机构

• 长春光学精密机械与物... [1]
• 数学与系统科学研究院 [1]
• 生态环境研究中心 [1]

采集方式

• OAI收割 [3]

内容类型

• 期刊论文 [2]
• 会议论文 [1]

发表日期

• 2016 [1]
• 2015 [1]
• 2011 [1]

学科主题

筛选

浏览/检索结果: 共3条，第1-3条 帮助 条数/页： 5101520253035404550556065707580859095100 排序方式： 请选择题名升序题名降序提交时间升序提交时间降序作者升序作者降序发表日期升序发表日期降序 Tuning of Sampled-Data ADRC for Nonlinear Uncertain Systems 期刊论文  OAI收割 JOURNAL OF SYSTEMS SCIENCE & COMPLEXITY, 2016, 卷号: 29, 期号: 5, 页码: 1187-1211 作者:  Xue Wenchao;  Huang Yi   |  收藏  |  浏览/下载：25/0  |  提交时间：2018/07/30 Active disturbance rejection control (ADRC)  extended state observer  nonlinear uncertain systems  parameters tuning  sampled-data control   Comparing Machine Learning Classifiers for Object-Based Land Cover Classification Using Very High Resolution Imagery 期刊论文  OAI收割 REMOTE SENSING, 2015, 卷号: 7, 期号: 1, 页码: 153-168 作者:  Qian, Yuguo;  Zhou, Weiqi;  Yan, Jingli;  Li, Weifeng;  Han, Lijian 收藏  |  浏览/下载：16/0  |  提交时间：2016/03/03 object-based classification  machine learning classifiers  very high resolution image  urban area  tuning parameters   A fuzzy control method based on information integration for double inverted pendulum (EI CONFERENCE) 会议论文  OAI收割 2011 2nd International Conference on Digital Manufacturing and Automation, ICDMA 2011, August 5, 2011 - August 7, 2011, Zhangjiajie, Hunan, China 作者:  Fan Y. 收藏  |  浏览/下载：59/0  |  提交时间：2013/03/25 This article proposes a new fuzzy controller based on information integration. The mathematical model of Linear double inverted pendulum has been studied and estabLished with dynamics analytical method and LQR theory is used to design the optimal Linear inverted pendulum controller  then  the integration technology is used to design the variable parameters self-tuning fuzzy controller. Thereby  the fuzzy controller input variable dimension and the number of fuzzy control rules have been extremely reduced. Two controllers are designed for inverted pendulum system control and the comparison simulation experiments have been done. The results show that the controllers can both reaLize good control  and the fuzzy controller has higher precision  faster response  better stabiLity and robustness. 2011 IEEE.