The Instrumental Variable Method: A Practical Approach to Identification and System Parameter Estimation
IFAC Proceedings VolumesPublished 1 July 1985
Peter C. Young
Citations91
Generate an AI Snapshot to get a quick, structured summary of this paper.
Study Snapshot
ObjectiveStudy objective
MethodsResearch methodology
PopulationPopulation studied
Sample sizeSample sizes
OutcomesStudy outcomes here
ResultsStudy results comes here
LimitationsResearch study limitations comes here
A concise AI-generated summary of the paper will appear here once you click Generate AI Snapshot.
Abstract
The paper is intended as an introduction to the Instrumental Variable (IV) method for the identification and estimation of discrete-time, transfer function (TF) models for stochastic dynamic systems. Iterative and recursive-iterative versions of both the ordinary and refined (i.e. optimal) IV algorithms are discussed in relation to their implementation in the MICROCAPTAIN personal computer program package. The practical utility of the IV method is illustrated by a number of examples from the areas of environmental science and engineering. These examples show how procedures such as adaptive prefiltering and time-variable parameter estimation can be useful in practical terms
Keywords
Computer ScienceEngineering
Theory and Practice of Recursive Identification
4,008 Citations1983Lennart Ljung, Torsten Söderström
Methods of recursive identification deal with the problem of building mathematical models of signals and systems on-line, at the same time as data is being collected.
Journal of the Operational Research SocietyTime Series Analysis Forecasting and Control
1,792 Citations1971D. J. Bartholomew
AutomaticaAn instrumental variable method for real-time identification of a noisy process
405 Citations1970Peter C. Young
International Journal of ControlRefined instrumental variable methods of recursive time-series analysis Part III. Extensions
291 Citations1980Peter C. Young, Anthony J. Jakeman
The paper shows how the refined IV procedure can be extended in various important directions and how it can provide the basis for the synthesis of optimal generalized equation error (GEE) algorithms for a wide class of stochastic dynamic systems.
Recursive Estimation and Time-Series Analysis: An Introduction
262 Citations1984Peter Young
Journal of the Franklin InstituteIdentification and system parameter Estimation
219 Citations1975Rolf Isermann
AutomaticaAn instrumental variable method for model order identification
190 Citations1980Peter C. Young, Anthony J. Jakeman +1 more
The paper describes a simple instrumental variable method for identifying the structure of a wide class of time-series models that can be applied to single input-single output and multivariable systems using either discrete or continuous-time series models.
International Journal of ControlRefined instrumental variable methods of recursive time-series analysis Part I. Single input, single output systems
187 Citations1979Peter C. Young, Anthony J. Jakeman
The implementation of a recursive/iterative version of the refined IVAML algorithm for single input, single output systems is discussed in detail and the performance of the algorithm is evaluated by Monte-Carlo simulation analysis applied to five simulated stochastic systems.
Journal of Environmental EngineeringLongitudinal Dispersion in Natural Streams
183 Citations1983Tom Beer, Peter C. Young
International Journal of ControlSome observations on instrumental variable methods of time-series analysis
175 Citations1976Peter C. Young
This paper discusses the instrumental variable (IV) and approximate maximum likelihood (AML) methods of recursive time-series analysis and shows how they can be unified to some extent within the context of maximum likelihood estimation.
Journal of ForecastingRecursive estimation and forecasting of non‐stationary time series
107 Citations1990C.N. Ng, Peter C. Young
A unified, fully recursive approach to the modelling and forecasting of non-stationary time-series based on the well-known ‘component’ or ‘structuraL’ form, which allows for conventional or self-adaptive implementation of state-space forecasting and seasonal adjustment.
International Journal of ControlRefined instrumental variable methods of recursive time-series analysis Part II. Multivariable systems
98 Citations1979Anthony J. Jakeman, Peter C. Young
The analysis indicates that the refined IVAML algorithm yields asymptotically efficient estimation results, whilst providing low variance estimates of the basic system parameters for medium sample sizes.
AutomaticaAn instrumental product moment test for model order estimation
94 Citations1978P.E. Wellstead
An instrumental variable modification to the product moment technique which overcomes problems when significant amounts of extraneous noise are present with a negligible amount of extra computation.
BiometrikaLeast squares estimation in dynamic-disturbance time series models
82 Citations1972D. A. Pierce
The Validity and Credibility of Models for Badly Defined Systems
79 Citations1983Peter C. Young
These characteristics are, of course, desirable in a mathematical model of a physical system; but they are clearly too subjective to provide useful and rigorous criteria for model evaluation.
European Journal of Operational ResearchModeling, identification and control in environmental systems
79 Citations1979Uri Shamir
Annual Review of Plant PhysiologyQuantitative Interpretation of Phloem Translocation Data
54 Citations1980P. E. H. MINCHIN, J. H. Troughton
The paper presents a meta-modelling framework for estimating the Parameter Variability of the Input-Output Model and some examples of models used in the US have shown variations in the response of the Response to Screaming Fish.
