Research on Optimal Control Strategy for Unpowered Downslope of High-Voltage Inspection Robot Based on Motor Temperature Rise in Complexity Microgrid Networks by Zhiyong Yang, Qiao Fang, Zihao Zhang, Xing Liu, Xianjin Xu, Yu Yan, Chen Miao

“…Firstly, the thermal equivalent circuit model of the walking motor is established, and the mapping relationship between the armature winding temperature of the walking motor and ambient temperature is solved; secondly, the influence of armature winding temperature on unpowered downhill speed and energy recovery control strategy of robot is analyzed; thirdly, according to the temperature of front and rear wheel walking motors and the temperature difference between them, the optimal control strategy of unpowered downhill speed and energy recovery of robot is put forward; fourthly, by adjusting the duty ratio u of the energy consumption speed control system and the front wheel feedback brake distribution factor λ, the temperature difference between the front and rear wheel walking motors is reduced. …”
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Optimal control strategy based on artificial intelligence applied to a continuous dark fermentation reactor for energy recovery from organic wastes by Kelly Joel Gurubel Tun, Elizabeth León-Becerril, Octavio García-Depraect

“…Machine learning (ML) and optimization methods are used to model the nonlinear process and then, a neural predictive control (NPC) strategy to drive the system to its optimal operating order under varying influent conditions is developed. …”
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Disturbance Observer Based on Fixed Time Sliding Mode Control and Optimal State Observer for Three-Phase Three-Level T-Type Inverters by Anh Tuan Duong, Thanh Long Pham, Van Nam Giap, Phuong Vu

“…This paper presents the advanced control method together with the disturbance rejection method with the aims to obtain the low of total harmonic distortion (THD). …”
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LD-aminopterin in the canine homologue of human atopic dermatitis: a randomized, controlled trial reveals dosing factors affecting optimal therapy. by John A Zebala, Alan Mundell, Linda Messinger, Craig E Griffin, Aaron D Schuler, Stuart J Kahn

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A Self-Tuning Variable Universe Fuzzy PID Control Framework with Hybrid BAS-PSO-SA Optimization for Unmanned Surface Vehicles by Huixia Zhang, Zhao Zhao, Yuchen Wei, Yitong Liu, Wenyang Wu

“…In this study, a hybrid heading control framework for unmanned surface vehicles (USVs) is proposed, combining variable domain fuzzy Proportional–Integral–Derivative (VUF-PID) with an improved algorithmic Beetle Antennae Search–Particle Swarm Optimization–Simulated Annealing (BAS-PSO-SA) optimization to address the multi-objective control challenge. …”
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Tooth Aligned Control of Shifting Process in a Dedicated Hybrid Transmission by Wei Ren, Ming Cao

“…To accomplish TAC with short duration and high precision, a novel model predictive control (MPC) approach based on Pontryagin’s minimum principle (PMP-MPC) is proposed. …”
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Quantitative evaluation of hospital workplace violence prevention and control policies in China: based on PMC index model by Haoyu Chi, Hanye Tang, Chao Sun, Linjun Zhong, Jiaqi Guo, Yuanheng Li, Yazhou Wang, Mingxue Ma, Lifeng Wei, Jingzhi Wang, Jiajun Shi, Kun Wei, Jida Li, Wei Jiang, Peihang Sun, Mingli Jiao

“…Abstract Background Hospital workplace violence (WPV) is a serious obstacle to the sustainable development of global health care, Therefore, it is necessary to adjust and optimize the current WPV prevention and control policies (WPVPCPs), and policy evaluation is the first prerequisite of this link. …”
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Multi-Agent Deep Reinforcement Learning Cooperative Control Model for Autonomous Vehicle Merging into Platoon in Highway by Jiajia Chen, Bingqing Zhu, Mengyu Zhang, Xiang Ling, Xiaobo Ruan, Yifan Deng, Ning Guo

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Soft actor-critic algorithm and improved GNN model in secure access control of disaggregated optical networks by Zhenqian Zhao, Yuhe Wang

