Model Predictive Control of Tandem Rotor Vehicles

Due to advances in on-board computing, model predictive control (MPC) has become viable for real-time control of unmanned aerial vehicles (UAVs). MPC is of particular interest due to its ability to explicitly enforce constraints on the control input and states. This work focuses on designing an MPC controller for a tandem rotor vehicle. The states of the system are defined using a matrix Lie group. A matrix Lie group error, which is commonly used in estimation problems for navigation, is leveraged during the linearization process to design the MPC algorithm. The resulting MPC algorithm realizes trajectory tracking while enforcing constraints on the applied thrust and torque, as well as the attitude of the tandem rotor vehicle. This talk will present the problem formulation, an overview of the proposed control structure, and simulation results.

James Richard Forbes received the BASc degree in Mechanical Engineering (Honours, Co-op) from the University of Waterloo, Waterloo, ON, Canada, and the MASc and PhD degrees in Aerospace Science and Engineering from the University of Toronto Institute for Aerospace Studies (UTIAS), Toronto, ON, Canada, in 2008 and 2011, respectively. James is currently Associate Professor of Mechanical Engineering at McGill University, Montreal, QC, Canada. In recognition of his research contributions James was awarded a William Dawson Scholar award in 2018. James is a Full Member of the Centre for Intelligent Machines (CIM) and a Member of the Group for Research in Decision Analysis (GERAD). James was awarded the McGill Associate for Mechanical Engineering (MAME) Professor of the Year Award in 2016, the Engineering Class of 1944 Outstanding Teaching Award in 2018, and the Carrie M. Derick Award for Graduate Supervision and Teaching in 2020. The focus of James' research is navigation and control of robotic and aerospace systems. James' research group, the Dynamics, Estimation, and Control of Aerospace and Robotic (DECAR) Systems Group (https://www.decar.ca/), conducts fundamental and applied research in collaboration with various industrial companies in Quebec, Canada, and internationally.