Distributed model predictive control of switched nonlinear systems

In this work, we present a framework for the design of distributed model predictive control systems for a broad class of switched nonlinear systems for which the mode transitions take place according to a prescribed switching schedule. Under appropriate stabilizability assumptions on the existence of a set of feedback controllers that can stabilize the closed-loop switched, nonlinear system, we design a cooperative, distributed model predictive control architecture using Lyapunov-based model predictive control in which the distributed controllers carry out their calculations in parallel and communicate in an iterative fashion to compute their control actions. The proposed distributed model predictive control design is applied to a nonlinear chemical process network with scheduled mode transitions.