MRAC-Based Nonlinear Disturbance Observer And Its Applications To UAV Control
Li, Shuai; Pitkänen, Ville; Tikanmäki, Antti; Alahuhta, Petteri; Röning, Juha (2023-11-20)
IEEE
20.11.2023
S. Li, V. Pitkänen, A. Tikanmäki, P. Alahuhta and J. Röning, "MRAC-Based Nonlinear Disturbance Observer And Its Applications To UAV Control," 2023 IEEE International Conference on Networking, Sensing and Control (ICNSC), Marseille, France, 2023, pp. 1-7, doi: 10.1109/ICNSC58704.2023.10318844
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© 2023 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists,or reuse of any copyrighted component of this work in other works.
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Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:oulu-202405284020
https://urn.fi/URN:NBN:fi:oulu-202405284020
Tiivistelmä
Abstract
Unknown disturbances are one of the most critical factors impacting control performances, and the design of globally convergent disturbance observers for estimation of disturbances in real-time plays an important role in improving the performance of control systems. This work presents the design of a novel disturbance observer based on model reference adaptive control to relax the restrictive gain conditions in conventional nonlinear disturbance observer design. The proposed Model Reference Adaptive Control-based Nonlinear Disturbance Observer (MRAC-NDO) features a simple structure with theoretically guaranteed global convergence for estimating unknown disturbances appearing in affine systems. The proposed strategy is applied to unmanned aerial vehicles (UAVs) based on cascaded control incorporated by MRAC-NDO disturbance compensation. Numerical results validate the effectiveness of the proposed solution.
Unknown disturbances are one of the most critical factors impacting control performances, and the design of globally convergent disturbance observers for estimation of disturbances in real-time plays an important role in improving the performance of control systems. This work presents the design of a novel disturbance observer based on model reference adaptive control to relax the restrictive gain conditions in conventional nonlinear disturbance observer design. The proposed Model Reference Adaptive Control-based Nonlinear Disturbance Observer (MRAC-NDO) features a simple structure with theoretically guaranteed global convergence for estimating unknown disturbances appearing in affine systems. The proposed strategy is applied to unmanned aerial vehicles (UAVs) based on cascaded control incorporated by MRAC-NDO disturbance compensation. Numerical results validate the effectiveness of the proposed solution.
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