Tikhonov regularization based control allocation for underactuated input-affine systems
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Universidade Federal de Minas Gerais
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This paper proposes a novel control allocation method for underactuated input-affine nonlinear mechanical systems, based on the Tikhonov regularization. A hardware-in-the-loop experiment is conducted using an unmanned aerial manipulator to corroborate the effectiveness of the proposed method. The results demonstrate that, in comparison with the classic Moore-Penrose pseudo-inverse control allocation method, the proposed Tikhonov regularization-based control allocation is computationally faster and attenuates additive noise terms within the generalized input vector. Besides, it reduces the residual error between the desired and applied generalized input when the input coupling matrix is ill-posed.
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Couplings , Additive noise , Conferences , Education , Manipulators , Control systems , Resource management, Control allocation , Underactuated systems , Non-linear systems, Weight Decay , Control Allocation , Underactuated Systems , Classical Methods , Nonlinear Systems , Systematic Method , Mechanical Systems , Additional Term , Input Vector , Residual Error , Moore Penrose Inverse , Degrees Of Freedom , Optimization Problem , Actuator , Optimal Control , Diagonal Matrix , Weight Matrix , Effect Of Noise , Beginning Of The Experiment , Control Input , Unmanned Aerial Vehicles , Class Of Systems , Control Input Vector , Singular Value Decomposition , Nonlinear Control , Lagrange Equations , Italic Letters , Redundant System , Pseudo-inverse Matrix , Off-diagonal
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https://ieeexplore.ieee.org/document/10332966