Search Results - "Twin delayed deep deterministic policy gradient algorithm"

Adaptive neuro-fuzzy PID controller based on twin delayed deep deterministic policy gradient algorithm by Shi, Qian, Lam, Hak-Keung, Xuan, Chengbin, Chen, Ming

“…This paper presents an adaptive neuro-fuzzy PID controller based on twin delayed deep deterministic policy gradient (TD3) algorithm for nonlinear systems. In…”
Get full text

Multiagent-based deep reinforcement learning framework for multi-asset adaptive trading and portfolio management by Cheng, Li-Chen, Sun, Jian-Shiou

“…The highly dynamic nature of stock markets has motivated researchers to propose various supervised learning models to assist investors to optimize financial…”
Get full text

Coordinated automatic generation control of interconnected power system with imitation guided exploration multi-agent deep reinforcement learning by Li, Jiawen, Yu, Tao, Zhang, Xiaoshun

“…•An intelligent automatic power generation control (IAGC) framework is proposed.•The proposed framework can improve the dynamic performance and reduce…”
Get full text

A novel data-driven model-free synchronization protocol for discrete-time multi-agent systems via TD3 based algorithm by Liu, Zhongxin, Li, Ye, Lan, Ge, Chen, Zengqiang

“…System modeling is a complex and time-consuming task in engineering, and traditional model-based or observer-based methods are unable to deal situations when…”
Get full text

Trajectory planning of redundant parallel mechanism considering motion accuracy based on reinforcement learning by Zeng, Chen-dong, Qiu, Zhi-cheng, Zhang, Fen-hua, Zhang, Xian-min

“…The motion accuracy of the trajectory directly affects the reliability of parallel mechanisms in precision tasks such as micro-assembly. Thus, this paper…”
Get full text

Network-level aircraft trajectory planning via multi-agent deep reinforcement learning: Balancing climate considerations and operational manageability by Baneshi, Fateme, Cerezo-Magaña, María, Soler, Manuel

“…Optimizing flight trajectories emerges as a viable strategy to mitigate the non-CO2 climate impacts of aviation. However, integrating individually optimized…”
Get full text

Deep reinforcement learning based controller with dynamic feature extraction for an industrial claus process by Liu, Jialin, Tsai, Bing-Yen, Chen, Ding-Sou

“…•The DRL-based controller integrating with the process dynamics is developed.•The dynamic feature is extracted from the historical data using the Seq2seq…”
Get full text

Satellite attitude tracking control of moving targets combining deep reinforcement learning and predefined-time stability considering energy optimization by Shi, Zhong, Zhao, Fanyu, Wang, Xin, Jin, Zhonghe

“…•An attitude tracking control method combining deep reinforcement learning and traditional satellite attitude controller for moving targets tracking and…”
Get full text

Reinforcement learning–driven proportional–integral–derivative controller tuning for mass–spring systems: Stability, performance, and hyperparameter analysis by Demircioğlu, Ufuk, Bakır, Halit

“…Artificial intelligence (AI) methods—particularly reinforcement learning (RL)—are used to tune Proportional–Integral–Derivative (PID) controller parameters for…”
Get full text

Reinforcement Learning for Dynamic Optimization of Eco-Driving in Smart Healthcare Transportation Networks by Cai, Wang, Anwlnkom, Tomley, Zhang, Lingling, Basheer, Shakila, Yang, Jing

“…Smart transportation networks face increasing demands for efficiency and sustainability. This study presents a reinforcement learning approach that optimizes…”
Get full text

Temperature Control of Proton Exchange Membrane Fuel Cell Based on Machine Learning by Li, Jiawen, Li, Yaping, Yu, Tao

“…In order to improve the proton exchange membrane fuel cell (PEMFC) working efficiency, we propose a deep-reinforcement-learning based PID controller for…”
Get full text

Twin Delayed Deep Deterministic Policy Gradient Algorithm for a Heterogeneous Multifactory Remanufacturing Optimization Problem by Qi, Liang, Zeng, Qiqi, Liu, Shixin, Wang, Jiacun, Qin, Shujin, Guo, Xiwang

“…To reduce resource consumption and environmental impact, the manufacturing industry increasingly leans towards repurposing, repairing, or updating products. In…”
Get full text

Adaptive Active Disturbance Rejection Load Frequency Control for Power System with Renewable Energies Using the Lyapunov Reward-Based Twin Delayed Deep Deterministic Policy Gradient Algorithm by Zheng, Yuemin, Tao, Jin, Sun, Qinglin, Sun, Hao, Chen, Zengqiang, Sun, Mingwei

“…The substitution of renewable energy sources (RESs) for conventional fossil fuels in electricity generation is essential in addressing environmental pollution…”
Get full text

Research on the Dynamic Characteristics Analysis and Power Control Method of Heat Pipe Reactors by Yin, Shaoxuan, Yu, Ren, Sheng, Dongjie, Mao, Wei, Zhao, Yudong

“…A heat pipe reactor (HPR) is a kind of modular small reactor with broad application prospects, and its dynamic characteristics and nuclear power control are…”
Get full text

Electro-Mechanical Actuators for Safety-Critical Aerospace Applications

“…Aircraft electrification is one of the most important and strategic initiatives currently supporting the innovation of the aviation industry. This manifests in…”
Get full text

Application of Deep Reinforcement Learning in Reconfiguration Control of Aircraft Anti-Skid Braking System by Liu, Shuchang, Yang, Zhong, Zhang, Zhao, Jiang, Runqiang, Ren, Tongyang, Jiang, Yuan, Chen, Shuang, Zhang, Xiaokai

“…The aircraft anti-skid braking system (AABS) plays an important role in aircraft taking off, taxiing, and safe landing. In addition to the disturbances from…”
Get full text

Path following control for powered parafoil system based on TD3-LADRC by Zheng, Yuemin, Tao, Jin, Sun, Qinglin, Sun, Hao, Sun, Mingwei, Chen, Zengqiang

“…The powered parafoil system is a distinctive flight vehicle that comprises a thrust device and an airdrop parafoil, affording significant advantages such as…”
Get full text

A TD3 Algorithm Based Reinforcement Learning Controller for DC-DC Switching Converters by Ye, Jian, Guo, Huanyu, Mei, Sen, Hu, Yingjie, Zhang, Xinan

“…Various linear and nonlinear controllers have been developed to improve the dynamic performance of DC-DC converters. Most controllers can only be designed on…”
Get full text

Intelligent Flight Control for Cruise Vehicle Based on Backstepping Design and Reinforcement Learning by Liu, Xiaodong, Jia, Chenhui, Yang, Qingjun, Wu, Tiancai, Zhang, Yu

“…Aiming at velocity/height tracking control and attitude stabilization for the longitudinal flight of cruise vehicle, the research of intelligent flight control…”
Get full text

Knowledge Assisted Deep Reinforcement Learning for Electric Vehicle Charging Control by Zai, Rui, Guo, Ye, Liu, Qiong, Sun, Hongbin, Wu, Qiuwei, Xiao, Li

“…Deep reinforcement learning (DRL) is a promising data-driven approach to solve the electric vehicle (EV) charging problem. However, DRL based charging…”
Get full text