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自动化研究所 [4]
山东大学 [4]
武汉大学 [3]
湖南大学 [3]
大连理工大学 [2]
北京航空航天大学 [2]
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期刊论文 [24]
发表日期
2019 [24]
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Neural Adaptive Event-Triggered Control for Nonlinear Uncertain Stochastic Systems With Unknown Hysteresis
期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2019, 卷号: 30, 期号: 11, 页码: 3300-3312
作者:
Wang, Jianhui
;
Liu, Zhi
;
Zhang, Yun
;
Chen, C. L. Philip
收藏
  |  
浏览/下载:12/0
  |  
提交时间:2020/03/30
Actuators
Hysteresis
Nonlinear systems
Artificial neural networks
Adaptive systems
Stochastic systems
System performance
Actuator failure
adaptive control
event-triggered
neural networks (NNs)
stochastic nonlinear systems
unknown direction hysteresis
Baffles Optimization of a Flat Plat Solar Air Collector with Double Channels
期刊论文
Shanghai Jiaotong Daxue Xuebao/Journal of Shanghai Jiaotong University, 2019, 卷号: 53, 期号: 11, 页码: 1302-1307
作者:
Zhang, Dong
;
Zhang, Jianjun
;
Zhang, Yuezhi
;
Li, Jinping
;
Wang, Linjun
收藏
  |  
浏览/下载:20/0
  |  
提交时间:2020/11/14
Efficiency
Optimization
Double channel
Efficiency increase
Flat plate
Flow dead zone
Optimization scheme
Perforated baffles
Solar air collector
Thermal Performance
Improving the light energy utilization of an avalanche photodiode array detector by using a micro compound parabolic concentrator array
期刊论文
Journal of Optical Technology (A Translation of Opticheskii Zhurnal), 2019, 卷号: 86, 期号: 10, 页码: 642-646
作者:
Huang, Yuan
;
Ma, Xiaoyu
;
Rao, Changhui
收藏
  |  
浏览/下载:12/0
  |  
提交时间:2021/05/06
Robust adaptive visual tracking control for uncertain robotic systems with unknown dead-zone inputs
期刊论文
JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS, 2019, 卷号: 356, 期号: 12, 页码: 6255-6279
作者:
Wang, Fujie
;
Liu, Zhi
;
Chen, C. L. Philip
;
Zhang, Yun
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  |  
浏览/下载:45/0
  |  
提交时间:2019/12/16
Adaptive Fuzzy Tracking Control of Uncertain Nonlinear Systems Subject to Actuator Dead Zone With Piecewise Time-Varying Parameters
期刊论文
IEEE TRANSACTIONS ON FUZZY SYSTEMS, 2019, 卷号: 27, 期号: 7, 页码: 1493-1505
作者:
Lu, Kaixin
;
Liu, Zhi
;
Lai, Guanyu
;
Zhang, Yun
;
Chen, C. L. Philip
收藏
  |  
浏览/下载:47/0
  |  
提交时间:2019/12/16
Adaptive fuzzy control
dead zone
piecewise Lyapunov function
prescribed performance
Adaptive Reinforcement Learning Control Based on Neural Approximation for Nonlinear Discrete-Time Systems With Unknown Nonaffine Dead-Zone Input
期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2019, 卷号: 30, 期号: 1, 页码: 295-305
作者:
Liu, Yan-Jun
;
Li, Shu
;
Tong, Shaocheng
;
Chen, C. L. Philip
收藏
  |  
浏览/下载:44/0
  |  
提交时间:2019/07/12
Discrete-time systems
neural networks (NNs)
nonlinear systems
optimal control
reinforcement learning
Global fast terminal sliding mode controller for hydraulic turbine regulating system with actuator dead zone
期刊论文
JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS, 2019, 卷号: 356, 期号: 15, 页码: 8366-8387
作者:
Chen, Zhihuan
;
Yuan, Xiaohui*
;
Wu, Xiaotao*
;
Yuan, Yanbin
;
Lei, Xiaohui
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  |  
浏览/下载:23/0
  |  
提交时间:2019/12/04
Adaptive neural control for switched nonlinear systems with unknown backlash-like hysteresis and output dead-zone
期刊论文
NEUROCOMPUTING, 2019, 卷号: 357, 页码: 203-214
作者:
Ma, Li
;
Huo, Xin
;
Zhao, Xudong
;
Niu, Ben
;
Zong, Guangdeng
收藏
  |  
浏览/下载:19/0
  |  
提交时间:2019/12/02
Neural tracking control
Switched nonlinear systems
Nonstrict-feedback structure
Backstepping
Output dead-zone
H∞ non-fragile observer-based dynamic event-triggered sliding mode control for nonlinear networked systems with sensor saturation and dead-zone input
期刊论文
ISA transactions, 2019, 卷号: 94, 页码: 93-107
作者:
Chu Xiaoan
;
Li Muguo
收藏
  |  
浏览/下载:22/0
  |  
提交时间:2019/12/02
Dead-zone control,Dynamic event-triggered scheme,Lipschitz nonlinear networked systems,Sensor saturation,Sliding mode control
Estimating the maximum impact force of dry granular flow based on pileup characteristics
期刊论文
JOURNAL OF MOUNTAIN SCIENCE, 2019, 卷号: 16, 期号: 10, 页码: 2435-2452
作者:
Xiao Si-you
;
Su Li-jun
;
Jiang Yuan-jun
;
Mehtab Alam
;
Li Cheng
收藏
  |  
浏览/下载:24/0
  |  
提交时间:2019/11/26
Dry granular flow
Tilted retaining wall
Impact force
Discrete element method
Pileup height
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