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Fundamental design tradeoffs in filtering, prediction, and smoothing

IEEE TRANSACTIONS ON AUTOMATIC control 1997年第9期42卷 1240-1251页

作者： Goodwin, GC Seron, MM Centre for Integrated Dynamics and Control Department of Electrical and Computer Engineering University of Newcastle NSW Australia Center for Control Engineering and Computation University of California Santa Barbara CA USA

This paper examines fundamental design tradeoffs that apply to all linear filtering, prediction, and smoothing problems, We introduce sensitivity functions that quantify filter performance, and we show that their frequency response satisfies constraints imposed by unstable poles and nonminimum phase zeros of the system, The constraints allow one to determine, a priori, whether or not a desired filter performance is attainable and how different arrangements of the measurement system influence the achievable performance.

关键词： Bode limits linear filtering performance limits

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A 2.4-GHz silicon-on-sapphire CMOS low-noise amplifier

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IEEE MICROWAVE AND GUIDED WAVE LETTERS 1997年第10期7卷 350-352页

作者： Johnson, RA Chang, CE delaHoussaye, PR Wood, ME Garcia, GA Asbeck, PM Lagnado, I IEEE Department of Electrical and Computer Engineering University of California Rockwell Science Center Naval Command Control and Ocean Surveillance Center RDT&E Division (NRaD)

A low-noise amplifier operating at 2.4 GHz has been fabricated with MOSFET's in silicon-on-sapphire technology, The amplifier has a 2.8-dB noise figure, IO-dB gain, and 14-dBm output referred IP3 with 14-mW power ... 详细信息

关键词： microwave FET amplifiers noise MMIC's

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Interlaced systems and recursive designs for global stabilization 4

Interlaced systems and recursive designs for global stabiliz...

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4th European control Conference, ECC 1997

作者： Sepulchre, R. Janković, M. Kokotović, P.V. Universite Catholique de Louvain Av. G. Lemaitre 4 Louvain-La-NeuveB1348 Belgium Ford Scientific Research Laboratories P.O. Box 2053 DearbornMI48121 United States Center for Control Engineering and Computation Dept. of Electrical and Computer Engineering University of California Santa BarbaraCA93106 United States

ISBN: (纸本)9783952426906

Interlaced systems constitute a class of systems only characterized by the zero entries of their matrix configuration and a local stabilizability condition. All these systems are globally stabilizable by a recursive design procedure which combines steps of backstepping and forwarding. When a nonlinear system misses this structural characterization, other types of conditions (sign, growth) are needed to ensure global stabilization.

关键词： Design

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Evolutionary fuzzy speed regulation for a DC motor

Evolutionary fuzzy speed regulation for a DC motor

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Southeastern Symposium on System Theory

作者： M.-R. Akbarzadeh-T Y.T.K. Feerouzbakhsh B. Feerouzbakhsh NASA Center For Autonomous Control Engineering Electrical Engineering and Computer Engineering Building University of New Mexico Albuquerque NM USA

Fuzzy logic is a powerful tool in control of systems with ill-defined, inaccurate or unknown mathematical models. In classical applications of fuzzy logic, however, there is a great dependency on proper expert knowledge acquisition. The authors remove that dependency by using a genetic algorithm (GA) to automatically determine parameters of fuzzy rule sets such as membership functions. This approach differs from conventional applications of GA-fuzzy knowledge development in that expert knowledge is incorporated in creating an initial highly fit population while allowing for randomness among members of the population for diversity. This method is useful for search in GA-hard landscapes and is successfully applied to speed regulation of a DC motor. It is shown that the presented method improves upon the initial fuzzy knowledge-base and significantly outperforms classical PID response.

关键词： DC motors Fuzzy control Fuzzy logic Fuzzy sets Three-term control Genetic algorithms Velocity control NASA control engineering Power engineering computing

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Reusable launch vehicle control in sliding modes

Reusable launch vehicle control in sliding modes

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Guidance, Navigation, and control Conference, 1997

作者： Shtessel, Yuri Tournes, Christian Krupp, Don Electrical and Computer Engineering Department University of Alabama in Huntsville HuntsvilleAL35899 United States Guidance and Control Systems Division NASA Marshall Space Flight Center MSFC AL35812 United States

control of a reusable launch vehicle (RLV) is considered in sliding modes. The sliding mode controllers are designed for the RLV in two operational modes: re-entry (descending) mode and launch (ascending) mode. The decentralized sliding mode controllers are designed to guarantee robust de-coupled asymptotic tracking of the Euler angles’ reference profiles upon the RLV model uncertainties and external disturbances. The angular rates command vector is formed in the outer loop in order to provide an asymptotic tracking of the Euler angles’ reference profiles. This command vector is tracked in the internal loop via the smoothed sliding mode controllers. Effectiveness of the designed sliding mode controllers is confirmed via computer simulations of a vertical- takeoff, horizontal-landing wing-body single-stage RLV studied at NASA Marshall Space Flight center. © 1997 by the American Institute of Aeronautics and Astronautics, Inc. All rights reserved.

关键词： Uncertainty analysis

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Real time control of a direct drive motor by a learning neuro-fuzzy controller

Real time control of a direct drive motor by a learning neur...

