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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： S.C.A. Thomopoulos I.N.M. Papadakis Decision and Control Systems Laboratory Department of Electrical and Computer Engineering Pennsylvania State University University Park PA USA

A modified output error method (MOEM) for model reference adaptive control (MRAC) and identification (MRAI) is introduced. The regressors are properly chosen so that the open-loop system can be compactly expressed as a stable system with an input linear with respect to the unknown plant parameters. The output error satisfies a constructible stable filtered equation. The method does not require any strictly positive real or arbitrary stable filterings, and the uncertainty on the magnitude of the high-frequency gain of the plant does not result in an overparameterization of the identifier. Sufficient conditions on the reference input under which the parameter and output errors converge exponentially to zero are also given.< >

关键词： Adaptive control Error correction Polynomials computer errors Open loop systems Frequency Transfer functions Convergence control system synthesis Laboratories

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CAE Tools for Nonlinear systems Analysis and Design Based on Sinusoidal-Input Describing Functions

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IFAC Proceedings Volumes 1991年第4期24卷 89-94页

作者： J.R. O'Donnell J.H. Taylor Department of Electrical Computer and Systems Engineering Rensselaer Polytechnic Institute Troy NY 12180-3590 USA Control Systems Laboratory General Electric Corporate Research and Development P. O. Box 8 Schenectady NY 12301 USA

We report on recent progress in the development of a computer-aided engineering (CAE) environment for nonlinear control system analysis and design based on sinusoidal-input describing function (SIDF) methods. Several major additions have been made to our nonlinear controls CAE software: ACSL macros were developed to allow the generation of SIDF models of nonlinear plants in a manner analogous to that of the SIMNON-based software developed earlier, and MATLAB routines were developed for the analysis of these models and for the design of general nonlinear controllers based on them. This software provides an integrated tool set for treating very general nonlinear systems with no restrictions on system order, number of nonlinearities, configuration, or nonlinearity type. Based on the new software presented here, the use of SIDF-based nonlinear control system analysis and design methods is substantially easier to carry out and more powerful than before

关键词： Nonlinear control systems describing functions control system design computeraided design computer software

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Fundamentals of control-oriented system identification and their application for identification in H∞

Fundamentals of control-oriented system identification and t...

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American control Conference (ACC)

作者： A. J. Helmicki C. A. Jacobson C. N. Nett Department of Electrical and Computer Engineering University of Cincinnati Cincinnati OH USA Department of Electrical and Computer Engineering Northeastern University Boston MA USA School of Aerospace Engineering Laboratory for Identification and Control of Complex Highly Uncertain Systems Georgia Institute of Technology Atlanta GA USA

This paper examines the system identification problem from the standpoint of control system design. Noting first that nearly all robust control design methods require explicit worst-case/deterministic bounds on the existing plant uncertainty, it is argued that the class of system identification methods which are inherently compatible with robust control design methods-or control-oriented is a subset of the class of system identification methods which yield an explicit worst-case/deterministic bound on the resulting identification error. An abstract theoretical framework for control-oriented system identification is then developed. This framework is inherently worst-case/deterministic in nature, and makes precise such notions as identification error, algorithm convergence, and algorithm optimality from a worst-case/deterministic standpoint. Finally, the abstract theoretical framework is utilized to formulate and solve two related control-oriented system identification problems for stable, linear, shift-invariant, distributed parameter plants. In each of these problems the assumed apriori information is minimal, consisting only of a lower bound on the relative stability of the plant, an upper bound on a certain gain associated with the plant, and an upper bound on the noise level. In neither case are any assumptions made concerning the structure of either the plant (i.e., dynamic order, relative order, etc.) or the noise (i.e., zero-mean, etc.). The first of these problems involves identification of a point sample of the plant frequency response from a noisy, finite, output time series obtained in response to an applied sinusoidal input with frequency corresponding to the frequency point of interest.

关键词： control systems System identification Robust control Design methodology Upper bound Frequency Uncertainty Error correction Convergence Stability

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DIGNET: a self-organizing neural network for automatic pattern recognition and classification

DIGNET: a self-organizing neural network for automatic patte...

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IEEE Conference on Decision and control

作者： S.C.A. Thomopoulos D.K. Bougoulias Decision and Control Systems Laboratory Department of Electrical & Computer Engineering Pennsylvania State University University Park PA USA Information Proc. & Intell. System Laboratory Department of Electrical Engineering Southem Illinois University Carbondale IL USA

The authors present a self-organizing artificial neural network (ANN) that exhibits deterministically reliable behavior to noise interference when the noise does not exceed a specified level of tolerance. The complexity of the proposed ANN, called DIGNET, in terms of neuron requirements versus stored patterns, increases linearly with the number of stored patterns and their dimensionality. The self-organization of DIGNET is based on the idea of competitive generation and elimination of attraction wells in the pattern space. The same neural network can be used for both pattern recognition and classification.< >

关键词： Neural networks Pattern recognition Artificial neural networks Neurons Interference Vectors Laboratories Noise level Signal detection Automatic control

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Worst Case System Identification in l1: Optimal Algorithms and Error Bounds

Worst Case System Identification in l1: Optimal Algorithms a...

