Results 31 to 40 of about 584 (163)

Neural-Network Based MPC for Enhanced Lateral Stability in Electric Vehicles

IEEE Access
Distributed electric drive vehicles offer maneuver-ability but face stability challenges under different driving conditions. Model Predictive Control (MPC) algorithms can improve lateral stability, but their high computational demands hinder real-time ...
Ahmed Hassan, Sara Ruiz-Moreno, Jose Ramon D. Frejo, Jose M. Maestre, Eduardo Fernandez Camacho   +4 more
doaj   +1 more source

A Design Framework for Predictive Engine Control Un cadre de conception pour la commande prédictive de moteurs

Oil & Gas Science and Technology, 2011
Model Predictive Control (MPC) has been proposed several times for automotive control, with promising results, mostly based on a linear MPC approach. However, as most automotive systems are nonlinear, Nonlinear MPC (NMPC) would be an interesting option.
Wang X., Waschl H., Alberer D., del Re L.   +3 more
doaj   +1 more source

An Adaptive RBF-NMPC Architecture for Trajectory Tracking Control of Underwater Vehicles

Machines, 2021
An adaptive control algorithm based on the RBF neural network (RBFNN) and nonlinear model predictive control (NMPC) is discussed for underwater vehicle trajectory tracking control. Firstly, in the off-line phase, the improved adaptive Levenberg–Marquardt-
Zhenzhong Chu, Da Wang, Fei Meng
doaj   +1 more source

Improved Model Predictive Control Algorithm for the Path Tracking Control of Ship Autonomous Berthing

Journal of Marine Science and Engineering
To address the issues of path tracking accuracy and control stability in autonomous ship berthing, an improved algorithm combining nonlinear model predictive control (NMPC) and convolutional neural networks (CNNs) is proposed in this paper.
Chunyu Song, Xiaomin Guo, Jianghua Sui
doaj   +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

Ultra-Fast Nonlinear Model Predictive Control for Motion Control of Autonomous Light Motor Vehicles

World Electric Vehicle Journal
Advanced Driver Assistance System (ADAS) is the latest buzzword in the automotive industry aimed at reducing human errors and enhancing safety. In ADAS systems, the choice of control strategy is not straightforward due to the highly complex nonlinear ...
Vaishali Patne, Pramod Ubare, Shreya Maggo, Manish Sahu, G. Srinivasa Rao, Deepak Ingole, Dayaram Sonawane   +6 more
doaj   +1 more source

Key Technical Fields and Future Outlooks of Space Manipulators: A Survey

SmartBot, EarlyView.
This paper systematically reviews the technological development of space manipulators, emphasizing the unique challenges posed by space environments. It examines four areas: structural design, modeling, planning, and control, while introducing typical ground test platforms.
Gang Chen, Zeyuan Huang, Ying Yan, Xiaokang An, Zhikai Zhao, Jirong Lin, Xiangrong Zhao, Xianyuan Gao, Junyi Zong, Xuewen Jia, Zhipeng Yao, Jianliang Liao, Ning Ji   +12 more
wiley   +1 more source

Nonlinear Model Predictive Growth Control of a Class of Plant-Inspired Soft Growing Robots

IEEE Access, 2020
Recently, researchers have shown an increased interest in considering plants as a model of inspiration for designing new robot locomotions. Growing robots, that imitate the biological growth presented by plants, have proved irresistible in unpredictable ...
Haitham El-Hussieny, Ibrahim A. Hameed, Jee-Hwan Ryu   +2 more
doaj   +1 more source

AI in chemical engineering: From promise to practice

AIChE Journal, Volume 72, Issue 7, July 2026.
Abstract Artificial intelligence (AI) in chemical engineering has moved from promise to practice: physics‐aware (gray‐box) models are gaining traction, reinforcement learning complements model predictive control (MPC), and generative AI powers documentation, digitization, and safety workflows.
Jia Wei Chew, Ronnie Andersson, Thomas Bierweiler, Patrik Ryttestal, Torsten Wik   +4 more
wiley   +1 more source