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recursive System Identification Using Instrumental Variable Subspace Tracking

IFAC Proceedings Volumes 1997年第11期30卷 1579-1584页

作者： Tony Gustafsson Signal Processing Group Department of Applied Electronics Chalmers University of Technology S-412 96 Gothenburg Sweden

In this paper a recursive instrumental variable (IV) based subspace identification algorithm is proposed. The basic idea of the algorithm is to utilize the close relationship with sensor array signal processing. Utilizing this relationship, an IV based subspace tracking algorithm originally developed for direction of arrival tracking is applied to track the subspace spanned by the observability matrix. The main features of the proposed algorithm are, a) a relatively low computational complexity, and b) the ability to handle colored disturbances that are mutually correlated.

关键词： recursive algorithms Subspace methods Identification Tracking

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A recursive Newton type algorithm for digital frequency relaying

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ELECTRIC POWER SYSTEMS RESEARCH 1996年第1期36卷 67-72页

作者： Terzija, VV Djuric, MB Jeremic, NZ Faculty of Electrical Engineering University of Belgrade Bulevar Revolucije 73 PO Box 816 11001 Belgrade Yugoslavia

This paper presents a new recursive Newton type algorithm devoted to frequency relaying. The algorithm is designed from the nonrecursive Newton type algorithm and recursive least error squares algorithm. The frequency is estimated from the uniformly sampled voltage signal. The algorithm testing based on computer simulated and experimentally obtained data record processing confirmed the good features of the algorithm developed. Due to its computational efficiency, the algorithm is suitable for various real-time power system measurement applications.

关键词： frequency relaying data processing recursive algorithms

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Dynamic simulation and neural network compliance control of an intelligent forging center

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JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS 1996年第1期17卷 81-99页

作者： Lilly, KW Melligeri, AS STATDESIGN INC DEARBORN MI 48120 USA

Automation of forging processes is important for both safety and efficiency in today's advanced manufacturing operations. This work supports the development of an Intelligent Open Die Forging System which will integrate state-of-the-arc modelling techniques, automatic die selection and sequencing, full system dynamic simulation, automatic machine programming and coordination, and sensor-based process control to enable the production of more general and complex workpiece geometries than are achievable using current forging methods. Effective automation of this open die forging system requires the coordination and control of the major system components: press, robot, and furnace. In particular, forces exerted on the robot through its manipulation of the workpiece during forging must be minimized to avoid damage to the manipulator mechanism. In this paper, the application of neural networks for compliance control of the forging robot to minimize these forces is investigated. Effectiveness ol the neural network-based compliance control module is evaluated through a full dynamic system simulation, which will later form a central part of the complete Intelligent Forging System. Dynamic simulation of the robot is achieved using an efficient O(N) recursive algorithm, while material flow of the workpiece is modeled with a finite element approach. Simulation and timing results for the complete processing system for a specific open die forging example are presented.

关键词： forging automation compliance control neural networks dynamic simulation finite element models recursive algorithms intelligent manufacturing

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On the interrelation of almost sure invariance principles for certain stochastic adaptive algorithms and for partial sums of random variables

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JOURNAL OF THEORETICAL PROBABILITY 1996年第4期9卷 811-840页

作者： Kouritzin, MA University of Minnesota

Since the novel work of Berkes and Philipp((3)) much effort has been focused on establishing almost sure invariance principles of the form [GRAPHICS] where {x(i), i=1, 2, 3,...} is a sequence of random vectors and {X(t), t greater than or equal to 0} is a Brownian motion. In this note, we show that if {A(k), k=1, 2, 3,...} and {b(k), k=1, 2, 3,...} are processes satisfying almost-sure bounds analogous to Eq. (1), (where {X(t), t greater than or equal to 0} could be a more general Gauss-Markov process) then {h(k), k= 1, 2, 3,...}, the solution of the stochastic approximation or adaptive filtering algorithm h(k+1)=h(k)+1/k(b(k)-A(k)h(k)) for k=1,23,... (2) also satisfies an almost sure invariance principle of the same type.

关键词： almost sure invariance principles stochastic approximation recursive algorithms dependent random variables

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On the convergence of linear stochastic approximation procedures

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IEEE TRANSACTIONS ON INFORMATION THEORY 1996年第4期42卷 1305-1309页

作者： Kouritzin, MA Institute for Mathematics and Its Applications University of Minnesota Minneapolis MN USA

Many stochastic approximation procedures result in a stochastic algorithm of the form (1) h(k+1) = h(k) + 1/k (b(k) - A(k)h(k)), for all k = 1, 2, 3,.... Here, {b(k), k = 1, 2, 3,...} is a R(d)-valued process, {A(k), k = 1, 2, 3,...} is a symmetric, positive semidefinite Re-dxd-valued process, and {h(k), k = 1, 2, 3,...} is a sequence of stochastic estimates which hopefully converges to (2) h corresponds to [(N - infinity)lim 1/N (k = 1)Sigma(N) EA(k)](-1).{(N --> infinity)lim 1/N (k = 1)Sigma(N) Eb(k)} (assuming everything here Is well defined). In this correspondence, we give an elementary proof which relates the almost sure convergence of {h(k), k = 1, 2, 3,...} to strong laws of large numbers for {b(k), k = 1, 2, 3,...} and {A(k), k = 1, 2, 3,...}.

