Results 71 to 80 of about 720,153 (314)
Convex model predictive control for collision avoidance
IET Control Theory & Applications, 2021 This manuscript proposes a model predictive control for collision avoidance for the regulation problem of deterministic linear systems, which provides a priori guarantees of strong system theoretic properties, such as positive invariance and asymptotic ...
Saša V. Raković +4 more
doaj +1 more source
Dynamic Positioning With Model Predictive Control [PDF]
IEEE Transactions on Control Systems Technology, 2016 Marine vessels with dynamic positioning (DP) capability are typically equipped with sufficient number of thrusters to make them overactuated and with satellite navigation and other sensors to determine their position, heading, and velocity. An automatic control system is tasked with coordinating the thrusters to move the vessel in any desired direction
Aleksander Veksler +3 more
openaire +2 more sources
Re‐Irradiation in Pediatric Diffuse Midline Glioma: A Multi‐Institutional Retrospective Study
Pediatric Blood &Cancer, EarlyView.ABSTRACT Background Children with recurrent diffuse midline gliomas (DMGs) have limited therapeutic options at recurrence. Re‐irradiation (RT2) may be used at progression, but with uncertainty about the benefit. Methods We conducted a multi‐institutional retrospective study of children aged < 18 with DMG treated at three centers (Toronto, Canada ...
Ajay Thomas Alex +13 more
wiley +1 more source
High-order volterra model predictive control and its application to a nonlinear polymerisation process [PDF]
, 2005 Model Predictive Control (MPC) has recently found wide acceptance in the process industry, but the existing design and implementation methods are restricted to linear process models. A chemical process involves, however, severe nonlinearity which cannot
Kashiwagi, H., Li, Y.
core +1 more source
Enhancing Strong Neighbor-Based Optimization for Distributed Model Predictive Control Systems
Mathematics, 2018 This paper considers a class of large-scale systems which is composed of many interacting subsystems, and each of them is controlled by an individual controller.
Shan Gao, Yi Zheng, Shaoyuan Li
doaj +1 more source
Direct Model-Predictive Control. [PDF]
, 2014 Due to simplicity and convenience, Model Predictive Control, which consists in optimizing future decisions based on a pessimistic deterministic forecast of the random processes, is one of the main tools for stochastic control. Yet, it suffers from a large computation time, unless the tactical horizon (i.e.
Christophe, Jean-Joseph +2 more
openaire +1 more source
Pediatric Blood &Cancer, EarlyView.ABSTRACT Background Survival after relapse in pediatric acute myeloid leukemia (AML) remains poor, highlighting the critical importance of identifying prognostic factors to guide optimal relapse management. Methods We investigated the prognostic impact of multiparameter flow cytometry (MFC) measurable residual disease (MRD) in 188 patients with first ...
Camilla Poulsen +21 more
wiley +1 more source
Nonlinear Model Predictive Control of an Inductive Power Transfer system [PDF]
, 2023 openIn this work a nonlinear model predictive control (NMPC) based method that can achieve fast transient response and provide good efficiency in the power transfer has been developed for an Inductive Power Transfer (IPT) system for battery charging of ...
TURRATO, VALENTINA
core
Pediatric Blood &Cancer, EarlyView.ABSTRACT Purpose Despite 5‐year survival rates of over 90% among children and adolescents/young adults (CAYAs) with classic Hodgkin lymphoma (cHL), 15%–20% relapse after frontline therapy. Prior analysis of frontline Children's Oncology Group (COG) clinical trials demonstrated that, despite similar rates of relapse, non‐Hispanic Black (NHB) and ...
Mallorie B. Heneghan +14 more
wiley +1 more source
Time Delay Compensation and Stability Analysis of Networked Predictive Control Systems Based on Hammerstein Model [PDF]
, 2007 A novel approach is proposed for a networked control system with random delays containing a nonlinear process based on a Hammerstein model. The method uses a time delay two step generalized predictive control (TDTSGPC), which consists of two parts, one ...
G.P. Liu +5 more
core +1 more source