“…Within this framework, the Soft Actor-Critic (SAC) algorithm is employed to construct a policy optimization mechanism. By integrating entropy-guided multi-objective reinforcement learning, GESAC maps encoded network states to access control strategies, jointly optimizing for security, service quality, and system resilience. …”
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Optimized BCMA/CS1 bispecific TRuC-T cells secreting IL-7 and CCL21 robustly control multiple myeloma by Min Li, Rong Zheng, Rong Zheng, Zairu Liu, Zairu Liu, Peiyuan Zhang, Tingwei Zhu, Tingwei Zhu, Xueyi Xin, Xueyi Xin, Hongli Zhao, Wenyi Chen, Binjiao Zheng, Ai Zhao, Jimin Gao, Jimin Gao

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Probabilistic Neural Networks (PNNs) for Modeling Aleatoric Uncertainty in Scientific Machine Learning by Farhad Pourkamali-Anaraki, Jamal F. Husseini, Scott E. Stapleton

“…Contributions of this paper include the development of a probabilistic distance metric to optimize PNN architecture, and the deployment of PNNs in controlled data sets as well as a practical material science case involving fiber-reinforced composites. …”
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Research on Safety Control Method of Power Grid Energy Storage System Based on Neural Network Model by Xianglong Chen, Wei Xie

“…This paper presents a security control method of Grid energy storage based on neural network model. …”
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Control of Formation of Foreign Language Written and Speech Skills with the Help of Mobile Applications: Theoretical and Methodological Model by E. K. Danilina

“…The results of testing this model in the educational process are presented. It is concluded that the theoretical and methodological model proposed by the author can contribute to the optimization of the forming control system, which allows to effectively adjust the learning process.…”
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Influence of Clearances in Variable Guide Vanes and Stators on the Performance of a Multi-stage Compressor and Its Flow Control by L. Huang, W. Chu, H. Zhang, Z. Guo

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Accurate Suspension Force Modeling and Its Control System Design Based on the Consideration of Degree-of-Freedom Interaction by Weiyu Zhang, Aojie Xu

“…To better adapt the established accurate model and ensure precise control of the flywheel battery system under various working conditions, the firefly algorithm is employed to optimize the BP neural network (FA-BPNN). …”
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Arterial Multi-Path Green Wave Control Model Concurrently Considering Motor Vehicles and Electric Bicycles by Binbin Jing, Fan Yang

“…To tackle this, an arterial multi-path green wave control model that considers both motor vehicles(cars and buses) and electric bicycles is presented in this paper. …”
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Systematic Review of Hierarchical and Multi-Agent Optimization Strategies for P2P Energy Management and Electric Machines in Microgrids by Paul Arévalo, Danny Ochoa-Correa, Edisson Villa-Ávila, Vinicio Iñiguez-Morán, Patricio Astudillo-Salinas

“…However, existing research often remains fragmented, with limited integration between control strategies, optimization frameworks, and practical implementation. …”
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Optimized biosynthesis and performance enhancement of γ-PGA from Bacillus licheniformis: a study on wettability, microstructure, and environmental performance by Mingming Cheng, Shuoshi Zhang, Jianbo Gao, Wenqing Liu, Gang Zhou, Tao Sui, Daoquan Cheng, Cheng Wang, Xiangchuan Wang, Xiaoyan Li, Yuxi Li

“…For operational face dust control, γ-PGA can be applied through high-pressure spray systems directly onto coal mining surfaces. …”
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Economic Model Predictive Control for Wastewater Treatment Processes Based on Global Maximum Error POD-TPWL by Zhiyu Wang, Jing Zeng, Jinfeng Liu

“…To address the challenge of low computational efficiency in nonlinear Economic Model Predictive Control (EMPC) for large-scale systems such as wastewater treatment plants (WWTPs), this paper proposes a Trajectory Piecewise Linearization (TPWL)-based EMPC framework integrated with global maximum error control (GMEC) and Proper Orthogonal Decomposition (POD). …”
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Extended State Observer-Based Robust Model Predictive Velocity Control for Permanent Magnet Synchronous Motor by Eunji Lee, Yonghao Gui, Sesun You, Jun Moon, Wonhee Kim

“…By estimating the state variables and disturbance using the ESO, the model predictive control (MPC) finds the optimal control input by predicting future system behavior. …”
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