Intelligent HVAC Control: Comparative Simulation of Reinforcement Learning and PID Strategies for Energy Efficiency and Comfort Optimization by Atef Gharbi, Mohamed Ayari, Nasser Albalawi, Yamen El Touati, Zeineb Klai

“…Our framework integrates real-time sensor data with a scalable RL architecture, allowing autonomous optimization without the need for a precise system model. …”
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A neural-network-enhanced parameter-varying framework for multi-objective model predictive control applied to buildings by Dylan Wald, Olga Doronina, Kathryn Johnson, Ryan King, Michael Sinner, Kevin Griffin, Rohit Chintala, Deepthi Vaidhynathan, Jibonananda Sanyal, Marc Day

“…We show that ANPV-MPC can approximate the building system dynamics with a 28.39% higher accuracy than traditional linear model predictive control, resulting in 36.23% better control performance without increasing complexity of the optimal control problem. …”
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Optimization Control of Flexible Power Supply System Applied to Offshore Wind–Solar Coupled Hydrogen Production by Lishan Ma, Rui Dong, Qiang Fu, Chunjie Wang, Xingmin Li

“…This paper addresses these challenges by proposing a novel harmonic control strategy and load response optimization approach. …”
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Nonlinear Adaptive Optimal Control Design and Implementation for Trajectory Tracking of Four-Wheeled Mecanum Mobile Robots by Yung-Hsiang Chen

“…This study proposes a nonlinear adaptive optimal control method, the adaptive <i>H</i>₂ control method, applied to the trajectory tracking problem of the wheeled mobile robot (WMR) with four-wheel mecanum wheels. …”
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Research on Load Adaptive Control for High-Frequency Motion of Voice Coil Motor With Online Parameter Optimization by Feng Huang, Chenxi Wang, Qipeng Li

“…To address this issue, this research proposes an innovative adaptive control method based on online parameter optimization. …”
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An improved meta-heuristic algorithm to optimize the fractional-order controller for an industrial manipulator with a parallelogram structure by Nazila Nikdel

“…Therefore, this article pursues two main objectives: 1) controlling the robotic system by presenting a method based on fractional-order calculus so that it can control the system despite its complexity and non-linearity, 2) presenting the meta-heuristic algorithm "Improved Grey Wolf" to optimize the system response.Methodology: First, the mathematical model of the robot is presented based on Lagrange rules, and then the fractional-order calculus is used to design the controller. …”
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Comparative analysis and optimal allocation of virtual inertia from grid‐forming and grid‐following controlled ESSs by Naixuan Zhu, Pengfei Hu, Chongxi Jiang, Yanxue Yu, Daozhuo Jiang

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Optimizing Controlled-Resonance Acoustic Metamaterials with Perforated Plexiglass Disks, Honeycomb Structures, and Embedded Metallic Masses by Giuseppe Ciaburro, Gino Iannace, Virginia Puyana Romero

“…In this research, we present the optimization of a resonance-controlled acoustic metamaterial based on a sandwich structure composed of perforated plexiglass disks, honeycomb structures, and added metal masses. …”
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Optimal Coherence Length Control in Interferometric Fiber Optic Hydrophones via PRBS Modulation: Theory and Experiment by Wujie Wang, Qihao Hu, Lina Ma, Fan Shang, Hongze Leng, Junqiang Song

“…In this study, we propose a pseudo-random binary sequence (PRBS) phase modulation method for laser coherence length control, establishing the first theoretical model that quantitatively links PRBS parameter to coherence length, elucidating the mechanism underlying its suppression of parasitic interference noise. …”
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Improving Muscle Force Distribution Model Using Reflex Excitation: Toward a Model-Based Exoskeleton Torque Optimization Approach by Mojtaba Rayati, Rezvan Nasiri, Majid Nili Ahmadabadi

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Structural Optimization and Fluid–Structure Interaction Analysis of a Novel High-Speed Switching Control Valve by Hexi Ji, Jiazhen Han, Yong Wang, Yongkang Liu, Yudong Xie, Sen Yang, Derui Shi, Yilong Song

