Scheduling PID Attitude and Position Control Frequencies for Time-Optimal Quadrotor Waypoint Tracking under Unknown External Disturbances
Recently, the use of quadrotors has increased in numerous applications, such as agriculture, rescue, transportation, inspection, and localization. Time-optimal quadrotor waypoint tracking is defined as controlling quadrotors to follow the given waypoints as quickly as possible. Although PID control...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2021-12-01
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| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/22/1/150 |
| _version_ | 1797497666342486016 |
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| author | Cheongwoong Kang Bumjin Park Jaesik Choi |
| author_facet | Cheongwoong Kang Bumjin Park Jaesik Choi |
| author_sort | Cheongwoong Kang |
| collection | DOAJ |
| description | Recently, the use of quadrotors has increased in numerous applications, such as agriculture, rescue, transportation, inspection, and localization. Time-optimal quadrotor waypoint tracking is defined as controlling quadrotors to follow the given waypoints as quickly as possible. Although PID control is widely used for quadrotor control, it is not adaptable to environmental changes, such as various trajectories and dynamic external disturbances. In this work, we discover that adjusting PID control frequencies is necessary for adapting to environmental changes by showing that the optimal control frequencies can be different for different environments. Therefore, we suggest a method to schedule the PID position and attitude control frequencies for time-optimal quadrotor waypoint tracking. The method includes (1) a Control Frequency Agent (CFA) that finds the best control frequencies in various environments, (2) a Quadrotor Future Predictor (QFP) that predicts the next state of a quadrotor, and (3) combining the CFA and QFP for time-optimal quadrotor waypoint tracking under unknown external disturbances. The experimental results prove the effectiveness of the proposed method by showing that it reduces the travel time of a quadrotor for waypoint tracking. |
| first_indexed | 2024-03-10T03:22:29Z |
| format | Article |
| id | doaj.art-cf01dcbcbae14d079e7477231d743771 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-10T03:22:29Z |
| publishDate | 2021-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-cf01dcbcbae14d079e7477231d7437712023-11-23T12:17:40ZengMDPI AGSensors1424-82202021-12-0122115010.3390/s22010150Scheduling PID Attitude and Position Control Frequencies for Time-Optimal Quadrotor Waypoint Tracking under Unknown External DisturbancesCheongwoong Kang0Bumjin Park1Jaesik Choi2Kim Jaechul Graduate School of AI, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, KoreaKim Jaechul Graduate School of AI, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, KoreaKim Jaechul Graduate School of AI, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, KoreaRecently, the use of quadrotors has increased in numerous applications, such as agriculture, rescue, transportation, inspection, and localization. Time-optimal quadrotor waypoint tracking is defined as controlling quadrotors to follow the given waypoints as quickly as possible. Although PID control is widely used for quadrotor control, it is not adaptable to environmental changes, such as various trajectories and dynamic external disturbances. In this work, we discover that adjusting PID control frequencies is necessary for adapting to environmental changes by showing that the optimal control frequencies can be different for different environments. Therefore, we suggest a method to schedule the PID position and attitude control frequencies for time-optimal quadrotor waypoint tracking. The method includes (1) a Control Frequency Agent (CFA) that finds the best control frequencies in various environments, (2) a Quadrotor Future Predictor (QFP) that predicts the next state of a quadrotor, and (3) combining the CFA and QFP for time-optimal quadrotor waypoint tracking under unknown external disturbances. The experimental results prove the effectiveness of the proposed method by showing that it reduces the travel time of a quadrotor for waypoint tracking.https://www.mdpi.com/1424-8220/22/1/150waypoint trackingexternal disturbance estimationquadrotor controlreinforcement learningdeep learningartificial intelligence |
| spellingShingle | Cheongwoong Kang Bumjin Park Jaesik Choi Scheduling PID Attitude and Position Control Frequencies for Time-Optimal Quadrotor Waypoint Tracking under Unknown External Disturbances Sensors waypoint tracking external disturbance estimation quadrotor control reinforcement learning deep learning artificial intelligence |
| title | Scheduling PID Attitude and Position Control Frequencies for Time-Optimal Quadrotor Waypoint Tracking under Unknown External Disturbances |
| title_full | Scheduling PID Attitude and Position Control Frequencies for Time-Optimal Quadrotor Waypoint Tracking under Unknown External Disturbances |
| title_fullStr | Scheduling PID Attitude and Position Control Frequencies for Time-Optimal Quadrotor Waypoint Tracking under Unknown External Disturbances |
| title_full_unstemmed | Scheduling PID Attitude and Position Control Frequencies for Time-Optimal Quadrotor Waypoint Tracking under Unknown External Disturbances |
| title_short | Scheduling PID Attitude and Position Control Frequencies for Time-Optimal Quadrotor Waypoint Tracking under Unknown External Disturbances |
| title_sort | scheduling pid attitude and position control frequencies for time optimal quadrotor waypoint tracking under unknown external disturbances |
| topic | waypoint tracking external disturbance estimation quadrotor control reinforcement learning deep learning artificial intelligence |
| url | https://www.mdpi.com/1424-8220/22/1/150 |
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