High-Linear Frequency-Swept Lasers with Data-Driven Control Photonics frequency-swept lasers reinforcement learning nonlinearity data-driven control |
| title | High-Linear Frequency-Swept Lasers with Data-Driven Control |
| title_full | High-Linear Frequency-Swept Lasers with Data-Driven Control |
| title_fullStr | High-Linear Frequency-Swept Lasers with Data-Driven Control |
| title_full_unstemmed | High-Linear Frequency-Swept Lasers with Data-Driven Control |
| title_short | High-Linear Frequency-Swept Lasers with Data-Driven Control |
| title_sort | high linear frequency swept lasers with data driven control |
| topic | frequency-swept lasers reinforcement learning nonlinearity data-driven control |
| url | https://www.mdpi.com/2304-6732/10/9/1056 |
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