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| A Wide Learning Approach for Interpretable Feature Recommendation for 1-D Sensor Data in IoT Analytics 期刊论文
International Journal of Automation and Computing, 2019, 卷号: 16, 期号: 6, 页码: 800-811
作者: Snehasis Banerjee; Tanushyam Chattopadhyay; Utpal Garain
 浏览 |  Adobe PDF(891Kb) |  收藏 | 浏览/下载：173/53 | 提交时间：2021/02/22
Feature engineering sensor data analysis Internet of things (IoT) analytics interpretable learning automation. |
| A Survey on 3D Visual Tracking of Multicopters 期刊论文
International Journal of Automation and Computing, 2019, 卷号: 16, 期号: 6, 页码: 707-719
作者: Qiang Fu; Xiang-Yang Chen; Wei He
浏览 | Adobe PDF(1299Kb) | 收藏 | 浏览/下载：154/53 | 提交时间：2021/02/22
Multicopter three-dimensional (3D) visual tracking camera placement camera calibration pose estimation. |
| Phenomenological Based Soft Sensor for Online Estimation of Slurry Rheological Properties 期刊论文
International Journal of Automation and Computing, 2019, 卷号: 16, 期号: 5, 页码: 696-706
作者: Jenny L. Diaz C.; Diego A. Muñoz; Hernan Alvarez
浏览 | Adobe PDF(2306Kb) | 收藏 | 浏览/下载：150/42 | 提交时间：2021/02/22
Soft sensor phenomenological based semi-physical model non-Newtonian fluids unknown input observer slurry flow. |
| Predictive Control Based on Fuzzy Supervisor for PWARX Hybrid Model 期刊论文
International Journal of Automation and Computing, 2019, 卷号: 16, 期号: 5, 页码: 683-695
作者: Olfa Yahya; Zeineb Lassoued; Kamel Abderrahim
浏览 | Adobe PDF(2179Kb) | 收藏 | 浏览/下载：83/50 | 提交时间：2021/02/22
Nonlinear control hybrid systems mixed logical dynamic (MLD) model predictive control fuzzy supervisor. |
| New LMI Conditions for Reduced-order Observer of Lipschitz Discrete-time Systems: Numerical and Experimental Results 期刊论文
International Journal of Automation and Computing, 2019, 卷号: 16, 期号: 5, 页码: 644-654
作者: Noussaiba Gasmi; Assem Thabet; Mohamed Aoun
 Adobe PDF(1366Kb) | 收藏 | 浏览/下载：87/25 | 提交时间：2021/02/22
Reduced-order observer discrete-time systems Lipschitz systems H∞ ARDUINO MEGA 2560 device. |
| A Fault Tolerant Control Scheme Using the Feasible Constrained Control Allocation Strategy 期刊论文
International Journal of Automation and Computing, 2019, 卷号: 16, 期号: 5, 页码: 628-643
作者: Mehdi Naderi; Tor Arne Johansen; Ali Khaki Sedigh
Adobe PDF(1916Kb) | 收藏 | 浏览/下载：82/41 | 提交时间：2021/02/22
Control allocation feasibility fault tolerant control model predictive control domain of attraction. |
| Multi-source Remote Sensing Image Registration Based on Contourlet Transform and Multiple Feature Fusion 期刊论文
International Journal of Automation and Computing, 2019, 卷号: 16, 期号: 5, 页码: 575-588
作者: Huan Liu; Gen-Fu Xiao; Yun-Lan Tan; Chun-Juan Ouyang
Adobe PDF(2216Kb) | 收藏 | 浏览/下载：141/39 | 提交时间：2021/02/22
Feature fusion multi-scale circle Gaussian combined invariant moment multi-direction gray level co-occurrence matrix multi-source remote sensing image registration contourlet transform. |
| A Linear Quadratic Controller Design Incorporating a Parametric Sensitivity Constraint 期刊论文
International Journal of Automation and Computing, 2019, 卷号: 16, 期号: 4, 页码: 553-562
作者: Mohamed Yagoubi
浏览 | Adobe PDF(1651Kb) | 收藏 | 浏览/下载：125/45 | 提交时间：2021/02/22
Linear quadratic control parametric uncertainties trajectory sensitivity non-standard Riccati equation Lur'e matrix equations linear time invariant (LMI) particle swarm optimization. |
| Control of a Two-wheeled Machine with Two-directions Handling Mechanism Using PID and PD-FLC Algorithms 期刊论文
International Journal of Automation and Computing, 2019, 卷号: 16, 期号: 4, 页码: 511-533
作者: Khaled M. Goher; Sulaiman O. Fadlallah
浏览 | Adobe PDF(2563Kb) | 收藏 | 浏览/下载：124/42 | 提交时间：2021/02/22
Two-wheeled inverted pendulum (IP) with two direction handling Lagrangian formulation proportional-integral-derivative (PID) fuzzy logic control (FLC) under-actuated systems. |
| Deep Learning Based Single Image Super-resolution: A Survey 期刊论文
International Journal of Automation and Computing, 2019, 卷号: 16, 期号: 4, 页码: 413-426
作者: Viet Khanh Ha; Jin-Chang Ren; Xin-Ying Xu; Sophia Zhao; Gang Xie; Valentin Masero; Amir Hussain
浏览 | Adobe PDF(1389Kb) | 收藏 | 浏览/下载：119/31 | 提交时间：2021/02/22
Image super-resolution convolutional neural network high-resolution image low-resolution image deep learning. |