“…Subsequently, an optimized control valve structure model was proposed. …”
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Optimizing larval mass-rearing techniques for Aedes mosquitoes: enhancing production and quality for genetic control strategies by Mamai Wadaka, Brengues Cécile, Maiga Hamidou, Wallner Thomas, Herbin Anthony, Whiteside Mathieu, Kotla Simran Singh, Bueno-Masso Odet, Somda Nanwintoum Sévérin Bimbilé, Xi Zhiyong, Yamada Hanano, de Beer Chantel Janet, Bouyer Jérémy

“…The quantity and quality of laboratory-reared insects are pivotal for the success of any sterile male-release program. Optimizing larval mass-rearing methods to enhance both production and quality in Aedes mosquitoes is essential to meet the growing demand from FAO/IAEA Member States for the sterile insect technique (SIT) as a component of area-wide integrated pest management to control or suppress disease vectors. …”
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Centralized Regulation and Optimization Strategy for MV Distribution Network with PV Integration by Zezhou WANG, Mingming ZHANG, Fengqiang QIAN, Hongyi ZHOU, Haomiao YU

“…Then, a multi-objective optimal control model is established, with the power flow balance equation, node voltage, branch current and system operation as constrains, and with the minimal network loss, minimal voltage fluctuation and maximum consumption of DGs as objective. …”
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Performance Optimization of Synchronous Reluctance Motor using Adaptive MTPA Curve Fitting with Anti-Windup Current Control by Alex V, Rammohan A

“…This method effectively minimizes computational burden while preserving high control accuracy. The proposed method derives a mathematical model based on the motor torque equation, where the optimal d-axis and q-axis current components are expressed as a function of motor parameters, including inductances, rotor position, and torque demand. …”
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Research on WSN lifetime optimization game algorithm combined power and channel by Xiaochen HAO, Ning YAO, Lixia XIE, Jiaojiao WANG, Liyuan WANG

“…Due to the problem of shortening the network lifetime which was caused by the big energy consumption for wireless sensor network (WSN) whose energy and computing power was limit,a lifetime optimization game algorithm combined power control and channel allocation (LOAPC) was proposed.The influence of node power and residual energy on the node interference was explored to construct an interference affection measurement model.Then,expected transmission times was introduced to establish a novel node lifetime model.Finally,LOAPC aimed at reducing interference and prolonging lifetime,and the node power was limited by an optional power set which ensured the network connectivity and economized energy consumption,so as to prolong the network lifetime effectively.At the same time,the simulation results show that the algorithm has the characteristics of low interference,low energy consumption and effectively prolonging the lifetime of the network.…”
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The hot-to-cold spot quotient for SAR-based treatment planning in deep microwave hyperthermia by Massimiliano Zanoli, Hana Dobšíček Trefná

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Optimizing osteoarthritis care through clinical and community partnership: Results of an exploratory trial by Kelli D. Allen, Liubov Arbeeva, Leigh F. Callahan, Katherine Combs, Tamara Godfrey, Yvonne M. Golightly, Derek Hales, Carla Hill, Katie F. Huffman, Amanda E. Nelson, Jennifer Rees, Todd A. Schwartz

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Experimental and Computational Modeling of Complex Fluid Dispensing Systems by Sheldon Wang, Dalong Gao, Hassan Pouraria, Mary Nall, Ethan Shumaker, Amit Yonjan

“…In this work, we present a series of experimental and computational modeling procedures related to precision controls of intermittent dispensing systems for complex fluids. …”
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Optimal Control Strategy Design Based on Dynamic Programming for a Dual-Motor Coupling-Propulsion System by Shuo Zhang, Chengning Zhang, Guangwei Han, Qinghui Wang

“…A dual-motor coupling-propulsion electric bus (DMCPEB) is modeled, and its optimal control strategy is studied in this paper. …”
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Optimization of EEG-based wheelchair control: machine learning, feature selection, outlier management, and explainable AI by Amr M. Hamed, Abdel-Fattah Attia, Heba El-Behery

“…This study proposes an optimized classification framework that evaluates ten machine learning (ML) models, emphasizing ensemble methods, feature selection (FS), and outlier utilization. …”
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