Seminar: Control of complex systems through differential flatness and Model Predictive Control

Abstract:

This talk will first introduce some research directions of LCIS lab of Grenoble INP related to the control of complex systems via optimization-based control, differential flatness and mixed-integer programming.

Next, we will concentrate on two applications: i) the hierarchical control of a meshed DC microgrid system and ii) quadcopter trajectory generation and tracking.

For the first application, a multi-scale supervision scheduling is developed to handle the load balancing problem for the efficient energy distribution within the transmission network.  The control architecture considers three control layers. These are implemented via a combination of differential flatness and MPC (Model Predictive Control). Flat representations serve to define analytically profile, costs and constraints which are subsequently used in an MPC framework.

For the second application involving the trajectory generation and tracking of thrust propelled vehicles, we will briefly highlight the use of differential flatness and B-splines parametrizations in a hierarchical control approach using feedback linearization and MPC.