Water science and technology libraryRiver Flow Modelling and Forecasting
45 Citations1986D. A. Kraijenhoff, J. R. Moll
IEEE Transactions on Systems Man and CyberneticsInstrumental Variable Algorithms for Multiple Input Systems Described by Multiple Transfer Functions
43 Citations1980Anthony J. Jakeman, L. Paul Steele +1 more
Instumental variable algorithms are presented for multiple input-single output systems where the characteristic polynomials of the transfer functions associated with each input are not constrained to be Identical.
IFAC Proceedings VolumesProcess Parameter Estimation and Self Adaptive Control
41 Citations1965Peter C. Young
The paper describes a method of automatic process parameter estimation which has been mechanised with the aid of hybrid (analogue-digital) equipment, and differs from earlier schemes of this type in not requiring direct measurement of the input and output time derivatives of the process.
Water science and technology libraryTime-Series Methods and Recursive Estimation in Hydrological Systems Analysis
39 Citations1986Peter C. Young
This chapter will see how models of hydrological systems can be considered within a unified stochastic setting and how it is then possible to treat model calibration as a problem of time-series analysis.
Applied Mathematics and ComputationRecursive estimation: A unified approach to the identification estimation, and forecasting of hydrological systems
38 Citations1985Peter C. Young, Stephen George Wallis
The general class of linear, dynamic models, as applied to the characterisation of flow and dispersion behavior in rivers, are considered, and it is shown how these can be unified within the context of recursive time-series analysis and estimation.
Transactions of the American Institute of Electrical Engineers Part II Applications and IndustryPlant identification in the presence of disturbances and application to digital adaptive systems
31 Citations1961Pinchas J. Joseph, Jean M. Lewis +1 more
The newer adaptive point of view in designing a control system can, in general, allow for changes in input signal characteristics, plant characteristics, and disturbance characteristics with a minimum amount of a priori knowledge.
IEEE Transactions on Automatic ControlComments on "On-line identification of linear dynamic systems with applications to Kalman filtering"
29 Citations1972Peter C. Young
The approach to discrete system identification described in a recent paper by Mehra is shown to be one example of a whole class of instrumental variable (IV) solutions and an alternative, statistically more efficient, approximate maximum likelihood procedure is outlined.
International Journal of ControlAdvanced methods of recursive time-series analysis
26 Citations1983Anthony J. Jakeman, Peter C. Young
While the methods are quite similar for the TF model, it is shown that the instrumental-variable inspired OGEE approach yields algorithms that are computationally simpler and more robust when applied in practical situations.
Electronics LettersSelf-adaptive Kalman filter
25 Citations1979Peter C. Young
It is shown how the refined instrumental variable (r.i.v.) method of recursive parameter estimation can be modified simply so that it functions as an optimal adaptive filter and state-estimation algorithm.
International Journal of ControlOn the decoupling of system and noise model parameter estimation in time-series analysis
22 Citations1981Anthony J. Jakeman, Peter C. Young
The paper demonstrates that the procedure for decoupling of system and noise model parameter estimation used in the refined IVAML method of time- series analysis for the transfer function (TF) model has relevance to the estimation of other time-series model forms, including the popular ARMAX model.
Electronics LettersJoint parameter/state estimation
13 Citations1979Anthony J. Jakeman, Peter C. Young
IFAC Proceedings VolumesA Computer Program for General Recursive Time-Series Analysis
9 Citations1982Anthony J. Jakeman, Peter Young +1 more
A computer program for recursive time series analysis of data which may come from MISO or SISO systems with discrete or continuous-time representations with the incorporation of powerful model structure identification criteria and the provision to obtain asymptotically efficient estimates when the stochastic disturbances have rational spectral density.
IFAC Proceedings VolumesInstrumental Variable Methods for Arma Parameter Estimation
9 Citations1985B. Friedlander, Petre Stoica +1 more
The relationship of the modified Yule-Walker equations to IV methods is discussed and the asymptotic properties of the IV estimates are summarized in the context of optimizing estimation accuracy.
IFAC Proceedings VolumesTime Series Methods in Biological and Medical Data Analysis
4 Citations1979Anthony J. Jakeman, Peter C. Young
Time-series methods such as the recursive instrumental variable estimation procedure can be used to aid the analysis of biological and medical data obtained during transport experiments on the circulatory systems of both man and plants.
IFAC Proceedings VolumesRecursive-Iterative IV Estimation of Multiple-Input Transfer Function Models
2 Citations1985Karl Thomaseth, Peter C. Young +1 more
A modifica-tion of the RIV method which corrects deficiencies by a novel application of the Kalman filter is proposed, demonstrated through its application to the analysis of time-series data obtained from experiments on the glucose insulin system in humans and dogs.