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Fixed-time observer based adaptive neural network time-varying formation tracking control for multi-agent systems via minimal learning parameter approach 期刊论文
IET CONTROL THEORY AND APPLICATIONS, 2020, 卷号: 14, 期号: 9, 页码: 1147-1157
作者:  Xiong, Tianyi;  Pu, Zhiqiang;  Yi, Jianqiang;  Tao, Xinlong
收藏  |  浏览/下载：283/0  |  提交时间：2020/07/06
neurocontrollers  multi-agent systems  Lyapunov methods  closed loop systems  nonlinear control systems  time-varying systems  adaptive control  observers  uncertain systems  position control  radial basis function networks  robust control  control system synthesis  learning (artificial intelligence)  minimal learning-parameter approach  fixed-time CLSO  time-varying formation tracking problem  formation tracking control scheme  multiagent systems  time-varying formation tracking control problem  model uncertainties  velocity measurements  radial basis function neural networks  fixed-time cascaded leader state observer  fixed-time observer-based adaptive neural network time-varying formation tracking control  RBFNN-based adaptive control scheme  
Using reinforcement learning techniques to solve continuous-time non-linear optimal tracking problem without system dynamics 期刊论文
IET CONTROL THEORY AND APPLICATIONS, 2016, 卷号: 10, 期号: 12, 页码: 1339-1347
作者:  Zhu, Yuanheng;  Zhao, Dongbin;  Li, Xiangjun
浏览  |  Adobe PDF(976Kb)  |  收藏  |  浏览/下载：387/161  |  提交时间：2016/12/26
Nonlinear Control Systems  Continuous Time Systems  Learning (Artificial Intelligence)  Optimal Control  Dynamic Programming  Lyapunov Methods  Linear Systems  Reinforcement Learning  Continuous-time Problem  Nonlinear Optimal Tracking Problem  Adaptive Dynamic Programming  Model-free Adaptive Optimal Tracking Algorithm  Lyapunov Analysis  Linear System