Abstract— In this paper we present a dual-based decomposition method, called here the proximal center method, to solve distributed model predictive control (MPC) problems for cou...
-- The goal of a dynamic power management policy is to reduce the power consumption of an electronic system by putting system components into different states, each representing ce...
In this paper, we investigate limiting behavior of linear dynamic systems driven by random stochastic matrices. We introduce and study the new concepts of partial ergodicity and 1-...
We present an extension of the Dynamics Based Control (DBC) paradigm to environment models based on Predictive State Representations (PSRs). We show an approximate greedy version ...
Ariel Adam, Zinovi Rabinovich, Jeffrey S. Rosensch...
Nonlinear model predictive control (MPC) of a simulated chaotic cutting process is presented. The nonlinear MPC combines a neural-network model and a genetic-algorithm-based optim...