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浏览/检索结果: 共5条，第1-5条 帮助 限定条件 发表日期：2023     已选(0)清除 条数/页：5101520253035404550556065707580859095100   排序方式：请选择作者升序作者降序题名升序题名降序发表日期升序发表日期降序提交时间升序提交时间降序 Event-Triggered-Based Consensus Neural Network Tracking Control for Nonlinear Pure-Feedback Multiagent Systems With Delayed Full-State Constraints 期刊论文 IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING, 2023, 页码: 11 作者:  Wang, Xiao-An;  Zhang, Guang-Ju;  Niu, Ben;  Wang, Ding;  Wang, Xiao-Mei 收藏  |  浏览/下载：6/0  |  提交时间：2024/02/22 Nonlinear multiagent systems  delayed full state constraints  event-triggered design  asymptotic tracking control  adaptive control   Robust Optimal Parallel Tracking Control Based on Adaptive Dynamic Programming 期刊论文 IEEE TRANSACTIONS ON CYBERNETICS, 2023, 页码: 14 作者:  Wei, Qinglai;  Jiao, Shanshan;  Wang, Fei-Yue;  Dong, Qi 收藏  |  浏览/下载：6/0  |  提交时间：2023/12/21 Optimal control  Control systems  Uncertainty  Robust control  Performance analysis  Dynamic programming  Uncertain systems  ADP  NN  nonlinear robust optimal control  parallel control  tracking control   Constrained-cost adaptive dynamic programming for optimal control of discrete-time nonlinear systems 期刊论文 IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2023, 卷号: 35, 期号: 3, 页码: 3251 - 3264 作者:  Wei, Qinglai;  Li, Tao 收藏  |  浏览/下载：0/0  |  提交时间：2024/05/28 Adaptive dynamic programming  approximate dynamic programming  constrained cost  optimal control  reinforcement learning   Dynamic Movement Primitives Based Robot Skills Learning 期刊论文 Machine Intelligence Research, 2023, 卷号: 20, 期号: 3, 页码: 396-407 作者:  Ling-Huan Kong 收藏  |  浏览/下载：8/0  |  提交时间：2023/05/29 Dynamic movement primitives (DMPs), trajectory tracking control, robot learning from demonstrations, neural networks (NNs), adaptive control   Dynamic Movement Primitives Based Robot Skills Learning 期刊论文 Machine Intelligence Research, 2023, 卷号: 20, 期号: 3, 页码: 396-407 作者:  Ling-Huan Kong;  Wei He;  Wen-Shi Chen;  Hui Zhang;  Yao-Nan Wang 收藏  |  浏览/下载：3/0  |  提交时间：2024/04/23 Dynamic movement primitives (DMPs), trajectory tracking control, robot learning from demonstrations, neural networks (NNs), adaptive control