机构

• 自动化研究所 [3]
• 长春光学精密机械与物... [1]

采集方式

• OAI收割 [4]

内容类型

• 期刊论文 [3]
• 会议论文 [1]

发表日期

• 2021 [1]
• 2019 [1]
• 2013 [1]
• 2006 [1]

学科主题

筛选

浏览/检索结果: 共4条，第1-4条 帮助 条数/页： 5101520253035404550556065707580859095100 排序方式： 请选择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作者升序作者降序 A Vibration Control Method for Hybrid-Structured Flexible Manipulator Based on Sliding Mode Control and Reinforcement Learning 期刊论文  OAI收割 IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2021, 卷号: 32, 期号: 2, 页码: 841-852 作者:  Long, Teng;  Li, En;  Hu, Yunqing;  Yang, Lei;  Fan, Junfeng   |  收藏  |  浏览/下载：30/0  |  提交时间：2021/03/29 Vibrations  Mathematical model  Manipulator dynamics  Torque  Robustness  Neural networks  Hybrid-structured flexible manipulator  reinforcement learning  sliding mode control  vibration control method   Neural Dynamics for Control of Industrial Agitator Tank With Rapid Convergence and Perturbations Rejection 期刊论文  OAI收割 IEEE ACCESS, 2019, 卷号: 7, 页码: 102941-102950 作者:     |  收藏  |  浏览/下载：33/0  |  提交时间：2019/12/16 Chemical industry  automatic control  control design  neural dynamics method  rapid convergence  perturbations rejection   Neural-network-based online optimal control for uncertain non-linear continuous-time systems with control constraints 期刊论文  OAI收割 IET CONTROL THEORY AND APPLICATIONS, 2013, 卷号: 7, 期号: 17, 页码: 2037-2047 作者:  Yang, Xiong;  Liu, Derong;  Huang, Yuzhu 收藏  |  浏览/下载：34/0  |  提交时间：2015/08/12 adaptive control  approximation theory  closed loop systems  continuous time systems  Lyapunov methods  neurocontrollers  nonlinear control systems  optimal control  robust control  uncertain systems  neural network-based online adaptive optimal control  uncertain nonlinear continuous-time systems  control constraints  infinite-horizon optimal control problem  control policy  saturation constraints  identifier-critic architecture  Hamilton-Jacobi-Bellman equation approximation  uncertain system dynamics  critic NN  action-critic dual networks  reinforcement learning  identifier NN  policy iteration  LyapunovaEuros direct method  closed loop system stability   An improved adaptive neural network method for control system (EI CONFERENCE) 会议论文  OAI收割 2006 International Conference on Machine Learning and Cybernetics, August 13, 2006 - August 16, 2006, Dalian, China Wang L.-M.; Xie M.-J.; Wu D.-Y. 收藏  |  浏览/下载：23/0  |  提交时间：2013/03/25 Classical methods for designing a controller depend on the accuracy of system model. However  plant's models and other parts in a physical system can not accurately represent all possible dynamics. Thus the controller designed is usually not the optimal one. In this article  a new  simple adaptive control method  which combines the classical frequency domain method with the neural network theory  is proposed. Firstly  we can obtain a controller using classical method. Secondly we use the coefficients in digitized controller equation as the initial values of an Adaline network. Finally  LMS learning rules is used to adjust the weights adaptively. Experimental results show that this method is very effective in improving the performance of conventional controller. 2006 IEEE.