Results 41 to 50 of about 3,837,082 (288)
Generalized Data–Driven Predictive Control: Merging Subspace and Hankel Predictors
Data–driven predictive control (DPC) is becoming an attractive alternative to model predictive control as it requires less system knowledge for implementation and reliable data is increasingly available in smart engineering systems.
M. Lazar, P. C. N. Verheijen
doaj +1 more source
Data-Driven Power Control for State Estimation: A Bayesian Inference Approach
We consider sensor transmission power control for state estimation, using a Bayesian inference approach. A sensor node sends its local state estimate to a remote estimator over an unreliable wireless communication channel with random data packet drops ...
Lau, Vincent +4 more
core +2 more sources
An Extended Kalman Filter for Data-enabled Predictive Control
The literature dealing with data-driven analysis and control problems has significantly grown in the recent years. Most of the recent literature deals with linear time-invariant systems in which the uncertainty (if any) is assumed to be deterministic and
Alpago, Daniele +2 more
core +1 more source
Achieving the Dispatchability of Distribution Feeders through Prosumers Data Driven Forecasting and Model Predictive Control of Electrochemical Storage [PDF]
We propose and experimentally validate a control strategy to dispatch the operation of a distribution feeder interfacing heterogeneous prosumers by using a grid-connected battery energy storage system (BESS) as a controllable element coupled with a ...
Cherkaoui, Rachid +3 more
core +4 more sources
Data-driven simulation and control [PDF]
Classical linear time-invariant system simulation methods are based on a transfer function, impulse response, or input/state/output representation. We present a method for computing the response of a system to a given input and initial conditions directly from a trajectory of the system, without explicitly identifying the system from the data ...
Markovsky, Ivan, Rapisarda, Paolo
openaire +3 more sources
COVID‐19 in cancer patients: The impact of vaccination on outcomes early in the pandemic
Background With the rapid evolution of the severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) pandemic, the development of effective and safe vaccines was of utmost importance to protect vulnerable individuals, including cancer patients ...
Fareed Khawaja +10 more
doaj +1 more source
Noniterative Data-Driven Gain-Scheduled Controller Design Based on Fictitious Reference Signal
This paper proposes a noniterative direct data-driven gain-scheduled control. Gain-scheduled proportional–integral–derivative (PID) control is one of the most popular approaches for nonlinear systems.
Shuichi Yahagi, Itsuro Kajiwara
doaj +1 more source
Data-Driven Dynamic Event-Triggered Control
This paper revisits the event-triggered control problem from a data-driven perspective, where unknown continuous-time linear systems subject to disturbances are taken into account. Using data information collected off-line instead of accurate system model information, a data-driven dynamic event-triggered control scheme is developed in this paper.
Tao Xu +3 more
openaire +3 more sources
ABSTRACT Background While Wilms tumor (WT) typically has a favorable prognosis, relapsed cases—especially those with high‐risk histology—remain therapeutically challenging after intensive frontline therapy. The combination of vincristine and irinotecan has demonstrated activity in pediatric solid tumors, and pazopanib, a multi‐targeted tyrosine kinase ...
Maria Debora De Pasquale +6 more
wiley +1 more source
Non-Iterative Data-Driven Tuning of Model-Free Control Based on an Ultra-Local Model
In this paper, we present a data-driven tuning method for model-free control based on an ultra-local model (MFC-ULM), which is also called intelligent proportional-integral-derivative control.
Shuichi Yahagi, Itsuro Kajiwara
doaj +1 more source