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IEEE International Conference on Systems, Man and Cybernetics

作者： K.K. Kumbla M. Jamshidi NASA Center for Autonomous Control Engineering Department of Electrical and Computer Engineering University of New Mexico Albuquerque NM USA

A neuro-fuzzy controller is presented which uses neural networks to modify the parameters of an adaptive fuzzy logic controller. The adaptiveness of the fuzzy controller is derived from a rule generation mechanism and changing the scaling factor or the shape of the membership functions. The neural network functions as a classifier of the system's temporal responses. A multilayer perceptron is used to classify the temporal response of the system into different patterns. Depending on the type of pattern such as "response with overshoot", "damped response", "oscillating response", etc. the scaling factor of the input and output membership functions are adjusted to make the system respond in a desired manner. The rule generation mechanism also utilizes the temporal response of the system to evaluate new fuzzy rules. The non-redundant rules are appended to the existing rule base during the tuning cycles. This controller architecture is used in real-time to control a direct drive motor. The control system hardware utilizes a digital signal processor and a PC to implement the controller architecture. Experimental results are illustrated.

关键词： Neural networks Shape control control systems Programmable control Adaptive control Fuzzy logic Fuzzy control Multilayer perceptrons Fuzzy systems Hardware

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Neural network based identification of robot dynamics used for neuro-fuzzy controller

Neural network based identification of robot dynamics used f...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： K.K. Kumbla M. Jamshidi NASA Center for Autonomous Control Engineering Department of Electrical and Computer Engineering University of New Mexico Albuquerque NM USA

A technique of identifying the dynamics of a robotics system using neural network is presented. The identified model is used by a fuzzy controller to evaluate the range of the control variables and also the performance of the adaptive control laws on the identified model. An overview of the neuro-fuzzy control architecture is also discussed. This architecture uses two neural networks, one which identifies the system dynamics and another classifies the temporal response of the robotic system. The information from the neural networks is used to make suitable adjustments in the parameter of the fuzzy controller. This paper however concentrates on the theory and operation of identifying the dynamics of a Adept-Two industrial robot. Simulation results are presented.

关键词： Neural networks Robots Fuzzy control Fuzzy neural networks Automatic control Adaptive control System identification control systems NASA Electric variables control

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Planar photoelastic effect for rf photonics system 8

Planar photoelastic effect for rf photonics system

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Optical Technology for Microwave Applications VIII 1997

作者： Liu, Q.Z. Chen, W.X. Weistand, R.B. Guan, Z.F. Xing, Q.J. Jiang, H. Pappert, S.A. Zappe, H.P. Lau, S.S. Yu, P.K.L. Department of Electrical and Computer Engineering University of California San Diego San DiegoCA92093-0407 United States Naval Command Control and Ocean Surveillance Center United States Paul Scherrer Institute Zurich Switzerland Zurich8048 Switzerland

Planar photoelastic effect on compound semiconductor structures has been investigated for integrated optical transmitter in rf photonics system. While our prior works emphasized the investigation of low-loss photoelastic waveguide, photoelastic waveguide modulator, and photoelastic optical splitter, the present work focuses on the attainment of high performance laser which employs the photoelastic effect for waveguiding. Planar separate-confinement, doubleheterostructure, single-quantum-well photoelastic GaAs/A1GaAs lasers have been fabricated using WNi stressors for waveguiding and ion implantation for isolation. Even without bonded on heat-sinks, these planar photoelastic lasers operate continuous wave at room temperature. The lowest threshold is 29 mA for a cavity length of 178 jim and a stressor width of 5tim. The main waveguiding mechanism of the photoelastic lasers is determined to be weak index-guiding with the beam waist in the junction plane measured at 10 jim behind the end-facet. © 1997 Proceedings of SPIE - The International Society for Optical engineering. All rights reserved.

关键词： Gallium arsenide

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Evolutionary Fuzzy control of a Flexible-Link

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Intelligent Automation and Soft Computing 1997年第1期3卷 77-88页

作者： Akbarzadeh-T., M.-R. Jamshidi, M. NASA Center for Autonomous Control Engineering Electrical Engineering and Computer Engineering Building University of New Mexico Albuquerque NM 87131 United States

In recent years, evolution based knowledge optimization has gained a great deal of popularity due to its inherent ability in efficient and parallel search of complex and multi-modal landscapes. Application of Genetic Algorithms (GA) to knowledge enhancement involves several aspects. First is how to code a string to represent all the necessary degrees of freedom for search in the fuzzy knowledge domain. The second aspect is how to incorporate existing expert knowledge into the GA optimising algorithm, and in general, how to take advantage of several experts' opinions in creation of an initial population. Conventional applications of GA Fuzzy suggest using a random initial population. However, it is intuitively clear that any search routine could converge faster if starting points are good solutions. In this article, a methodology is illustrated which incorporates expert knowledge in creating an initial population while allowing for randomness among members of the population for diversity. Furthermore, the methodology is applied to step response optimization of a flexible link feedback control system. Various aspects of real time implementation of such system are discussed. © 1997 Taylor & Francis Group, LLC.

关键词： Flexible robots Fuzzy control GA fuzzy systems Genetic algorithms Real-time control

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Robust control of cupola iron furnaces

Robust control of cupola iron furnaces

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American control Conference (ACC)

作者： M.A. Abdelrahman K.L. Moore Electrical and Computer Engineering Department Tennessee Technological University Cookeville TN USA Measurement and Control Engineering Research Center Idaho State University College of Engineering Pocatello ID USA

We present the results of a continuing effort towards the introduction of automatic control to the operation of cupola iron furnaces. The cupola furnace has played an important role in the foundry industry since its invention in 1794. The main aim of this research is to improve the operational efficiency and performance of the cupola furnace. A lumped model for the cupola is used for the controller design. The controller is divided into three parts. A feedforward controller is used to decouple the model into delayed and undelayed dynamics. A robust controller is designed for the delayed dynamics of the model based upon a combination of H/sub /spl infin// control and a Smith predictor. The controller for the undelayed portion of the model is designed using an LQR procedure.

关键词： Robust control Iron Furnaces Foundries Temperature control Delay Electric variables measurement control engineering Educational institutions Automatic control

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