Nullspace-Based Control Allocation of Overactuated UAV Platforms
Yao Su, Pengkang Yu, Matthew J. Gerber, Lecheng Ruan, Tsu‐Chin Tsao
Abstract
Multirotor copters with full six Degree of Freedom (DoF) maneuvering are often overactuated. The control allocation of overactuated UAV platforms can have an infinite number of solutions due to their redundancy. The most common allocation framework is based on Force Decomposition (FD), which provides a robust least-square solution and is easy to implement, but it does not account for input constraints. A control allocation framework based on Quadratic Programming (QP) can take input constraints; however, it will introduce linear approximation error and it has not been formulated and implemented on physical systems. In this letter, we propose a nullspace-based allocation framework for overactuated UAV platforms that combines the advantages of the FD-based framework and QP-based framework. Our proposed nullspace-based framework can take input constraints while eliminating the linear approximation error in the control allocation. It is also robust against controller sampling frequency and measurement noise. These three allocation frameworks are implemented and compared on our novel overactuated UAV platform in simulation to evaluate the robustness of the proposed method and in experiment for a vertical rotation trajectory to demonstrate its performance.