A new approach, recursive incremental estimation, is presented for identification of time-varying systems. The basic idea is to assume implicitly a changing system model, instead of a constant one as with most variant...
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A new approach, recursive incremental estimation, is presented for identification of time-varying systems. The basic idea is to assume implicitly a changing system model, instead of a constant one as with most variants of the standard least squares algorithm, and then to identify the characteristics of this model. The derived algorithm can enlarge the memory length of the estimator while maintaining tracking ability, so that some of the major problems experienced with the existing algorithms can be reduced. Copyright (C) 1996 Elsevier Science Ltd.
Quality control is becoming a key success factor in many industrial areas. The need for high quality in production processes gives new impetus to the development and application of advanced control strategies for proc...
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Quality control is becoming a key success factor in many industrial areas. The need for high quality in production processes gives new impetus to the development and application of advanced control strategies for processes which, up to now, have been controlled with ''classical'' techniques. In this paper, quality control for coiling machines is addressed. It is shown that, to guarantee high quality to the process of spring production, a complex adaptive control strategy must be developed. The resulting control system is based on the estimation of suitable parameters, characterizing the disturbances that exist on the process, and on the use of such parameters to tune a controller of appropriate structure. Interestingly enough, the method proposed in the paper, due to the peculiarity of the disturbance which presents narrow-band spectral components, has strong analogies with similar approaches developed in the field of active noise and vibration control, thereby enlarging the field of application of such techniques. The algorithm described here has been applied to a real coiling machine, and the experimental results are presented in the paper. Copyright (C) 1997 Elsevier Science Ltd.
This paper proposes a unified approach to the estimation of the physical parameters defining both geared and linear resonant systems, namely the dead-zone, inertia, stiffness and damping parameters. Although the techn...
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This paper proposes a unified approach to the estimation of the physical parameters defining both geared and linear resonant systems, namely the dead-zone, inertia, stiffness and damping parameters. Although the technique is based on discrete-time models, it allows extraction of the continuous-time parameters from the discrete coefficients. This is facilitated by a modular procedure, involving separate locked- and unlocked-load measurements. The difference equation coefficients associated with the discrete model become trivial functions of the physical system parameters, which are computed using predetermined polynomial approximations. The reduced-order estimation modules improve noise immunity and simplify the estimation routines. Very accurate experimental results verify the utility of the approach. (C) 2003 Elsevier Science Ltd. All rights reserved.
The problem of evaluating model uncertainty in the framework of subspace identification methods is considered and the use of the methods of computational statistics is proposed. In particular, a procedure for the esti...
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The problem of evaluating model uncertainty in the framework of subspace identification methods is considered and the use of the methods of computational statistics is proposed. In particular, a procedure for the estimation of the standard error of the eigenvalues and of the frequency response of the identified models is presented. Simulation results demonstrate that accurate estimates of the standard error can be obtained by this approach. (C) 2000 Elsevier Science Ltd. All rights reserved.
In this paper, a model-based procedure exploiting analytical redundancy for the detection and isolation of faults on a gas turbine process is presented. The main point of the present work consists of exploiting system...
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In this paper, a model-based procedure exploiting analytical redundancy for the detection and isolation of faults on a gas turbine process is presented. The main point of the present work consists of exploiting system identification schemes in connection with observer and filter design procedures for diagnostic purpose. Linear model identification (black-box modelling) and output estimation (dynamic observers and Kalman filters) integrated approaches to fault diagnosis are in particular advantageous in terms of solution complexity and performance. This scheme is especially useful when robust solutions are considered for minimise the effects of modelling errors and noise, while maximising fault sensitivity. A model of the process under investigation is obtained by identification procedures, whilst the residual generation task is achieved by means of output observers and Kalman filters designed in both noise-free and noisy assumptions. The proposed tools have been tested on a single-shaft industrial gas turbine prototype model and they have been evaluated using non-linear simulations, based on the gas turbine data. (C) 2006 Elsevier Ltd. All rights reserved.
Dynamic errors-in-variables (EV) models are a new type of linear system models and have found extensive practical applications. One common and important concern with EV models is how to remove noise-induced bias in pa...
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Dynamic errors-in-variables (EV) models are a new type of linear system models and have found extensive practical applications. One common and important concern with EV models is how to remove noise-induced bias in parameter estimators. In this paper some significant extensions to the newly established bias-eliminated least-squares (BELS) method are made, so that this BELS method can be applied to unbiased identification of a general class of dynamic EV models where input noise is white noise and output noise is correlated noise but the noise statistics are unknown a priori. Though still based on the bias correction principle, this method is very meaningful in that it presents a novel and efficient way of utilizing signal-processing techniques to draw much more useful information from sampled data in order to get desirable identification results. The performance of the proposed method is illustrated by numerical examples.
Tyres play a key role in ground vehicles' dynamics because they are responsible for traction, braking and cornering. A proper tyre-road interaction model is essential for a useful and reliable vehicle dynamics mod...
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Tyres play a key role in ground vehicles' dynamics because they are responsible for traction, braking and cornering. A proper tyre-road interaction model is essential for a useful and reliable vehicle dynamics model. In the last two decades Pacejka's Magic Formula (MF) has become a standard in simulation field. This paper presents a Tool, called TRIP-ID (Tyre Road Interaction Parameters identification), developed to characterize and to identify with a high grade of accuracy and reliability MF micro-parameters from experimental data deriving from telemetry or from test rig. The tool guides interactively the user through the identification process on the basis of strong diagnostic considerations about the experimental data made evident by the tool itself. A motorsport application of the tool is shown as a case study. (C) 2017 Elsevier Ltd. All rights reserved.
In this paper a complete and systematic procedure for the identification of the dynamic parameters of rigid robot manipulators is presented. Starting from the basic results on the subject present in the literature and...
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In this paper a complete and systematic procedure for the identification of the dynamic parameters of rigid robot manipulators is presented. Starting from the basic results on the subject present in the literature and on a new technique to find exciting trajectories for the estimation, the procedure is developed. A set of algorithms is provided for the implementation of the various steps of the procedure for a generic open-chain structure. The algorithms have been coded in the popular Matlab/Maple environment and the procedure has been tested in a practical case study to identify the dynamic parameters of a six-degree-of-freedom conventional industrial robot.
We give a consistency proof for two subspace methods. We then show the asymptotic equivalence of a special subspace method and the initial estimate proposed by Hannan and Rissanen. Finally, a simulation study comparin...
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We give a consistency proof for two subspace methods. We then show the asymptotic equivalence of a special subspace method and the initial estimate proposed by Hannan and Rissanen. Finally, a simulation study comparing two subspace methods and the maximum-likelihood method is performed.
Second-order notch filters are commonly used for frequency estimation purposes. They are characterized by a single design parameter, the value of which is selected so as to achieve a suitable compromise between tracki...
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Second-order notch filters are commonly used for frequency estimation purposes. They are characterized by a single design parameter, the value of which is selected so as to achieve a suitable compromise between tracking performance and bias/variance errors. In this paper a new class of filters (of fourth order) is presented: the funnel-shaped filters, or funnel filters for short. These filters enables one to estimate harmonic signals with enhanced tracking capability, without any deterioration of the steady-state performance. (C) 1997 Elsevier Science Ltd.
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