On March 28, we organized a scientific seminar on “Constraint removal in model predictive control for quadcopters“. Nora Lindner, a PhD student at Ruhr University Bochum, Germany, led the seminar, which was organized in the framework of the FrontSeat project as part of the seminar series on “Research Seminar on Smart Cybernetics.”
Abstract:
Model Predictive Control (MPC) is a powerful optimization-based control strategy, but its high computational demands present challenges for battery-powered embedded systems like quadcopters. To address this, we apply a constraint removal approach to the altitude control of a quadcopter, aiming to improve computational efficiency and reduce energy consumption. The method involves an offline phase, where constraint bounds are precomputed, and an online phase, where inactive constraints are systematically removed. Simulation results indicate that this approach significantly reduces the computational burden of MPC while maintaining control performance. Furthermore, ongoing research addresses the consideration of disturbances for the constraint removal strategy.
This project has received funding from the European Union’s Horizon under grant no. 101079342 (Fostering Opportunities Towards Slovak Excellence in Advanced Control for Smart Industries).
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