Adaptive Incremental Nonlinear Dynamic Inversion Control for Aerial Manipulators

This paper proposes an adaptive incremental nonlinear dynamic inversion (INDI) controller for unmanned aerial manipulators (UAMs). A novel adaptive law is employed to enable aerial manipulators to manage the inertia parameter changes that occur when the manipulator moves or picks up unknown objects during any phase of the UAM’s flight maneuver. The adaptive law utilizes a Kalman filter to estimate a set of weighting factors employed to adjust the control gain matrix of a previously developed INDI control law formulated for the corresponding UAV (no manipulator included). The proposed adaptive control scheme uses acceleration and actuator input measurements of the UAV without necessitating any knowledge about the manipulator, its movements, or the objects being grasped, thus enabling the use of previously developed INDI UAV controllers for UAMs. The algorithm is validated through simulations demonstrating that the adaptive control gain matrix used in the UAV’s INDI controller is promptly updated based on the UAM maneuvers, resulting in effective UAV and robot arm control.

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Publication Details

Journal
Aerospace
Published
2024-08-15
DOI
https://doi.org/10.3390/aerospace11080671
Citations
10
Primary Topic
UAV Applications and Optimization
Type
article
Field-Weighted Citation Impact
12.99
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article

Adaptive Incremental Nonlinear Dynamic Inversion Control for Aerial Manipulators

Alejandro Ramirez‐Serrano, Chanhong Park, Mahdis Bisheban
10 citations
Aerospace
UAV Applications and Optimization
12.99
article

Adaptive Incremental Nonlinear Dynamic Inversion Control for Aerial Manipulators

Alejandro Ramirez‐Serrano, Chanhong Park, Mahdis Bisheban
article en
10 citations

Abstract

This paper proposes an adaptive incremental nonlinear dynamic inversion (INDI) controller for unmanned aerial manipulators (UAMs). A novel adaptive law is employed to enable aerial manipulators to manage the inertia parameter changes that occur when the manipulator moves or picks up unknown objects during any phase of the UAM’s flight maneuver. The adaptive law utilizes a Kalman filter to estimate a set of weighting factors employed to adjust the control gain matrix of a previously developed INDI control law formulated for the corresponding UAV (no manipulator included). The proposed adaptive control scheme uses acceleration and actuator input measurements of the UAV without necessitating any knowledge about the manipulator, its movements, or the objects being grasped, thus enabling the use of previously developed INDI UAV controllers for UAMs. The algorithm is validated through simulations demonstrating that the adaptive control gain matrix used in the UAV’s INDI controller is promptly updated based on the UAM maneuvers, resulting in effective UAV and robot arm control.

AerospaceVol. 11(8)
University of Calgary (CA)
Peace, Justice and strong institutions
Openalex Percentile: Top 2%
UAV Applications and Optimization
12.99
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