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Fuzzy Adaptive Compensation Control of Uncertain Stochastic Nonlinear Systems With Actuator Failures and Input Hysteresis Journal article
IEEE TRANSACTIONS ON CYBERNETICS, 2019,Volume: 49,Issue: 1,Page: 2-13
Authors:  Wang, Jianhui;  Liu, Zhi;  Chen, C. L. Philip;  Zhang, Yun
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Actuator failure/fault  adaptive control  hysteresis  stochastic nonlinear systems  transient performance  
Fuzzy adaptive compensation control of uncertain stochastic nonlinear systems with actuator failures and input hysteresis Journal article
IEEE Transactions on Cybernetics, 2019,Volume: 49,Issue: 1,Page: 2-13
Authors:  Wang J.;  Liu Z.;  Chen C.L.P.;  Zhang Y.
Favorite  |  View/Download：2/0  |  Submit date：2019/02/11
Actuator failure/fault  adaptive control  hysteresis  stochastic nonlinear systems  transient performance  
Finite-Time Filter Decentralized Control for Nonstrict-Feedback Nonlinear Large-Scale Systems Journal article
IEEE TRANSACTIONS ON FUZZY SYSTEMS, 2018,Volume: 26,Issue: 6,Page: 3289-3300
Authors:  Sui, Shuai;  Tong, Shaocheng;  Chen, C. L. Philip
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Backstepping technique  filter state observer  finite time  nonlinear large-scale systems  nonstrict-feedback form  
Optimized Multi-Agent Formation Control Based on an Identifier-Actor--Critic Reinforcement Learning Algorithm Journal article
IEEE TRANSACTIONS ON FUZZY SYSTEMS, 2018,Volume: 26,Issue: 5,Page: 2719-2731
Authors:  Wen, Guoxing;  Chen, C. L. Philip;  Feng, Jun;  Zhou, Ning
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Fuzzy logic systems (FLSs)  identifier-actor-critic architecture  multi-agent formation  optimized formation control  reinforcement learning (RL)  
Prescribed Performance Observer-Based Adaptive Fuzzy Control for Nonstrict-Feedback Stochastic Nonlinear Systems Journal article
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, 2018,Volume: 48,Issue: 10,Page: 1747-1758
Authors:  Zhou, Qi;  Li, Hongyi;  Wang, Lijie;  Lu, Renquan
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Adaptive fuzzy control  input saturation  nonstrict-feedback system  prescribed performance  
Optimized Multi-Agent Formation Control Based on an Identifier-Actor-Critic Reinforcement Learning Algorithm Journal article
IEEE Transactions on Fuzzy Systems, 2018,Volume: 26,Issue: 5,Page: 2719-2731
Authors:  Wen G.;  Chen C.L.P.;  Feng J.;  Zhou N.
Favorite  |  View/Download：2/0  |  Submit date：2019/02/11
Fuzzy logic systems (FLSs)  identifier-actor-critic architecture  multi-agent formation  optimized formation control  reinforcement learning (RL)  
Histogram of Oriented Gradient Based Plantar Pressure Image Feature Extraction and Classification Employing Fuzzy Support Vector Machine Journal article
JOURNAL OF MEDICAL IMAGING AND HEALTH INFORMATICS, 2018,Volume: 8,Issue: 4,Page: 842-854
Authors:  Wang, Cunlei;  Li, Zairan;  Dey, Nilanjan;  Li, Zhaochun;  Ashour, Amira S.;  Fong, Simon James;  Sherratt, R. Simon;  Wu, Lijun;  Shi, Fuqian
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Artificial Intelligence  Machine Learning Algorithms  Fuzzy Logic  Image Mining  Health Care  
Neural Network-Based Adaptive Leader-Following Consensus Control for a Class of Nonlinear Multiagent State-Delay Systems Journal article
IEEE TRANSACTIONS ON CYBERNETICS, 2017,Volume: 47,Issue: 8,Page: 2151-2160
Authors:  Wen, Guoxing;  Chen, C. L. Philip;  Liu, Yan-Jun;  Liu, Zhi
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Consensus control  external disturbance  neural networks (NNs)  nonlinear multiagent systems  state delay  
Dempster-Shafer structure based fuzzy logic system for stochastic modeling Journal article
APPLIED SOFT COMPUTING, 2017,Volume: 56,Page: 134-142
Authors:  Li, Han-Xiong;  Wang, Yan;  Chen, C. L. Philip
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Fuzzy logic system  Dempster-Shafer theory  Stochastic uncertainty  
Dempster–Shafer structure based fuzzy logic system for stochastic modeling Journal article
Applied Soft Computing Journal, 2017,Volume: 56,Page: 134-142
Authors:  Li H.-X.;  Wang Y.;  Chen C.L.P.
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Dempster–Shafer theory  Fuzzy logic system  Stochastic uncertainty