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IEEE International Conference on Electro-Information Technology

作者： Jacob N. Allen Hoda S. Abdel-Aty-Zohdy Robert L. Ewing Microelectronics System Design Laboratory Department of Electrical and Computer Engineering Oakland University Rochester Hills MI USA Air Force Research Laboratory OH USA

Rapid HDL is a hardware definition language developed in C# for the Microsoft .Net platform. Rapid HDL unifies digital FPGA hardware development and co-software integration. Hardware is scripted using reusable software objects, communication between hardware and software is automatic, and synthesis is automated using a free tool chain. Rapid HDL represents 18,000 lines of code and is freely available under the MIT license.

关键词： Hardware design languages Software libraries Testing Licenses microelectronics Force sensors Field programmable gate arrays Software reusability Software tools High level languages

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Development of a 6-axis robotic arm controller implemented on a low-cost microcontroller

Development of a 6-axis robotic arm controller implemented o...

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International Conference on electrical engineering/Electronics, Computer, Telecommunications and Information Technology, ECTI-CON

作者： Agus Bejo Wanchalerm Pora Hiroaki Kunieda Embedded System and IC Design Research Laboratory Department of Electrical Engineering Faculty of Engineering Chulalongkom University Thailand Kunieda-Isshiki Laboratory Department of Communication and Integrated Systems Graduate School of Science and Engineering Tokyo Institute of Technology Japan

This paper presents a case study of development of a 6-axis robotic arm controller. The robot is powered by a hydraulic pump. The position of each axis can be derived from its potentiometer voltage. At each and every axis, a servo-valve is employed to control a servo motor. Its relative velocity is related to the servo-valve input. With 2 nd order PID controller, a micro-controller commands movements of all axes. The PID inputs are the six voltages from potentiometers and its outputs are the six DC voltages, which command the six servo-valves. A trajectory file is generated by solving the inverse kinematics problem with some (angular to digital value) conversions. A special case; closed-form calculation is developed to solve kinematics problem. With some constraints it only yields one solution. Experiments show that robot follow the given trajectory with acceptable errors.

关键词： Robot control Microcontrollers Robot kinematics Control systems Potentiometers Communication system control Voltage Servomechanisms Servomotors Service robots

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Bio-Inspired Adaptive Integrated Information Processing

Bio-Inspired Adaptive Integrated Information Processing

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IEEE National Conference on Aerospace and Electronics (NAECON)

作者： Hoda S. Abdel-Aty-Zohdy Microelectronics Systems Design Laboratory Department of Electrical and Computer Engineering Oakland University Rochester MI USA

Biological brains are dramatically more effective in dealing with real-world adaptive information processes and decisions than most advanced computers. Advanced computers can utilize the discipline of classical signal processing whereby providing theoretical mathematical and statistical approaches for information processing, and with the vision of bio-inspired adaptive processing are evolving into neuromorphic integrated sensory processing systems. Numerous MISO (multi-input, single output) sensory applications demand reliable and effective information processing which, at an initial stage may be addressed by solving the key problems of advanced computing platforms, which are: i-massive parallelism; ii-low power consumption of massively large systems; iii-intelligent systems that learn from observations and perform better on the next run; iv-integrated systems for embedded feasibility; and v-systems that adapt to the environment. Thus, our Adaptive Integrated Information Processing (AIIP) approaches, presented in this paper. Two AIIP systems are presented: Neural networks with synaptic plasticity, as our Spiking Neural Networks (SNNs), with up to one million inputs, for chemical sensing and detection; and Adaptive Recurrent Dynamic Neural Networks (ARDNNs) for defect tracking, reliable system deployment, and prognosis for telecommunication and similar applications. Further-our presented AIIP systems may provide a viable solution to offering powerful modulation schemes and transmission rates far beyond current possible communications systems.

关键词： Information processing Power system reliability Biological neural networks Neural networks Recurrent neural networks Biology computing Computer vision Adaptive signal processing Biomedical signal processing Neuromorphics

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Modeling and simulation for on-chip power grid networks by locally dominant krylov subspace method

Modeling and simulation for on-chip power grid networks by l...

