Results 201 to 210 of about 37,119 (308)

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

open access: yesInternational 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   +4 more
wiley   +1 more source

Deep Reinforcement Learning‐Based Control for Real‐Time Hybrid Simulation of Civil Structures

open access: yesInternational Journal of Robust and Nonlinear Control, EarlyView.
ABSTRACT Real‐time Hybrid Simulation (RTHS) is a cyber‐physical technique that studies the dynamic behavior of a system by combining physical and numerical components that are coupled through a boundary condition enforcer. In structural engineering, the numerical components are subjected to environmental loads that become dynamic displacements of the ...
Andrés Felipe Niño   +6 more
wiley   +1 more source

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

open access: yesJournal 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   +3 more
wiley   +1 more source

PID Controller

open access: yesThe Review of Laser Engineering, 2011
openaire   +2 more sources

Redefining Optimal Coverage Path Planning for FLS‐Equipped AUVs With Deep Reinforcement Learning

open access: yesJournal of Field Robotics, EarlyView.
ABSTRACT Autonomous Underwater Vehicles (AUVs) have emerged as indispensable tools for a variety of subsea tasks, from habitat monitoring and seabed mapping to infrastructure inspection and mine countermeasures. A fundamental challenge in this field is Coverage Path Planning (CPP), the problem of ensuring complete and efficient area coverage.
Lorenzo Cecchi   +3 more
wiley   +1 more source

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