G
Guilherme V. Raffo
Researcher at Universidade Federal de Minas Gerais
Publications - 99
Citations - 2087
Guilherme V. Raffo is an academic researcher from Universidade Federal de Minas Gerais. The author has contributed to research in topics: Control theory & Model predictive control. The author has an hindex of 17, co-authored 87 publications receiving 1682 citations. Previous affiliations of Guilherme V. Raffo include National Institute of Standards and Technology & Universidade Federal de Santa Catarina.
Papers
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Journal ArticleDOI
An integral predictive/nonlinear H∞ control structure for a quadrotor helicopter
TL;DR: An integral predictive and nonlinear robust control strategy to solve the path following problem for a quadrotor helicopter with parametric and structural uncertainties presented to corroborate the effectiveness and the robustness of the proposed strategy.
Journal ArticleDOI
A Predictive Controller for Autonomous Vehicle Path Tracking
TL;DR: Practical experiments obtained using an autonomous ldquoMini-Bajardquo vehicle equipped with an embedded computing system confirm that the proposed MPC structure is the solution that better matches the target criteria.
Proceedings ArticleDOI
Backstepping/nonlinear H ∞ control for path tracking of a quadrotor unmanned aerial vehicle
TL;DR: A nonlinear robust control strategy to solve the path tracking problem for a quadrotor unmanned aerial vehicle and a control law based on backstepping approach to track the reference trajectory is presented.
Journal ArticleDOI
Path Tracking of a UAV via an Underactuated Control Strategy
TL;DR: A nonlinear robust control strategy designed for underactuated mechanical systems is proposed in order to solve the path tracking problem for a quadrotor unmanned aerial vehicle.
Journal ArticleDOI
Nonlinear H∞ Controller for the Quad-Rotor Helicopter with Input Coupling
TL;DR: In this article, a nonlinear H∞ control law for underactuated mechanical systems with input coupling is presented, which considers the dynamics of the remaining degrees of freedom in the cost variable, which allows to stabilize them.