Results 81 to 90 of about 922 (173)

A Novel Cascaded RPIDD2‐PI Controller Tuned by Enhanced Cooperation Search Algorithm for Automatic Voltage Regulator Systems

IET Control Theory &Applications, Volume 19, Issue 1, January/December 2025.
In this study, a novel cascaded RPIDD2‐PI controller is proposed for automatic voltage regulator (AVR) systems, marking its first application in the literature. This controller is designed to achieve superior voltage regulation by addressing critical performance metrics such as precision, stability, and dynamic responsiveness.
Davut Izci, Fatma A. Hashim, Serdar Ekinci, Sahar F. Sabbeh, Mohit Bajaj, Lukas Prokop, Ievgen Zaitsev   +6 more
wiley   +1 more source

An optimized feature selection using triangle mutation rule and restart strategy in enhanced slime mould algorithm

Egyptian Informatics Journal
This paper proposes an improved feature selection method based on an improved Slime Mould Algorithm (SMA), called the Triangular Mutation Rule Restart Strategy Slime Mould Algorithm (TRSMA), to overcome some of the shortcomings of the SMA, including ...
Ibrahim Musa Conteh, Gibril Njai, Abass Conteh, Qingguo Du   +3 more
doaj   +1 more source

Stability Enhancement of DC Microgrids Under CPLs Using Secretary Bird Optimization Algorithm‐Tuned Backstepping‐GITSM Control: Design, Simulation, and Experimental Approach

IET Power Electronics, Volume 18, Issue 1, January/December 2025.
This article presents a robust composite control strategy to stabilize DC microgrids affected by constant power loads (CPLs), which induce negative incremental impedance and destabilize system dynamics. By integrating Global Integral Terminal Sliding Mode Control with backstepping and optimizing parameters using the Secretary Bird Optimization ...
Md Saiful Islam, Israt Jahan Bushra, Tushar Kanti Roy, Jim Mortaej Chowdhury   +3 more
wiley   +1 more source

METAHEURISTIC-BASED TUNING OF PROPORTIONAL-DERIVATIVE LEARNING RULES FOR PROPORTIONAL-INTEGRAL FUZZY CONTROLLERS IN TOWER CRANE SYSTEM PAYLOAD POSITION CONTROL [PDF]

This paper proposes the use of metaheuristic optimization algorithms to tune the Proportional-Derivative (PD) learning rules within the framework of Iterative Learning Control applied to low-cost Takagi-Sugeno Proportional-Integral (PI)-fuzzy controllers
Bojan-Dragos, Claudia-Adina, Hedrea, Elena-Lorena, Petriu, Emil M., Precup, Radu-Emil, Roman, Raul-Cristian, Szedlak-Stinean, Alexandra-Iulia   +5 more
core   +2 more sources

The optimization of the loading ramp mechanism of a heavy-weight trailer [PDF]

, 2023
This research optimized the loading ramp mechanism of the trailer for transporting heavy construction machiner to minimize the force in the hydro-cylinder.
Bulatovic, Radovan, Marković, Goran, Mladenović, Predrag, Pavlovic, Goran, Savković, Mile, Zdravković, Nebojša B.   +5 more
core  

Green manufacturing electrical network scheduling using Slime Mould and Interior search algorithms [PDF]

The strategic reduction of power consumption in electrical machines, particularly within manufacturing networks, is critical for achieving energy efficiency and sustainability.
Belmabrouk, Karima, Dekhici, Latifa, Guerraiche, Khaled   +2 more
core   +1 more source

Enhancing software fault prediction using wrapper-based metaheuristic feature selection methods [PDF]

The application of software fault prediction (SFP) to predict faulty components at the early stage has been investigated in various studies. Reducing feature redundancy is key to enhancing the predictive accuracy of SFP models.
Binh, Nguyen Thanh, Duy, Dao Khanh, Ngan, Dang Thi Kim, Phuong, Ha Thi Minh   +3 more
core   +2 more sources

Machine learning-embedded energy cost optimization for hybrid flow shop scheduling toward low-carbon industrial energy systems

Unconventional Resources
Reducing energy consumption in industrial scheduling has become a critical concern for sustainable manufacturing. This paper addresses energy-aware scheduling in a multi-stage hybrid flow shop (HFS) system by proposing a novel framework that integrates ...
Latifa Dekhici, Khaled Guerraiche, Aykut Fatih Güven, Mohit Bajaj, Vojtech Blazek, Lukas Prokop   +5 more
doaj   +1 more source

Optimum Design of Steel Space Frames Using a Hybrid Slime Mould–Jaya Algorithm with Online Distributed Computing

Applied Sciences
This paper introduces a novel hybrid metaheuristic optimization algorithm, combining improved formulations of the Slime Mould Algorithm (SMA) and the Jaya Algorithm (JA) (HSMJA) with online distributed computing (ODC), referred to as HSMJA-ODC.
Ibrahim Behram Ugur, Luciano Lamberti, Sadik Ozgur Degertekin   +2 more
doaj   +1 more source

Investigating The Performance Of Metaheuristics To Optimize The Revenue Of Semiconductor Supply Chain [PDF]

, 2022
Investigating the performance of metaheuristics to optimise the revenue of the semiconductor supply chain is the final year project that focuses on to identify the supply chain shortage problem related to semiconductors and to compare among the 20 ...
Roslee, Muhammad Sharifuddin
core