An Artificial Neural Network for Online Tuning of Genetic Algorithm Based PI Controller for Interior Permanent Magnet Synchronous Motor–Drive حسب Rahman, M. A.

"…An artificial neural network (ANN) for online tuning of a genetic algorithm based PI controller for interior permanent magnet synchronous motor (IPMSM) drive is presented in this paper. …"
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Parameter Identification of Flexible Drive Systems using Particle Swarm Optimization حسب Hafez, Ishaq

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Modeling and Identification of Nonlinear DC Motor Drive Systems Using Recurrent Wavelet Networks حسب Zahidi, Sarah Hussain

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Development and Implementation of a Hybrid Intelligent Controller for Interior Permanent Magnet Synchronous Motor Drives حسب Nasir Uddin, M.

"…In the optimization procedure a performance index is developed to reflect the minimum speed deviation, minimum settling time and zero steady-state error. A fuzzy basis function network (FBFN) is utilized for online tuning of the PI controller parameters to ensure optimum drive performance under different disturbances. …"
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Integrated Energy Optimization and Stability Control Using Deep Reinforcement Learning for an All-Wheel-Drive Electric Vehicle حسب Reza Jafari (3494018)

"…<p dir="ltr">This study presents an innovative solution for simultaneous energy optimization and dynamic yaw control of all-wheel-drive (AWD) electric vehicles (EVs) using deep reinforcement learning (DRL) techniques. …"

Modified Elite Opposition-Based Artificial Hummingbird Algorithm for Designing FOPID Controlled Cruise Control System حسب Abualigah, Laith

"…This study proposes a novel approach for designing a fractional order proportional-integral-derivative (FOPID) controller that utilizes a modified elite opposition-based artificial hummingbird algorithm (m-AHA) for optimal parameter tuning. Our approach outperforms existing optimization techniques on benchmark functions, and we demonstrate its effectiveness in controlling cruise control systems with increased flexibility and precision. …"
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Autonomous Robot Navigation Based On Recurrent Neural Networks حسب Al-Sagban, Mariam Qusai

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