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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：222/0  |  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  
Fuzzy Broad Learning System: A Novel Neuro-Fuzzy Model for Regression and Classification 期刊论文
IEEE TRANSACTIONS ON CYBERNETICS, 2020, 卷号: 50, 期号: 2, 页码: 414-424
作者:  Feng, Shuangg;  Chen, C. L. Philip
收藏  |  浏览/下载：210/0  |  提交时间：2020/03/30
Broad learning system (BLS)  classification  k-means  regression  Takagi-Sugeno (TS) fuzzy system  
Formation Control With Obstacle Avoidance for a Class of Stochastic Multiagent Systems 期刊论文
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 2018, 卷号: 65, 期号: 7, 页码: 5847-5855
作者:  Wen, Guoxing;  Chen, C. L. Philip;  Liu, Yan-Jun
收藏  |  浏览/下载：204/0  |  提交时间：2019/12/16
Directed topology  formation control  obstacle avoidance  stochastic multiagent system  H-infinity analysis  
Discriminative graph regularized broad learning system for image recognition 期刊论文
SCIENCE CHINA-INFORMATION SCIENCES, 2018, 卷号: 61, 期号: 11, 页码: 14
作者:  Jin, Junwei;  Liu, Zhulin;  Chen, C. L. Philip
收藏  |  浏览/下载：188/0  |  提交时间：2019/12/16
broad learning system  deep learning  graph regularization  image recognition  feature extraction  incremental learning  
Optimized Multi-Agent Formation Control Based on an Identifier-Actor--Critic Reinforcement Learning Algorithm 期刊论文
IEEE TRANSACTIONS ON FUZZY SYSTEMS, 2018, 卷号: 26, 期号: 5, 页码: 2719-2731
作者:  Wen, Guoxing;  Chen, C. L. Philip;  Feng, Jun;  Zhou, Ning
收藏  |  浏览/下载：240/0  |  提交时间：2019/12/16
Fuzzy logic systems (FLSs)  identifier-actor-critic architecture  multi-agent formation  optimized formation control  reinforcement learning (RL)  
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：250/0  |  提交时间：2019/12/16
Common Lyapunov function  finite time  non-triangular structure  switched systems  
Adaptive Tracking Control of Surface Vessel Using Optimized Backstepping Technique 期刊论文
IEEE TRANSACTIONS ON CYBERNETICS, 2019, 卷号: 49, 期号: 9, 页码: 3420-3431
作者:  Wen, Guoxing;  Ge, Shuzhi Sam;  Chen, C. L. Philip;  Tu, Fangwen;  Wang, Shengnan
收藏  |  浏览/下载：169/0  |  提交时间：2019/12/16
Actor-critic architecture  Lyapunov stability  optimized backstepping (OB)  reinforcement learning (RL)  surface vessel  
Formation control with obstacle avoidance of second-order multi-agent systems under directed communication topology 期刊论文
SCIENCE CHINA-INFORMATION SCIENCES, 2019, 卷号: 62, 期号: 9, 页码: 14
作者:  Wen, Guoxing;  Chen, C. L. Philip;  Dou, Hui;  Yang, Hongli;  Liu, Chunfang
收藏  |  浏览/下载：140/0  |  提交时间：2019/12/16
formation control  obstacle avoidance  artificial potential field method  H-infinity performance  second-order multi-agent system  directed topology  
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：259/0  |  提交时间：2019/12/16
Active suspension systems (ASSs)  adaptive control  barrier Lyapunov function (BLF)  neural networks (NNs)  
Universal Approximation Capability of Broad Learning System and Its Structural Variations 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2019, 卷号: 30, 期号: 4, 页码: 1191-1204
作者:  Chen, C. L. Philip;  Liu, Zhulin;  Feng, Shuang
收藏  |  浏览/下载：246/0  |  提交时间：2019/12/16
Broad learning system (BLS)  deep learning  face recognition  functional link neural networks (FLNNs)  non-linear function approximation  time-variant big data modeling  universal approximation