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American control Conference (ACC)

作者： C. A. Jacobson C. N. Nett Department of Electrical and Computer Engineering North Eastern University Boston MA USA Laboratory for Identification and Control of Complex Highly Uncertain Systems (LICCHUS) School Institute of Technology Georgia Institute of Technology Atlanta GA USA

This paper analyzes worst case identification of linear shift invariant systems with an l 1 error criterion. A characterization of optimal algorithms and intrinsic errors of identification is given. The application of this characterization is made to identification in l 1 . The assumed apriori information on the plant are bounds on the system gain and decay rate of the impulse response of the unknown system and the experimental data is assumed to be a finite set of corrupted impulse or step response samples of the systems. Comparisons are made with the H ∞ system identification problem. Comments on the l 1 identification of small signal models of smooth nonlinear discrete time systems are made.

关键词： System identification Robust control Convolution Jacobian matrices Algorithm design and analysis Signal processing Discrete time systems control system synthesis Nonlinear control systems Design methodology

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THE ESTIMATION OF GEOMETRY AND MOTION OF A SURFACE FROM IMAGE SEQUENCES BY MEANS OF LINEARIZATION OF A PARAMETRIC MODEL

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computer VISION GRAPHICS AND IMAGE PROCESSING 1990年第1期50卷 1-28页

作者： KORSTEN, MJ HOUKES, Z Control Systems and Computer Engineering Laboratory Faculty of Electrical Engineering University of Twente P.O. Box 217 7500AE Enschede The Netherlands

A method is given to estimate the geometry and motion of a moving body surface from image sequences. To this aim a parametric model of the surface is used, in order to reformulate the problem to one of parameter estimation. After linearization of the model standard linear estimation methods can be used to estimate the parameters. The main contribution of this paper is that a method is provided to perform the linearization without specifying the model. Therefore structure from motion estimation and nonrigid body motion estimation can be performed regardless of the model.

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Non-linear filtering to improve dexterity in spatial control

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Transactions of the Institute of Measurement & control 1990年第1期12卷 44-48页

作者： Bosman, D. Bakker, W. Faculty of Electrotechnology Control Systems and Computer Engineering Group Vision Laboratory University of Twente 7500 AE Enschede The Netherlands United States

Task-dependent response - eg, in instrument calibration, spatial positioning and the like - is a long nursed requirement: transition to the end state very fast, albeit imprecise, followed by slower but very accurate final action. The realisation, of course, is a non-linear filter which can take many levels of refinement. In this paper the analysis is presented of the most simple continuous type and it is shown that signal-dependent overshoot (associated with fast response) can be obtained using networks with strictly low-pass (non-negative) impulse response. © 1990, Sage Publications. All rights reserved.

关键词： adaptive dexterity Non-linear filter spatial control spreading

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An explicit model-matching approach to lateral-axis autopilot design

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IEEE control systems Magazine 1990年第4期10卷 22-28页

作者： K.D. Minto J.H. Chow J.W. Beseler GECorporate Research and Development Center Schenectady Control Systems Laboratory NY USA Electrical Systems and Computer Engineering Department Rensselaer Polytechnic Institute Troy NY USA

The application of a linear multivariable control law design methodology to an autopilot design for large transport aircraft is described. The design method is an explicit model-matching approach, whereby compensator parameters are tuned via a least-squares optimization approach to minimize the error between the desired and the actual closed-loop frequency responses. This method incorporates some recent theoretical advances, including controller parameterization and plant factorization, and has been implemented within the ISICLE software package, a MATLAB-based control design toolbox. A desirable feature of the ISICLE design software is the capability to constrain the compensator dynamic order and structure, issues motivated by the necessity for low complexity implementations in order to simplify gain scheduling and limit protection.< >

关键词： Mathematical model Design methodology Aircraft Aerospace control Design optimization Frequency Software packages computer languages control design Software design

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The Linear Constrained Regulation Problem for Discrete-Time systems

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IFAC Proceedings Volumes 1990年第8期23卷 321-326页

作者： G. Bitsoris M. Vassilaki Control Systems Laboratory Electrical Engineering Department. University of Patras 26500 Patras Greece AMBER S.A. Computer Systems P.D. Box 3500 Athens Greece

In this paper the Linear Constrained Regulation Problem for discrete-time systems is studied. The first part of the paper deals with the problem of existence of linear state-feedback control laws that transfer asymptotically to the origin all initial states belonging to a polyhedral subset of state space while linear state and control constraints are respected. Then an eigenstructure assignment technique is developed for derivation of a solution to this problem. The results presented in the paper are based on the properties of systems possessing polyedral positively invariant sets.

关键词： Constraint theory discrete time systems eigenvalue assignment, invariance linear systems stability

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Synthesis of Nonlinear controllers with Rate Feedback via Sinusoidal-Input Describing Function Methods

Synthesis of Nonlinear Controllers with Rate Feedback via Si...

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American control Conference (ACC)

作者： James H. Taylor James R. O'Donnell Control Systems Laboratory General Electric Corporate Research and Development Schenectady NY USA Department of Electrical Computer and Systems Engineering Rensselaer Polytechnic Institute Troy NY USA

In this paper, we report on recent advances in the design of fully nonlinear controllers for amplitude-sensitive nonlinear plants using sinusoidal-input describing function methods. This work includes the development of a new nonlinear controller synthesis approach that includes derivative action in an inner-loop feedback path (nonlinear rate feedback), and its application to a motor + load model with torque saturation and stiction. This approach is capable of treaing nonlinear systems of a very general nature, with no restrictions as to system order, number of nonlinearities, configuration, or nonlinearity type; additionally, the techniques can be generalized for the design of nonlinear controllers of different structures. The end result is a closed-loop nonlinear control system that is relatively insensitive to reference-input amplitude.

关键词： Feedback control system synthesis Nonlinear control systems Signal synthesis Three-term control Load modeling Nonlinear systems control systems Laboratories Research and development

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