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Force Sensorless Admittance Control With Neural Learning for Robots With Actuator Saturation 期刊论文
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 2020, 卷号: 67, 期号: 4, 页码: 3138-3148
作者:  Peng, Guangzhu;  Yang, Chenguang;  He, Wei;  Chen, C. L. Philip
收藏  |  浏览/下载：224/0  |  提交时间：2020/03/30
Robot sensing systems  Admittance  Manipulators  Force  Torque  Adaptation models  Adaptive neural control  admittance control  neural networks (NNs)  observer  
Adaptive Neural Network Control for Active Suspension Systems With Time-Varying Vertical Displacement and Speed Constraints 期刊论文
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 2019, 卷号: 66, 期号: 12, 页码: 9458-9466
作者:  Liu, Yan-Jun;  Zeng, Qiang;  Tong, Shaocheng;  Chen, C. L. Philip;  Liu, Lei
收藏  |  浏览/下载：263/0  |  提交时间：2019/12/16
Active suspension systems (ASSs)  adaptive control  barrier Lyapunov function (BLF)  neural networks (NNs)  
Neural Network Filtering Control Design for Nontriangular Structure Switched Nonlinear Systems in Finite Time 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2019, 卷号: 30, 期号: 7, 页码: 2153-2162
作者:  Sui, Shuai;  Chen, C. L. Philip;  Tong, Shaocheng
收藏  |  浏览/下载：252/0  |  提交时间：2019/12/16
Common Lyapunov function  finite time  non-triangular structure  switched systems  
Fuzzy Adaptive Finite-Time Control Design for Nontriangular Stochastic Nonlinear Systems 期刊论文
IEEE TRANSACTIONS ON FUZZY SYSTEMS, 2019, 卷号: 27, 期号: 1, 页码: 172-184
作者:  Sui, Shuai;  Chen, C. L. Philip;  Tong, Shaocheng
收藏  |  浏览/下载：222/0  |  提交时间：2019/07/12
Multiple-input and multiple-output (MIMO) stochastic nonlinear systems  nontriangular form  state filter  stochastically finite-time control  
Finite-Time Filter Decentralized Control for Nonstrict-Feedback Nonlinear Large-Scale Systems 期刊论文
IEEE TRANSACTIONS ON FUZZY SYSTEMS, 2018, 卷号: 26, 期号: 6, 页码: 3289-3300
作者:  Sui, Shuai;  Tong, Shaocheng;  Chen, C. L. Philip
收藏  |  浏览/下载：263/0  |  提交时间：2019/07/12
Backstepping technique  filter state observer  finite time  nonlinear large-scale systems  nonstrict-feedback form