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2008 International Conference on Computer-Aided design, ICCAD

作者： Yan, Boyuan Tan, Sheldon X.-D. Chen, Gengsheng Wu, Lifeng Department of Electrical Engineering University of California Riverside CA 92521 United States ASIC and System State-Key-Lab Microelectronics Dept. Fudan Univeristy Shanghai 200433 China Cadence Design Systems Inc. San Jose CA 95134 United States

ISBN: (纸本)9781424428205

Fast analysis of power grid networks has been a challenging problem for many years. The huge size renders circuit simulation inefficient and the large number of inputs further limits the application of existing Krylov-subspace macromodeling algorithms. However, strong locality has been observed that two nodes geometrically far have very small electrical impact on each other because of the exponential attenuation. However, no systematic approaches have been proposed to exploit such locality. In this paper, we propose a novel modeling and simulation scheme, which can automatically identify the dominant inputs for a given observed node in a power grid network. This enables us to build extremely compact models by projecting the system onto the locally dominant Krylov subspace corresponding to those dominant inputs only. The resulting simulation can be very fast with the compact models if we only need to view the responses of a few nodes under many different inputs. Experimental results show that the proposed method can have at least 100X speedup over SPICE-like simulations on a number of large power grid networks up to 1M nodes.

关键词： Circuit simulation

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Fractional-Order Signal Processing using a Polymer-Electrolyte Transistor

Fractional-Order Signal Processing using a Polymer-Electroly...

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51st Midwest Symposium on Circuits and systems (MWSCAS 2008), vol.2

作者： Robert L. Ewing Hoda S. Abdel-Aty-Zohdy Michael C. Hollenbeck Kenneth S. Stevens Information Directorate US Air Force Research Laboratory OH USA Microelectronics System Design Laboratory Department of Electrical and Systems Engineering Oakland University Rochester MI USA Department of Electrical and Computer Engineering University of Utah Salt Lake UT USA

Fractional-order systems have applications in the areas of Flight Control, Robotics, Missile Guidance, Control of Structural Vibrations of Space Platforms and Sensor Technology. Fractional-order transfer functions can characterize complex nonlinear dynamics with many fewer parameters than integer-order functions. This paper addresses the use of a polymer-electrolyte transistor (PET) for use in implementating fractional-order algorithms for signal processing. The PET's advantage over the conventional RC and RL circuits is that it can be both functionally scaled and varied for dynamic fractional-order parameter controllability.

关键词： Fractional-Order Signal Processing Polymer-electrolyte transistor Acid/base chemistry Diffusion Electrokinetic flow

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Modeling and simulation for on-chip power grid networks by locally dominant Krylov subspace method 08

Modeling and simulation for on-chip power grid networks by l...

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IEEE International Conference on Computer-Aided design

作者： Boyuan Yan Sheldon X.-D. Tan Gengsheng Chen Lifeng Wu Department of Electrical Engineering University of California Riverside CA USA ASIC & System State-Key-Lab MicroElectronics Department Fudan University Shanghai China Cadence Design Systems Inc. San Jose CA USA

ISBN: (纸本)9781424428205

关键词： Network-on-a-chip Power grids Power system modeling Transfer functions Attenuation Filters system-on-a-chip Application specific integrated circuits microelectronics Circuit analysis

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Annual business and news:: Beginning the 31st year of the Journal of Guidance, Control, and Dynamics

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JOURNAL OF GUIDANCE CONTROL AND DYNAMICS 2008年第1期31卷 1-1页

作者： Schmidt, George T. Aeronautics and Astronautics Massachusetts Institute of Technology (MIT) AIAA Institute of Electrical and Electronics Engineers Russian Federation Academy of Navigation and Motion Control Department of Mechanical and Aerospace Engineering and Engineering Mechanics University of Missouri-Rolla(UMR) Lockheed Electronics Company Center for Space Research University of Texas Austin United States Wright Laboratory Eglin Air Force Base UMR AIAA Guidance Navigation and Control Technical Committee American Automatic Control Council Lockheed Martin Aeronautics Company Palmdale CA United States C4ISR and Unmanned Air Vehicle (UAV) Programs for Air Vehicle Sciences and Systems Accreditation Board Engineering and Technology Inc./Aeronautical National Technical Committee on Guidance Navigation and Control Department of Mechanical and Aerospace Engineering University at Buffalo State University of New York (SUNY) AIAA Technical Committee on GN and C Air Vehicles Directorate Air Force Research Laboratory (AFRL) Wright-Patterson Air Force Base Space Access and Hypersonic Vehicle Guidance and Control Group Control Science Center of Excellence AFRL AIAA Technical Committee on Guidance Navigation and Control Department of Mechanical and Aeronautical Engineering University of California (UC) Davis United States Boeing Company Modernized Flight Control System for the Apache Longbow AIAA Institute of Electrical and Electronics Engineers AHS Jet Propulsion Laboratory California Institute of Technology Boeing Company Flight Sciences and Advanced Design Group Guidance Navigation and Control (GN and C) Systems Engineer Distributed Space Systems NASA Goddard Space Flight Center (GSFC) AIAA GN and C Technical Committee Department of Aerospace Engineering and Engineering Mechanics University of Texas Austin United States Institute of Navigation American Astronautical Society AIAA Guidance Navigation (GN and C) and Control Technical Committee Department of Aerospace Engineering Iowa State University Iowa

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Biologically-Based Signal Processing Chips with Emphasis on Telecommunication Defect Tracking and Reliability Estimation

Biologically-Based Signal Processing Chips with Emphasis on ...

