The Experts below are selected from a list of 312 Experts worldwide ranked by ideXlab platform
D.w.t. Rippin - One of the best experts on this subject based on the ideXlab platform.
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Theory and application of the Modulating Function method—I. Review and theory of the method and theory of the spline-type Modulating Functions
Computers & Chemical Engineering, 1993Co-Authors: Heinz A. Preisig, D.w.t. RippinAbstract:Abstract The progress of research on Modulating Function methods and their applications over the period of 1954–1990 is summarized and analyzed herein. After introducing the concept of the Modulating Function method and defining the key properties of Modulating Functions the history of the method with its developments and applications is given. Applicable to nonlinear systems, the structure the models may have in terms of nonlinearities is explored in detail, which is followed by a discussion of the method in the framework of process identification. The second section introduces the analytically derived spline-type Modulating Functions and discusses in detail their specific properties.
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Theory and application of the Modulating Function method—II. algebraic representation of Maletinsky's spline-type Modulating Functions
Computers & Chemical Engineering, 1993Co-Authors: Heinz A. Preisig, D.w.t. RippinAbstract:Abstract The complete algebraic representation of Maletinsky's spline-type modulation Function method is presented for arbitrary order. This result is extended to the cases of arbitrarily overlapping modulations running in parallel but with shifted phase. The equations for constant-length and different-length modulation are derived. In both cases it could be shown that the basic signal operations that are to be installed on-line are the same as for the “normal arrangement” suggested by Maletinsky. Additionally, the equation for the normalization factor was obtained. A short example demonstrates the power of the Modulating Function approach in system identification.
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Theory and application of the Modulating Function method—III. application to industrial process, a well-stirred tank reactor
Computers & Chemical Engineering, 1993Co-Authors: Heinz A. Preisig, D.w.t. RippinAbstract:Abstract A dynamic model describing the energy dissipation in a poorly defined, industrial, well-stirred tank reactor is identified. A successive refinement approach is presented in which an initial simple model is refined in three stages: (i) the Modulating Function method is utilized for estimating the heat transfer parameters locally as a Function of time; (ii) the parameters, which, because of the modelling errors, change with changing operating conditions, are graphically correlated with the operating conditions; and (iii) the resulting nonlinear model is refined by introducing additional dynamic elements. Validation of the model was done by comparing the predicted steady-state heat losses with other experimental data.
Heinz A. Preisig - One of the best experts on this subject based on the ideXlab platform.
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Theory and application of the Modulating Function method—I. Review and theory of the method and theory of the spline-type Modulating Functions
Computers & Chemical Engineering, 1993Co-Authors: Heinz A. Preisig, D.w.t. RippinAbstract:Abstract The progress of research on Modulating Function methods and their applications over the period of 1954–1990 is summarized and analyzed herein. After introducing the concept of the Modulating Function method and defining the key properties of Modulating Functions the history of the method with its developments and applications is given. Applicable to nonlinear systems, the structure the models may have in terms of nonlinearities is explored in detail, which is followed by a discussion of the method in the framework of process identification. The second section introduces the analytically derived spline-type Modulating Functions and discusses in detail their specific properties.
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Theory and application of the Modulating Function method—II. algebraic representation of Maletinsky's spline-type Modulating Functions
Computers & Chemical Engineering, 1993Co-Authors: Heinz A. Preisig, D.w.t. RippinAbstract:Abstract The complete algebraic representation of Maletinsky's spline-type modulation Function method is presented for arbitrary order. This result is extended to the cases of arbitrarily overlapping modulations running in parallel but with shifted phase. The equations for constant-length and different-length modulation are derived. In both cases it could be shown that the basic signal operations that are to be installed on-line are the same as for the “normal arrangement” suggested by Maletinsky. Additionally, the equation for the normalization factor was obtained. A short example demonstrates the power of the Modulating Function approach in system identification.
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Theory and application of the Modulating Function method—III. application to industrial process, a well-stirred tank reactor
Computers & Chemical Engineering, 1993Co-Authors: Heinz A. Preisig, D.w.t. RippinAbstract:Abstract A dynamic model describing the energy dissipation in a poorly defined, industrial, well-stirred tank reactor is identified. A successive refinement approach is presented in which an initial simple model is refined in three stages: (i) the Modulating Function method is utilized for estimating the heat transfer parameters locally as a Function of time; (ii) the parameters, which, because of the modelling errors, change with changing operating conditions, are graphically correlated with the operating conditions; and (iii) the resulting nonlinear model is refined by introducing additional dynamic elements. Validation of the model was done by comparing the predicted steady-state heat losses with other experimental data.
Jerome Jouffroy - One of the best experts on this subject based on the ideXlab platform.
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On-line parameter and state estimation of an air handling unit model: experimental results using the Modulating Function method.
arXiv: Systems and Control, 2018Co-Authors: Ana Ionesi, Hossein Ramezani, Jerome JouffroyAbstract:This paper considers the on-line implementation of the Modulating Function method, for parameter and state estimation, for the model of an air-handling unit, the central element of HVAC systems. After recalling the few elements of the method, more attention is paid on issues related to its on-line implementation, issues for which we use two different techniques. Experimental results are obtained after implementation of the algorithms on a heat flow experiment, and they are compared with conventional techniques (conventional tools from Matlab for parameter estimation, and a simple Luenberger observer for state estimation) for their validation.
