Results 121 to 130 of about 469,590 (301)
This study introduces a data‐driven framework that combines deep reinforcement learning with classical path planning to achieve adaptive microrobot navigation. By training a surrogate neural network to emulate microrobot dynamics, the approach improves learning efficiency, reduces training time, and enables robust real‐time obstacle avoidance in ...
Amar Salehi +3 more
wiley +1 more source
PID Control Perspective: Techniques and Uses
This article covers both conventional and modern methods for PID tuning and its appli-cations in an array of fields. Because of its simple layout, ease of use, and ongoing research into PID tuning, PID control is used in the vast majority of control ...
Wisam Subhi Al-Dayyeni +1 more
doaj +1 more source
Sub‐Micrometer‐Precision Path Following of Piezo‐Actuated Mobile Robot
This article reports on the Holonomic‐Beetle (HB), a palm‐sized robot that achieves sub‐micrometer (sub‐µm) precision path tracking across spatial ranges from 100 µm to 10 mm. Using proportional‐integral‐derivative (PID) control, the HB accurately tracks both complex and straight paths with sub‐µm path errors, surpassing existing robots.
Eiji Kusui +9 more
wiley +1 more source
Development of three phase back to back converter with current flow control using raspberry Pi microcontroller [PDF]
A High-Voltage Direct Current (HVDC) electric power transmission system uses direct current form the bulk transmission of electrical power, in contrast with the common Alternating Current (AC) systems.
Mamat, Ibrahim
core
Shape memory alloy wires exhibit thermally induced phase changes that generate actuation strain and resistance variations enabling self‐sensing. However, hysteretic electromechanical behavior complicates accurate state estimation. This paper presents an artificial in‐based self‐sensing method to reconstruct SMA actuator position in real time, achieving
Krunal Koshiya +2 more
wiley +1 more source
Controlling Dynamical Systems Into Unseen Target States Using Machine Learning
Parameter‐aware next‐generation reservoir computing enables efficient, data‐driven control of dynamical systems across unseen target states and nonstationary transitions. The approach suppresses transient behavior while navigating system collapse scenarios with minimal training data—over an order of magnitude less than traditional methods.
Daniel Köglmayr +2 more
wiley +1 more source
Deep Learning Methods for Assessing Time‐Variant Nonlinear Signatures in Clutter Echoes
Motion classification from biosonar echoes in clutter presents a fundamental challenge: extracting structured information from stochastic interference. Deep learning successfully discriminates object speed and direction from bat‐inspired signals, achieving 97% accuracy with frequency‐modulated calls but only 48% with constant‐frequency tones. This work
Ibrahim Eshera +2 more
wiley +1 more source
ABSTRACT Introduction It is well established that exposure to chemical, radiological, and biological hazards in the workplace are infertility risk factors. Although workplace‐specific infertility risks have been documented, the associations between employment history and infertility risk remain largely unexplored.
Cerine Benomar +2 more
wiley +1 more source
Background Immune checkpoint inhibitors (ICIs) for cancer can lead to immune‐related adverse events, including ICI‐associated inflammatory arthritis (ICI‐IA). There are no validated International Classification of Diseases (ICD) code–based case definitions for ICI‐IA.
Manar Elsayed +11 more
wiley +1 more source
This study presents a comprehensive investigation into the optimization of PID control parameters for marine dual-fuel engines using an improved particle swarm algorithm.
Zhuo Hu +5 more
doaj +1 more source

