TY - GEN
T1 - Robust Trajectory Tracking by a Multicopter Platform
T2 - AIAA Science and Technology Forum and Exposition, AIAA SciTech Forum 2022
AU - Jha, Bhargav
AU - Gupta, Ujjwal
AU - Turetsky, Vladimir
AU - Shima, Tal
N1 - Publisher Copyright: © 2022, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.
PY - 2022
Y1 - 2022
N2 - In this paper, the problem of robust trajectory tracking by a multicopter platform is formulated as a linear-quadratic differential game against unknown external disturbances (nature). The desired trajectory is composed of position and yaw constraint, which is known to be a differentially flat output for multicopter state dynamics. Using this property, a linearized error dynamics is obtained in the vicinity of the nominal states and the nominal control inputs. To avoid singularities, the linearized error dynamics is derived using quaternion representation. Based on it, an optimal saddle point strategy for trajectory tracking is presented, where controller gains are calculated apriori by numerically solving a differential Ricatti equation. A salient feature of this control design is that both the position and the attitude control loops are integrated, and there are only two tuning parameters — one corresponding to the tradeoff between control effort and tracking accuracy and the other corresponding to robustness. Simulations as well as experimental validations are presented to demonstrate the performance and applicability of the controller.
AB - In this paper, the problem of robust trajectory tracking by a multicopter platform is formulated as a linear-quadratic differential game against unknown external disturbances (nature). The desired trajectory is composed of position and yaw constraint, which is known to be a differentially flat output for multicopter state dynamics. Using this property, a linearized error dynamics is obtained in the vicinity of the nominal states and the nominal control inputs. To avoid singularities, the linearized error dynamics is derived using quaternion representation. Based on it, an optimal saddle point strategy for trajectory tracking is presented, where controller gains are calculated apriori by numerically solving a differential Ricatti equation. A salient feature of this control design is that both the position and the attitude control loops are integrated, and there are only two tuning parameters — one corresponding to the tradeoff between control effort and tracking accuracy and the other corresponding to robustness. Simulations as well as experimental validations are presented to demonstrate the performance and applicability of the controller.
UR - http://www.scopus.com/inward/record.url?scp=85123577749&partnerID=8YFLogxK
U2 - https://doi.org/10.2514/6.2022-1396
DO - https://doi.org/10.2514/6.2022-1396
M3 - منشور من مؤتمر
SN - 9781624106316
T3 - AIAA Science and Technology Forum and Exposition, AIAA SciTech Forum 2022
BT - AIAA SciTech Forum 2022
Y2 - 3 January 2022 through 7 January 2022
ER -