Adaptive temperature control of a reverse flow process by using reinforcement learning approach by A. Binid (22046054)

“…First, a policy iteration algorithm is introduced to learn the optimal solution of the associated linear-quadratic control problem online. …”

DeepRaman: Implementing surface-enhanced Raman scattering together with cutting-edge machine learning for the differentiation and classification of bacterial endotoxins by Samir Brahim, Belhaouari

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Low Cost Autopilot Design Using Fuzzy Supervisory Control by Hadi, Mahmoud

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A Data-Driven Decision-Making Framework for Fleet Management in the Government Sector of Dubai by ALGHANEM, HANI SUBHI MOHD

“…The proposed framework comprises key elements: Important Decisions derived from interviews with transportation leaders, Knowledge Management enhanced by AI algorithms, Data Mining/Analysis utilizing historical data, the Fleet Management System employing Oracle ERP, and a Data-Driven Decision Support Framework that leans towards the extended framework approach. …”
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Brain Source Localization in the Presence of Leadfield Perturbations by Momin, Rabiya Nakhat

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IDENTIFICATION AND CONTROL STRATEGY APPLIED IN LOAD MANAGEMENT OF RESIDENTIAL AIR-CONDITIONERS by Hussain, Syed Ameenuddin

“…These steps involve identifying the parameters of systems and applying the control strategies as forced duty cycles. An integrated simulation environment was developed wherein the identification and control algorithm were implemented. …”
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An Intelligent and Low-Cost Eye-Tracking System for Motorized Wheelchair Control by Mahmoud Dahmani (18810247)

“…This required modifying a motorized wheelchair to adapt it to the predictions output by the gaze estimation algorithm. The wheelchair control can bypass any decision made by the gaze estimator and immediately halt its motion with the help of an array of proximity sensors, if the measured distance goes below a well-defined safety margin. …”

Real-Time Selective Harmonic Mitigation Technique for Power Converters Based on the Exchange Market Algorithm by Abraham Marquez Alcaide (18582451)

“…The Exchange Market Algorithm (EMA), initially focused on optimizing financial transactions, is considered and executed to achieve the SHM targets. …”

Parameter identification of PV solar cells and modules using bio dynamics grasshopper optimization algorithm by Mostafa Jabari (21841727)

“…The BDGOA addresses deficiencies in both exploration and exploitation phases, exhibiting exceptional convergence speed and efficiency. The algorithm's simplicity, achieved through the implementation of an elimination phase and controlled search space, enhances its performance without intricate calculations. …”

Augmented arithmetic optimization algorithm using opposite-based learning and lévy flight distribution for global optimization and data clustering by Abu Zitar, Raed

A new fuzzy logic controller based IPM synchronous motor drive by Abido, M.A.

“…The proposed FLC is designed to have less computational burden, which makes it suitable for online implementation. The FLC parameters are optimized by genetic algorithm. …”
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A simplified sliding‐mode control method for multi‐level transformerless DVR by Hasan Komurcugil (16388513)

“…Therefore, the weighting factor necessity in the control algorithm is eliminated. Finally, the steady-state error in the compensation voltage is eliminated by the proportional-resonant (PR) controller. …”

Digital-Twin-Based Diagnosis and Tolerant Control of T-Type Three-Level Rectifiers by Ali Sharida (17947847)

“…Then, the DT is used for the diagnosis and tolerance of open-switch faults (OSFs) and faults related to voltage and current sensors or for sensorless control. The OSF detection and localization algorithm is implemented based on the dynamic response difference between the physical system and its DT. …”

Advanced Quantum Control with Ensemble Reinforcement Learning: A Case Study on the XY Spin Chain by Farshad Rahimi Ghashghaei (20880995)

“…<p dir="ltr">This research presents an ensemble Reinforcement Learning (RL) approach that combines Deep Q-Network (DQN) and Proximal Policy Optimization (PPO) algorithms to tackle quantum control problems. This research aims to use the complementary strengths of DQN and PPO algorithms to develop robust and adaptive control policies for noisy and uncertain quantum systems. …”

A simulated annealing-based optimal controller for a three phase induction motor by Mantawy, A.H.

“…The proposed algorithm comprises structure of the optimal controller, a new error system and vector control of a three phase IM. …”
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A PLC based power factor controller for a 3-phase induction motor by Al-Ali, A.R.

“…The look-up table is prepared according to a measured value of the phase angle between the stator phase voltage and the stator phase current. Implementation of a software algorithm incorporates measuring the power factor angle, selecting the binary pattern according to the control strategy and sending command signals to switch the appropriate capacitors and protection switches. …”
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Guidance, Control and Trajectory Tracking of Small Fixed Wing Unmanned Aerial Vehicles (UAV's) by Al-Radaideh, Amer

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An Incentivized and Optimized Dynamic Mechanism for Demand Response for Managing Voltage in Distribution Networks by Md Moktadir Rahman (16904751)

“…A holistic and practical approach of DR implementation is missing in the literature. This study proposes a dynamic fair incentive mechanism using a multi-scheme load control algorithm for a large number of DR participants coordinating with the existing network equipment for managing voltage at medium voltage (MV) networks. …”

Evolutionary support vector regression for monitoring Poisson profiles by Ali Yeganeh (16624998)

“…This paper aims to monitor Poisson profile monitoring problem in Phase II and develops a new robust control chart using support vector regression by incorporating some novel input features and evolutionary training algorithm. …”

Nonlinear analysis of shell structures using image processing and machine learning by M.S. Nashed (16392961)

“…The proposed approach can be significantly more efficient than training a machine learning algorithm using the raw numerical data. To evaluate the proposed method, two different structures are assessed where the training data is created using nonlinear finite element analysis. …”