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	Removing Feasibility Conditions on Adaptive Neural Tracking Control of Nonlinear Time-Delay Systems With Time-Varying Powers, Input, and Full-State Constraints 期刊论文 OAI收割 IEEE TRANSACTIONS ON CYBERNETICS, 2022, 卷号: 52, 期号: 4, 页码: 2553-2564 作者: Guo, Chao; Xie, Xue-Jun; Hou, Zeng-Guang \| 收藏 \| 浏览/下载：36/0 \| 提交时间：2022/06/10 Nonlinear systems Time-varying systems Control design Adaptive systems Delay effects Artificial neural networks Automation Feasibility conditions input and full-state constraints neural networks (NNs) nonlinear systems time-varying powers
	Adaptive Fuzzy Asymptotic Tracking Control of State-Constrained High-Order Nonlinear Time-Delay Systems and Its Applications 期刊论文 OAI收割 IEEE TRANSACTIONS ON CYBERNETICS, 2022, 卷号: 52, 期号: 3, 页码: 1671-1680 作者: Wu, You; Xie, Xue-Jun; Hou, Zeng-Guang \| 收藏 \| 浏览/下载：32/0 \| 提交时间：2022/07/25 Adaptive fuzzy asymptotic tracking control feasibility conditions full-state constraints high-order nonlinear time-delay systems
	Further Results on Adaptive Practical Tracking for High-Order Nonlinear Systems With Full-State Constraints 期刊论文 OAI收割 IEEE TRANSACTIONS ON CYBERNETICS, 2021, 页码: 8 作者: Xie, Xue-Jun; Wu, You; Hou, Zeng-Guang \| 收藏 \| 浏览/下载：22/0 \| 提交时间：2022/01/27 Nonlinear systems Adaptive systems Trajectory Safety Robots Lyapunov methods Fuzzy systems Adaptive practical tracking control feasibility conditions full-state constraints high-order nonlinear systems
	Support technique of ultra thin mirror in space optics (EI CONFERENCE) 会议论文 OAI收割 2nd International Symposium on Advanced Optical Manufacturing and Testing Technologies: Large Mirrors and Telescopes, November 2, 2005 - November 5, 2005, Xian, China 作者: Ren J.-Y.; Gao M.-H. 收藏 \| 浏览/下载：31/0 \| 提交时间：2013/03/25 With the development of space optical system the technique of ultra thin mirror come forth and is paid more attention because of less difficulty in machining low cost lightweight no disassembly during detecting and maintaining. The key technique takes advantage of deformation of ultra thin mirror as the influence of environment to adjust the surface figure. Its accuracy meets requirement. An analysis method is based on finite element analysis (FEA) and many items including the amount of support points the way of arrangement the optimum design of support component are studied. The finite element method was used to analyze the mirror and some different mirror support schemes. The principal aim of the mirror analysis is to get numbers of support points and the ways of the support. There are three schemes including 12-6-1 12-8-1 and 16-8-1 models. Deformation of deadweight is calculated under the three conditions. The way of 16-8-1 is more suitable than the designs of other two. The support subassembly is amended to meet with the mirror surface RMS in the range of 30m. Deformation of the mirror with support structure has been calculated. The result is 16.52nm lower than a quarter of the wavelength which indicates the feasibility of the support scheme applied to mirror. Theoretical result for the best way of support is presented. The result of analysis shows that requirement surface figure could be met through adjusting support points. It predicts feasibility of the support technique and provides theoretical value for active adjustment in the laboratory. At present support and adjusting experiment of ultra thin mirror is being carried on.
	Intelligent MRTD testing for thermal imaging system using ANN (EI CONFERENCE) 会议论文 OAI收割 ICO20: Remote Sensing and Infrared Devices and Systems, August 21, 2005 - August 26, 2005, Changchun, China Sun J.; Ma D. 收藏 \| 浏览/下载：25/0 \| 提交时间：2013/03/25 The Minimum Resolvable Temperature Difference (MRTD) is the most widely accepted figure for describing the performance of a thermal imaging system. Many models have been proposed to predict it. The MRTD testing is a psychophysical task for which biases are unavoidable. It requires laboratory conditions such as normal air condition and a constant temperature. It also needs expensive measuring equipments and takes a considerable period of time. Especially when measuring imagers of the same type the test is time consuming. So an automated and intelligent measurement method should be discussed. This paper adopts the concept of automated MRTD testing using boundary contour system and fuzzy ARTMAP but uses different methods. It describes an Automated MRTD Testing procedure basing on Back-Propagation Network. Firstly we use frame grabber to capture the 4-bar target image data. Then according to image gray scale we segment the image to get 4-bar place and extract feature vector representing the image characteristic and human detection ability. These feature sets along with known target visibility are used to train the ANN (Artificial Neural Networks). Actually it is a nonlinear classification (of input dimensions) of the image series using ANN. Our task is to justify if image is resolvable or uncertainty. Then the trained ANN will emulate observer performance in determining MRTD. This method can reduce the uncertainties between observers and long time dependent factors by standardization. This paper will introduce the feature extraction algorithm demonstrate the feasibility of the whole process and give the accuracy of MRTD measurement.