Numerical analysis for the pure Neumann control problem using the gradient discretisation method
The article discusses the gradient discretisation method (GDM) for distributed optimal control problems governed by diffusion equation with pure Neumann boundary condition. Using the GDM framework enables to develop an analysis that directly applies to a
Droniou, Jerome +2 more
core +2 more sources
Collision Avoidance Using Finite Control Set Model Predictive Control for Unmanned Surface Vehicle
In recent years, with the development of unmanned platforms, unmanned surface vehicles (USV) are attracting more and more attention. Compared to ordinary ships, USV have a smaller volume and faster speed, so their collision avoidance system (CAS) should ...
Xiaojie Sun +4 more
doaj +1 more source
Machine Learning Based Adaptive Prediction Horizon in Finite Control Set Model Predictive Control
In this paper, an adaptive prediction horizon approach based on machine learning is presented for the finite control set model predictive control (FCS-MPC) of power converters. Usually, in FCS-MPC, the prediction horizon is kept constant.
Muhammad Saleh Murtaza Gardezi +1 more
doaj +1 more source
An Effective Finite Control Set-Model Predictive Control Method for Grid Integrated Solar PV
The grid integration of a photovoltaic solar system operating with maximum power point tracking is being presented in this paper. The system uses a dc-dc converter for power tracking while employing finite control set model predictive control (FCS-MPC ...
Iresha Poonahela +4 more
doaj +1 more source
A discrete-pulse optimal control algorithm with an application to spin systems [PDF]
This article is aimed at extending the framework of optimal control techniques to the situation where the control field values are restricted to a finite set. We propose a generalization of the standard GRAPE algorithm suited to this constraint.
Dridi, G. +4 more
core +3 more sources
Finite-Control-Set Model Predictive Control With Improved Steady-State Performance [PDF]
Finite-control-set model predictive control (FCS-MPC) is a novel and promising control scheme for power converters and drives. Many practical and theoretical issues have been presented in the literature, showing good performance of this technique. The present work deals with one of the most relevant aspects of any controller, namely, the steady-state ...
Ricardo P. Aguilera +2 more
openaire +4 more sources
Switching Control for Parameter Identifiability of Uncertain Systems
This paper considers the problem of identifying the parameters of an uncertain linear system by means of feedback control. The problem is approached by considering time-varying controllers.
Battistelli, G., Tesi, P.
core +1 more source
Robust Control of Uncertain Markov Decision Processes with Temporal Logic Specifications [PDF]
We present a method for designing robust controllers for dynamical systems with linear temporal logic specifications. We abstract the original system by a finite Markov Decision Process (MDP) that has transition probabilities in a specified uncertainty ...
Murray, Richard M. +2 more
core +3 more sources
ABSTRACT Objective To explore how cerebral hypoxia and Normal‐Appearing White Matter (NAWM) integrity affect MS lesion burden and clinical course. Methods Seventy‐nine MS patients, including 13 clinically isolated syndrome (CIS) patients and 66 relapsing–remitting multiple sclerosis (RRMS) patients, and 44 healthy controls (HCs) were recruited from ...
Xinli Wang +8 more
wiley +1 more source
Finite Control Set MPC for DFIG Direct Power Control in Distorted Grids
This work proposes Finite Control Set - Model Predictive Control (FCS-MPC) for direct power control of grid-connected Doubly-Fed Induction Generators (DFIG) under distorted voltage situations.
Yuri O. Cota, Alfeu J. Sguarezi Filho
doaj +1 more source

