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自动化研究所 [65]

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	Distributed Economic MPC for Synergetic Regulation of the Voltage of an Island DC Micro-Grid 期刊论文 IEEE/CAA Journal of Automatica Sinica, 2024, 卷号: 11, 期号: 3, 页码: 734-745 作者: Yi Zheng; Yanye Wang; Xun Meng; Shaoyuan Li; Hao Chen 收藏 \| 浏览/下载：2/0 \| 提交时间：2024/02/19 Distributed model predictive control (DMPC) Lyapunov-based model predictive control micro-grid (MG) voltage control
	Finite-Time Stabilization for Constrained Discrete-time Systems by Using Model Predictive Control 期刊论文 IEEE/CAA Journal of Automatica Sinica, 2024, 卷号: 11, 期号: 7, 页码: 1656-1666 作者: Bing Zhu; Xiaozhuoer Yuan; Li Dai; Zhiwen Qiang 收藏 \| 浏览/下载：0/0 \| 提交时间：2024/06/07 Constraints deadbeat control finite-time stabilization model predictive control (MPC)
	Multistep Look-Ahead Policy Iteration for Optimal Control of Discrete-Time Nonlinear Systems With Isoperimetric Constraints 期刊论文 IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, 2023, 页码: 13 作者: Li, Tao; Wei, Qinglai; Wang, Fei-Yue 收藏 \| 浏览/下载：1/0 \| 提交时间：2024/02/22 Performance analysis Optimal control Dynamic programming Iterative algorithms Upper bound Measurement Convergence Adaptive dynamic programming (ADP) isoperimetric constraints nonlinear systems optimal control policy iteration
	ADMM-based joint rescheduling method for high-speed railway timetabling and platforming in case of uncertain perturbation ✩ 期刊论文 TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES, 2023, 卷号: 152, 页码: 27 作者: Liu, Xuan; Zhou, Min; Dong, Hairong; Wu, Xingtang; Li, Yidong 收藏 \| 浏览/下载：3/0 \| 提交时间：2023/11/17 Timetable rescheduling Platforming Uncertain perturbation Model predictive control Alternative direction method of multipliers
	CSR: Cascade Conditional Variational Auto Encoder with Socially-aware Regression for Pedestrian Trajectory Prediction 期刊论文 PATTERN RECOGNITION, 2023, 卷号: 133, 页码: 10 作者: Zhou, Hao; Ren, Dongchun; Yang, Xu; Fan, Mingyu; Huang, Hai 收藏 \| 浏览/下载：25/0 \| 提交时间：2022/11/14 Pedestrian trajectory prediction Socially -aware model Conditional variational autoencoder (CVAE)
	Dynamic-horizon model-based value estimation with latent imagination 期刊论文 IEEE Transactions on Neural Networks and Learning Systems, 2022, 页码: 1-14 作者: Wang JJ(王俊杰); Zhang QC(张启超); Zhao DB(赵冬斌) 收藏 \| 浏览/下载：11/0 \| 提交时间：2023/05/30 Latent world model model-based value expansion (MVE) reinforcement learning reinforcement learning
	A New Approach to Finite-Horizon Optimal Control for Discrete-Time Affine Nonlinear Systems via a Pseudolinear Method 期刊论文 IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 2022, 卷号: 67, 期号: 5, 页码: 2610-2617 作者: Wei, Qinglai; Zhu, Liao; Li, Tao; Liu, Derong 收藏 \| 浏览/下载：39/0 \| 提交时间：2022/07/25 Time-varying systems Nonlinear systems Optimal control Heuristic algorithms Dynamic programming Neural networks Linear systems Adaptive dynamic programming approximate dynamic programming finite horizon nonlinear systems optimal control pseudolinear approximation
	A New Neuro-Optimal Nonlinear Tracking Control Method via Integral Reinforcement Learning with Applications to Nuclear Systems 期刊论文 NEUROCOMPUTING, 2022, 卷号: 483, 页码: 361-369 作者: Zhong, Weifeng; Wang, Mengxuan; Wei, Qinglai; Lu, Jingwei 收藏 \| 浏览/下载：15/0 \| 提交时间：2022/06/10 Integral reinforcement learning Nuclear power reactor Nonlinear system Optimal tracking control Neural networks
	A Fusion Kalman Filter and UFIR Estimator Using the Influence Function Method 期刊论文 IEEE/CAA Journal of Automatica Sinica, 2022, 卷号: 9, 期号: 4, 页码: 709-718 作者: Wei Xue, Xiaoli Luan, Shunyi Zhao, Fei Liu 收藏 \| 浏览/下载：26/0 \| 提交时间：2022/03/09 Fusion filter,influence function,Kalman filter (KF),robustness,unbiased finite impulse response (FIR)
	Discrete-Time Self-Learning Parallel Control 期刊论文 IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, 2022, 卷号: 52, 期号: 1, 页码: 192-204 作者: Wei, Qinglai; Wang, Lingxiao; Lu, Jingwei; Wang, Fei-Yue 收藏 \| 浏览/下载：41/0 \| 提交时间：2022/02/16 Optimal control Nonlinear systems Time-varying systems Performance analysis Complex systems Biological neural networks ACP adaptive dynamic programming (ADP) approximate dynamic programming nonlinear systems optimal control parallel control reinforcement learning

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