作者：
F.L. LewisDept. of Electical Engineering
The University of Texas at Arlington U.S.A. F. L. Lewis was born in Wärzburg. Germany
subsequently studyning in Chile and Goruonstoun School in Scotland. He obtained the Bachelor's Degree in Physics/Electrical Engineering and the Master's of Electrical Engineering Degree at Rice University in 1971. He spent six years in the U.S. navy serving as Navigator aboard the frigate USS Trippe (FF-1075) and Executive Officer and Acting Commanding Officer aboard USS Salinan (ATF-161). In 1977 he received the Master's of Science in Aeronautical Engineering from the University of West Florida. In 1981 he obtained the Ph.D. degree at The Georgia Institute of Technology in Atlanta where he was employed as a professor from 1981 to 1990 and is currently an Adjunct Professor. He is a Professor of Electrical Engineering at The University of Texas at Arlington where he was awarded the Moncrief-O'Donnell Endowed Chair in 1990 at the Automation and Robotics Research Institute. Dr. Lewis has studied the geometric analytic and structural properties of dynamical systems and feedback control automation. His current interests include robotics intelligent control neural and fuzzy systes nonlinear systems and manufacturing process control. He is the author/co-author of 2 U.S. patents 124 journal papers 20 chapters and encyclopedia articles 210 refereed conference papers seven books: Optimal Control Optimal Estimation Applied Optimal Control and Estimation Aircraft Control and Simulation Control of Robot Manipulators Neural Network Control High-Level Feedback Control with Neural Networks and the IEEE reprint volume Robot Control. Dr. Lewis is a registered Professional Engineer in the State of Texas and was selected to the Editorial Boards of International Journal of Control Neural Computing and Applications and Int. J. Intelligent Control Systems. He is the recipient of an NSF Research Initiation Grant and has been continuously funded by NSF since 1982. Since 1991 he has received $1.8 m
A framework is given for controller design using Nonlinear Network Structures, which include both neural networks and fuzzy logic systems. These structures possess a universal approximation property that allows them t...
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A framework is given for controller design using Nonlinear Network Structures, which include both neural networks and fuzzy logic systems. These structures possess a universal approximation property that allows them to be used in feedback control of unknown systems without requirements for linearity in the system parameters or finding a regression matrix. Nonlinear nets can be linear or nonlinear in the tunable weight parameters. In the latter case weight tuning algorithms are not straightforward to obtain. Feedback control topologies and weight tuning algorithms are given here that guarantee closed-loop stability and bounded weights. Extensions are discussed to force control, backstepping control, and output feedback control, where dynamic nonlinear nets are required.
This paper describes a virtual reality and haptic interface between human and the Atomic Force Microscope (AFM), which allows the operator to sense and touch the surface and nanoparticles during the manipulation with ...
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This paper focuses on the nano-scale analysis of the mechanical properties of polymer and carbon nanotubes (CNT) embedded MEMS devices using the probe tip of the atomic force microscope (AFM).The mechanical properties...
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This paper focuses on the nano-scale analysis of the mechanical properties of polymer and carbon nanotubes (CNT) embedded MEMS devices using the probe tip of the atomic force microscope (AFM).The mechanical properties of the surfaces of layered materials were investigated by using nanoindentation produced with the tips of an AFM. Experiment results indicated the bending characteristics of the device and also the Young's modulus of the CNT embedded micro structure. Our objective was to determine the nano-scale mechanical properties and piezoresistivity of bulk carbon nanotubes using the local probe manipulation.
作者：
陈学东田文罡李小清渡边桂吾School of Mechanical Science and Engineering
Huazhong University of Science and Technology Wuhan 430074 China Dept. of Advanced Systems Control Engineering
Saga University Japanhe robot consists of a quadruped mechanism and two active dual-wheel casters possesses the advantages of wheeled and legged mechanism and can quickly move on the relatively plane ground with the wheeled mechanism and can walk on the extremely uneven terrain with the legged mechanism. The effectiveness of the motion design of the hybrid robot is iHustrated by simulation results.
The robot consists of a quadruped mechanism and two active dual-wheel casters possesses the advantages of wheeled and legged mechanism, and can quickly move on the relatively plane ground with the wheeled mechanism, a...
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The robot consists of a quadruped mechanism and two active dual-wheel casters possesses the advantages of wheeled and legged mechanism, and can quickly move on the relatively plane ground with the wheeled mechanism, and can walk on the extremely uneven terrain with the legged mechanism. The effectiveness of the motion design of the hybrid robot is iHustrated by simulation results.
For fault diagnosis, signal singularity and irregularity discontinuity fraction are very significant characteristics of signal. The discontinuity of output signal represents a system fault . In an angular measuring sy...
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For fault diagnosis, signal singularity and irregularity discontinuity fraction are very significant characteristics of signal. The discontinuity of output signal represents a system fault . In an angular measuring system, function transformer uses two D/A convertors, output circuit fault of a D/A convertor brings about discontinuity of one phase input voltage amplitude of inductosyn, results in a system error exceeding the allowable error and reduces the system accuracy. This is the reason why discontinuity is detected. Fourier transform has no resolution ability in angular domain, but wavelet can analyse signal in angular and frequency domains. So we decompose the error signal of angular measuring system by wavelet, detect the signal singularity at high frequency layer and find out the accurate position of it.
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