Abstract Model predictive control (MPC) has achieved considerable success in the process
industries, with its ability to deal with linear and nonlinear models, while observing system …

Abstract Model Predictive Control (MPC) has a long history in the field of control
engineering. It is one of the few areas that has received on‐going interest from researchers …

Objective: To investigate the cognitive skills of patients with relapsing remitting multiple
sclerosis (RRMS), secondary progressive MS (SPMS), and primary progressive MS (PPMS) …

In Model Predictive Controller (MPC) design, the traditional approach of expanding the
future control signal uses the forward shift operator to obtain the linear-in-the-parameters …

Machine learning has attracted extensive interest in the process engineering field, due to the
capability of modeling complex nonlinear process behavior. This work presents a method for …

An intermittent controller with fixed sampling interval is recast as an event-driven controller.
The key aspect of intermittent control that makes this possible is the use of basis functions …

This paper describes a new method for the design of model predictive control (MPC) using
non-minimal state space models, in which the state variables are chosen as the set of …

In this paper, a novel robust model predictive controller (R-MPC) for wave energy converters
(WECs) is proposed. The controller combines a constrained function-based predictive …

In the aftermath of super storm Sandy, a large region from North Carolina to Maine endured
food shortages, power outages, and long lines at gas stations forced to ration fuel due to low …

This paper introduces a continuous-time constrained control strategy, which mimics the
behavior of a traditional model predictive control scheme using dynamic feedback. The …