{"title":"Design of Controllers to Track Trajectories for Multi-rotor Unmanned Aerial Vehicles","authors":"Robinson S. Alvarez-Valle, P. Rivadeneira","doi":"10.1109/CCAC.2019.8921246","DOIUrl":null,"url":null,"abstract":"This paper presents the synthesis of controllers for a multi-rotor unmanned aerial vehicle with the goal to track trajectories, transforming its MIMO system representation into simpler structures based on SISO systems. Three control structures are provided to control the four outputs: x, y, z positions and the yaw angle. All the structures are based on decoupled control loops for each output described above. The first structure consists of classical controls, where the first two loops (x and y positions) use a third order transfer function control while the last two (z position and yaw angle) a PID/PD control. The second one uses for the first two loops a cascade control strategy based on a PD controllers. The third structure uses cascade control strategies with a PID-PID-PD-P control combination for the first two loops, while a PD-P combination for the last two. The control performance of each structure is assessed through simulation following changes of set points and a square trajectory. For a 1 [m] step change in x or y position, the system response has a setting time of around 5.7 [s, 4. 7[s], and 1.9 [s], with an overshoot of approximately 75.3%, 40.3% and 0.3% for each structure, respectively. For a 1 [m] change in z position, the setting time is 6.4 [s] and the overshoot is 24.9% for the first two structures. While for the last one, the setting time is 2.7 [s] without overshoot. Similar results are achieved for changes in the yaw angle. Finally, disturbances are included to test the robustness of the control strategies. Based on these results, the conclusion is that the third structure has the best performance.","PeriodicalId":184764,"journal":{"name":"2019 IEEE 4th Colombian Conference on Automatic Control (CCAC)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE 4th Colombian Conference on Automatic Control (CCAC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CCAC.2019.8921246","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
This paper presents the synthesis of controllers for a multi-rotor unmanned aerial vehicle with the goal to track trajectories, transforming its MIMO system representation into simpler structures based on SISO systems. Three control structures are provided to control the four outputs: x, y, z positions and the yaw angle. All the structures are based on decoupled control loops for each output described above. The first structure consists of classical controls, where the first two loops (x and y positions) use a third order transfer function control while the last two (z position and yaw angle) a PID/PD control. The second one uses for the first two loops a cascade control strategy based on a PD controllers. The third structure uses cascade control strategies with a PID-PID-PD-P control combination for the first two loops, while a PD-P combination for the last two. The control performance of each structure is assessed through simulation following changes of set points and a square trajectory. For a 1 [m] step change in x or y position, the system response has a setting time of around 5.7 [s, 4. 7[s], and 1.9 [s], with an overshoot of approximately 75.3%, 40.3% and 0.3% for each structure, respectively. For a 1 [m] change in z position, the setting time is 6.4 [s] and the overshoot is 24.9% for the first two structures. While for the last one, the setting time is 2.7 [s] without overshoot. Similar results are achieved for changes in the yaw angle. Finally, disturbances are included to test the robustness of the control strategies. Based on these results, the conclusion is that the third structure has the best performance.