Abstract
Conference Title: 2018 Annual American Control Conference (ACC) Conference Start Date: 2018, June 27 Conference End Date: 2018, June 29 Conference Location: Milwaukee, WI, USA This work focuses on the design of stochastic Lyapunov-based economic model predictive control (SLEMPC) systems for a broad class of stochastic nonlinear systems with input constraints. Under the assumption of stabilizability of the origin of the stochastic nonlinear system via a stochastic Lyapunov-based control law, an economic model predictive controller is proposed that utilizes suitable constraints based on the stochastic Lyapunov-based controller to ensure economic optimality, recursive feasibility and stability in probability in a well-characterized region of the state-space. A chemical process example is used to illustrate the application of the approach and demonstrate its economic benefits with respect to an existing robust EMPC scheme that treats the disturbances in a deterministic, bounded manner.