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IEEE Pacific Rim Conference on Communications, Computers and Signal Processing

作者： Hoda S Abdel-Aty-Zohdy Microelectronics System Design Laboratory Department of Electrical and Computer Engineering Oakland University Rochester MI USA

This paper provides observations and motivations to mimic biological information processing. Alternative bio-inspired systems definitions, basics, approaches, algorithms, and chip implementations will be illustrated to offer a base of choice for bio-based Intelligent Information Processing (IIP) systems. Hybrid biological and bio-based IIP are briefly presented. Two specific applications follow with embedded bio-based systems: Bio-chemical sensing and detection E-nose; and Track improvements In the reliability of the software used in telecommunication network deployments. The biologically-based processing discoveries gleaned from observing the spikes in the brain activity of monkeys, introduced the concept of plasticity in synapses used in our embedded Spiking Neural Network (SNN) system for the E-Nose The mathematical construct of a defect tracking classifier is nonlinear, and the event to be recognized involves a sequentially varying or non-stationary phenomenon for telecommunication defect tracking and reliability estimation. Thus, Adaptive Recurrent Dynamic Neural Network (ARDNN) system using wavelet function as the basis improved the failure event estimation of software defect tracking in telecommunications and reduced the error from 88% to L25-8%.

关键词： Biomedical signal processing Signal processing algorithms Information processing Telecommunication network reliability Biological neural networks Application software Embedded software Brain Nonlinear dynamical systems Neural networks

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OPTIMAL CONTROL FOR TWO-DIMENSIONAL LINEAR systems WITH VARIABLE COEFFICIENTS

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Asian Journal of Control 2008年第4期1卷

作者： Jimshone Li Jason Sheng-Hong Tsai Leang-San Shieh Control System Laboratory Department of Electrical Engineering National Cheng Kung University Tainan 701 Taiwan R.O.C. Jim-Shone Li was born in Taiwan R. O.C. on April 20 1967. He received B.S. and M.S. degrees in Electrical Engineering from the Chung-Cheng Institute of Technology Taoyuan Taiwan R.O.C. in 1989 and 1993 respectively. He is currently a Ph.D. student at National Cheng-Kung University Tainan Taiwan R.O.C. His research interests include analysis and design of multidimensional systems and nonlinear system control. Department of Electrical and Computer Engineering University of Houston Houston TX 77004-4793 U.S.A.

An optimal control method for two-dimensional (2-D) linear systems with variable coefficients and free boundary conditions in Roesser's model is proposed in this paper. Based on Roesser's model, an equivalent general 1-D model of the 2-D system is presented, and the problem of minimizing a 2-D linear quadratic (LQ) cost function is solved for the case where complete state information is available. The solution is obtained by using the proposed dynamic programming in 1-D descriptor form to solve the Riccati equation and then arriving at the optimal control law and minimum cost. The proposed control methodology can be applied to discrete-time models of systems described by partial differential equations and can also be used in the field of signal processing.

关键词： Two-dimensional system optimal control Roesser's model Riccati equation

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Bio-Inspired Integrated Chips for Telecommunications S/W Defect-Tracking

Bio-Inspired Integrated Chips for Telecommunications S/W Def...

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IEEE International Symposium on Signal Processing and Information Technology (ISSPIT)

作者： Hoda S Abdel-Aty-Zohdy Mostafa Hashem Sherif Adam Smiarowski Brian Searing WPAFB/RITA Air Force Research Laboratory OH USA Microelectronics System Design Lab Electrical and Computer Engineering Department Oakland University Rochester MI USA Middletown NJ USA

Defect tracking is important in evaluating the reliability of the software used in telecommunication networks. Bio-inspired integrated approaches and embedded chips have been developed and implemented to track improvements in the software reliability. In this paper, the integrated model for the failure discovery during testing is combined with bio-inspired approaches using the recurrent dynamic neural network (RDNN) with parametric adjustments and wavelets as basis; and the adaptive parameters RDNN (ARDNN) where the criterion is to minimize the error in failure intensity estimation, subject to the model constraints. Simulation results favor our adaptive recurrent dynamic neural network, with reduced error from 88% to 1.25 –to- 8% based on the number of iterations in the training phase.. The ARDNN approach provides optimum solution to the dynamic problem at hand since it iterates on the shape of the wavelet basis and provide adequate recovery of the data in the form of piecewise linear differential.

关键词： Software testing Neural networks Telecommunication network reliability Recurrent neural networks Genetic algorithms Parameter estimation Biomedical signal processing Information technology microelectronics Computer networks

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