Results 111 to 120 of about 7,728 (248)

A Multiple‐Model‐Informed Drug‐Development Approach for Optimal Regimen Selection of an Oncolytic Virus in Combination With Pembrolizumab

CPT: Pharmacometrics &Systems Pharmacology, Volume 14, Issue 3, Page 572-582, March 2025.
ABSTRACT The antitumor efficacy of an intratumoral injection of a genetically engineered oncolytic vaccinia virus carrying human IL‐7 and murine IL‐12 genes (hIL‐7/mIL‐12‐VV) was demonstrated in CT26.WT‐bearing mice. In the CT26.WT‐bearing mouse model, the efficacy of the combination of hIL‐7/mIL‐12‐VV plus the anti‐programmed cell death protein (PD)‐1
Akihiro Yamada, Mary P. Choules, Frances A. Brightman, Shigeru Takeshita, Shinsuke Nakao, Nobuaki Amino, Takeshi Nakayama, Masato Takeuchi, Kanji Komatsu, Fernando Ortega, Hitesh Mistry, David Orrell, Christophe Chassagnole, Peter L. Bonate   +13 more
wiley   +1 more source

A Two Degree of Freedom Approach for Discrete‐Time Sliding Mode Control

International Journal of Robust and Nonlinear Control, EarlyView.
ABSTRACT This paper proposes a new two degree of freedom (2‐DOF) framework for discrete‐time sliding mode control (DSMC) that decouples the disturbed evolution from its nominal counterpart. The novel nominal/disturbed subsystem separation for DSMC can be used to define multiple closed‐loop specifications. The nominal regulation (or tracking) controller
Tito L. M. Santos, Ary M. Batista
wiley   +1 more source

An accurate trajectory tracking method for low-speed unmanned vehicles based on model predictive control

Scientific Reports
Trajectory tracking on a low-speed vehicle using the model predictive control (MPC) algorithm usually assumes a simple road terrain. This assumption does not correspond to the actual road situation, leading to low tracking accuracy.
Lifen Wang, Sizhong Chen, Hongbin Ren
doaj   +1 more source

Accelerator Control Using Gaussian Process-Model Predictive Control (GP-MPC)

GP-MPC (Gaussian Process - Model Predictive Control) is a sophisticated control strategy to make informed decisions in control software systems. GPs are employed to model the dynamic behavior of the controlled system, monitoring not only expectedresponses but also uncertainties associated with the system reactions.
Aye, Su Lei, Kain, Verena, Schenk, Michael   +2 more
openaire   +2 more sources

Enhancing Reference Tracking in Induction Motor Drives: A Hybrid Model Predictive Control and Artificial Neural Network Approach

International Journal of Robust and Nonlinear Control, EarlyView.
ABSTRACT Induction motors (IMs) are widely used in industry for their robustness and cost‐effectiveness, yet their nonlinear and multivariable dynamics pose significant challenges for high‐performance speed control. Model Predictive Control (MPC) is a well‐established solution but suffers from limitations related to model accuracy and parameter ...
Asier del Rio, Oscar Barambones, Eneko Artetxe, Jokin Uralde, Isidro Calvo   +4 more
wiley   +1 more source

Model Predictive Control (MPC) Applied To Coupled Tank Liquid Level System

CoRR, 2014
Coupled Tank system used for liquid level control is a model of plant that has usually been used in industries especially chemical process industries. Level control is also very important for mixing reactant process. This survey paper tries to presents in a systemic way an approach predictive control strategy for a system that is similar to the process
openaire   +2 more sources

Multi‐Objective Bayesian Co‐Optimization of Parameterized Moving Horizon Estimation and Model Predictive Control

International Journal of Robust and Nonlinear Control, EarlyView.
ABSTRACT This paper proposes a Machine Learning (ML)‐enabled estimator‐controller design framework, in which a parameterized Model Predictive Controller (MPC) and a parameterized Moving Horizon Estimator (MHE) are jointly refined using Bayesian Optimization (BO).
Hossein Nejatbakhsh Esfahani, Javad Mohammadpour Velni   +1 more
wiley   +1 more source

Nonlinear Receding‐Horizon Differential Game for Drone Racing Along a Three‐Dimensional Path

International Journal of Robust and Nonlinear Control, EarlyView.
ABSTRACT Drone racing requires high‐speed navigation through three‐dimensional paths, posing significant challenges in control engineering. Existing control methods lack a feedback control framework that simultaneously addresses nonlinear drone dynamics and multi‐agent competitive interactions, such as overtaking or obstructing opponents.
Kijin Sung, Kenta Hoshino, Akihiko Honda, Takeya Shima, Toshiyuki Ohtsuka   +4 more
wiley   +1 more source

Control System for the Navigation of the Agricultural Robots: A Review

Journal of Field Robotics, EarlyView.
ABSTRACT Control systems for the navigation of autonomous agricultural robots—particularly those operating in uneven terrain and in the presence of static or dynamic obstacles—have advanced considerably in recent years. As conventional machinery evolves toward increasingly automated systems, the design of reliable navigation controllers has become ...
Edna Carolina Moriones Polanía, Hugo Rafacho Fernandes, Daniel Albiero, Angel Pontin Garcia   +3 more
wiley   +1 more source

Outracing a National Level Model Racing Car Champion: A Hybrid Model‐Based Data‐Driven Approach

Journal of Field Robotics, EarlyView.
ABSTRACT This paper discusses lap time optimization, focusing on a single lap without considering opponents in autonomous racing. The paper presents a control and optimization architecture composed of a model‐based low level controller and a higher level iterative learning algorithm with the goal of obtaining the fastest qualifying lap in autonomous ...
Mustafa Alp, Matteo Corno, Giulio Panzani, Sergio Matteo Savaresi   +3 more
wiley   +1 more source