关键词： almost sure convergence stochastic approximation adaptive filtering recursive algorithms dependent random variables Robbins-Monro process

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Application of simplified line searches in the design of adaptive envelope-constrained filters

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IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-FUNDAMENTAL THEORY AND APPLICATIONS 1996年第10期43卷 854-857页

作者： Zheng, WX Department of Mathematics University of Western Sydney Nepean NSW Canada

Envelope-constrained (EC) filtering is to design a finite impulse response filter such that the output of the filter is guaranteed to lie within a prescribed output pulse mask with respect to a given input pulse. The standard unconstrained least mean squares (LMS) or recursive least squares (RLS) algorithms are not applicable to this kind of adaptive filtering problem coupled with inequality constraints. A new type of recursive algorithms were proposed recently for designing an adaptive EC filter, and the corresponding convergence properties were established. In this paper, it is shown that faster convergence can be achieved by incorporating a simplified line search into the developed recursive algorithms. The modified recursive algorithms are very efficient, and very simple to implement.

关键词： recursive algorithms input pulse Levamisole Infinite impulse response filters Self tuning Filters learning management system inequality constraint Dosage Form Not Applicable line retrieval

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Computing minimum with primitive recursion over lists

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THEORETICAL COMPUTER SCIENCE 1996年第1-2期163卷 269-276页

作者： Fredholm, D UNIV STOCKHOLM DEPT MATH S-10691 STOCKHOLM SWEDEN

We show that there is no primitive recursive algorithm over the natural numbers and lists of natural numbers that computes the minimum of two numbers in time O(min), in call-by-value evaluation order. This is in contr... 详细信息

关键词： recursive algorithms LIST Natural number Primitive

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Parametric System Identification in the Presence of Uncertainty with Model Validation Constraints

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IFAC Proceedings Volumes 1996年第1期29卷 4052-4056页

作者： Er-Wei Bai Roberto Tempo Krishan Nagpal Dept. of Electrical and Electronic Engineering Hong Kong University of Science and Technology on leave from Dept. of Elec. and Comp. Engineering University of Iowa Iowa City Iowa 52242 USA CENS-CNR Politecnico di Torino 10129 Torino Italy Dept of Electrical Engineering and Computer Science University of Michigan

This paper presents two recursive algorithms for parametric identification in the presence of both, noise and model uncertainties. The estimates provided by these algorithms are not invalidated by the observed input-o... 详细信息

关键词： Parametric System Identification Uncertainty Model Validation recursive algorithms

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A Robust and recursive Identification Method for the Hammerstein Model

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IFAC Proceedings Volumes 1996年第1期29卷 4374-4379页

作者： M. Boutayeb H. Rafaralahy M. Darouach CRAN CNRS URA 821 University Henri Poincaré - Nancy I 186 rue de Lorraine 54400 Cosnes et Romain FRANCE. Tel : (33) - 82 - 25 - 91 - 49. Fax: (33) - 82 - 23 - 97 - 93.

In this note, a robust identification method of non linear systems using the Hammerstein model is presented. The main property of the proposed approach is that parameters of the linear and nonlinear parts are estimated in a recursive way while the global convergence is guaranted. The proposed method consists first to transform the non linear representation into an input-output model linear in parameters, after, a regular transformation based on the pseudo-inverse technique allows us to estimate in the least squares sense parameters vector of the original realization. For the case of correlated noise, to model measurement disturbances, we propose a simple technique based on the pseudo-linear regression method and we investigate all parameters dependencies to obtain a consistent solution. Sufficient conditions for global convergence are derived. Two numerical examples with different correlation structures and different Signal to Noise Ratio values are provided.

关键词： Robust estimation recursive algorithms Nonlinear models Coloured noise Convergence analysis

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DIVIDE-AND-CONQUER ORTHOGONALITY PRINCIPLE FOR PARALLEL OPTIMIZATIONS IN TSP

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NEUROCOMPUTING 1995年第3期8卷 249-261页

作者： SZU, H FOO, S FLORIDA STATE UNIV FAMUCOLL ENGNDEPT ELECT ENGNTALLAHASSEEFL 32316 USN CTR SURFACE WARFAREDAHLGREN DIVWHITE OAKMD 20309

A lossless divide-and-conquer (D&C) principle, implemented via an orthogonality projection, is described and illustrated with a recursive solution of the Traveling Salesman Problem (TSP), which is executable on a massively parallel and distributed computer. The lossless D&C principle guides us to look near the desirable boundary and to seek for a characteristic vector V (e.g. displacement vector in TSP) such that V approximate to A + B where two resultant vectors A and B (located one in each sub-domains to be divided) should be orthogonal to each other having no cross product terms, i.e. (A, B) = (B, A) = 0. In the case of parallel computing this goal amounts to minimum communication cost among processors. Then the global optimization of the whole domain: Min. \\V\\(2) = Min. \\A\\(2) + Min. \\B\\(2) can be losslessly divided into two sub-domains that each can seek its own optimized solution separately (by two separate sets of processors without inter-communication during processing). Such a theorem of orthogonal division error (ODE) for lossless D&C is proved, and the orthogonal projection is constructed for solving a large-scale TSP explicitly.

关键词： NONCONVEX OPTIMIZATION SIMULATED ANNEALING TRAVELING SALESMAN PROBLEM LOSSLESS DIVIDE-AND-CONQUER BOUNDARY RESULTANT VECTORS ORTHOGONAL PROJECTIONS recursive algorithms

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