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WSC - Online parameter estimation of reduced-order models for buildings energy dynamics using the Modulating Function method
2018 Winter Simulation Conference (WSC), 2018Co-Authors: Ana Ionesi, Jerome JouffroyAbstract:This paper considers parameter estimation of a reduced-order model (ROM) for building energy dynamics using the Modulating Function (MF) method. After briefly presenting a model of building dynamics, we recall the MF method and present a way of determining a Modulating Function directly from the available data instead of defining it a priori. Then, we look at the application of this method in a case study, where actual weather-based data (solar radiation and outdoor ambient temperature) is used. The results together with the advantages of the MF underline the potential of the proposed algorithm.
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AIM - On-line parameter estimation of an Air Handling Unit model: experimental results using the Modulating Function method
2018 IEEE ASME International Conference on Advanced Intelligent Mechatronics (AIM), 2018Co-Authors: Ana Ionesi, Jerome JouffroyAbstract:In this paper, we investigate the implementation of an on-line parameter estimation scheme on a heat flow experiment. The aim is to estimate on-line the parameters of a reduced-order model for the heat flow process in the air handling unit of a typical fan coil compact HVAC system. The well-known Modulating Function method is used as the estimation algorithm. The results obtained from implementation on an actual experimental platform show a good performance.
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CCA - Finite-time simultaneous parameter and state estimation using Modulating Functions
2015 IEEE Conference on Control Applications (CCA), 2015Co-Authors: Jerome Jouffroy, Johann RegerAbstract:This paper discusses the use of techniques related to the Modulating Function method for performing joint parameter and state estimation. After a short review of other methods related to Modulating Functions, we look at observability issues and the so-called Least-Squares observers to extend currently existing results on joint parameter and state estimation using Modulating Functions. An example is given as illustration.
Heinz Unbehauen - One of the best experts on this subject based on the ideXlab platform.
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Batch scheme recursive Hartley Modulating Functions identification of nonlinear continuous-time Hammerstein model
1999 European Control Conference (ECC), 1999Co-Authors: S. Daniel-berhe, Heinz UnbehauenAbstract:In this contribution, a new batch scheme recursive Hartley Modulating Functions identification approach is developed to estimate the parameters of a nonlinear continuous-time Hammerstein model. The method is implemented by moving a fixed window size of time series data forward at each sampling instance. A new transformation is formulated for the Hartley Modulating Function (HMF) which is suitable for recursive Hartley spectra computations. Once the initial sequential batch data is measured, the algorithm computes the required input-output Hartley transforms then updates recursively the sequential Hartley transforms and spectra for each coming sample of input-output signals. Hence, this will update the regressand vector and regression matrix of the system HMF model. After that, a least squares algorithm is employed to estimate recursively parameters of the linear dynamic system and the static nonlinear element. The batch scheme recursive algorithm developed here offers significant reductions in the computation of numerical Hartley integration compared to the nonrecursive implementation of the HMF-method [4]. In this paper, the numerical Hartley integration is based on a stair-case approximation and updated as a fixed window size which is shifted one step forward every sampling instant. Simulation studies are provided to illustrate the performance of the proposed algorithm.
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Bilinear continuous-time systems identification via Hartley-based Modulating Functions
Automatica, 1998Co-Authors: S. Daniel-berhe, Heinz UnbehauenAbstract:Abstract This paper highlights the relevance and merits of the Hartley Modulating Functions (HMF) method for the identification of bilinear continuous-time (BCT) systems from recorded input and noise-contaminated output data and it provides an insight into parameter estimation of a wider range of nonlinear systems in practice. The methodology replaces the I/O-differential equation representing the dynamic system behavior by the Hartley spectrum equation. As a result it involves the known derivatives of the Modulating Function instead of the derivatives of the input and noisy output data by applying integral transformation to signals. A frequency weighted least-squares algorithm is also applied in the identification and a normalized root mean square criterion is used to investigate some computational considerations and the bias of the estimates. Results of the simulation studies demonstrate the appropriateness of the approach and its efficiency.
L. Sani - One of the best experts on this subject based on the ideXlab platform.
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Modulating Functions for identification and modeling of ZVS class E 2 resonant converters
Industrial Electronics 2002. ISIE 2002. Proceedings of the 2002 IEEE International Symposium on, 2002Co-Authors: Alessandro Balestrino, A. Landi, Ottorino Bruno, L. SaniAbstract:Aim of the paper is to build mathematical models of class E2 resonant DC/DC converters from input-output data. Among the various identification techniques, the Modulating Functions were chosen, due to their capability for revealing converter dynamics even in case of fast time constants. Each obtained model was tested around its working point: an accurate analysis was performed by varying both the number of pole-zeroes and the window width for identification. Extensive Spice simulations were run for an exhaustive and accurate evaluation of the models proposed. Preliminary results from experimental tests confirm the simulated ones. As a relevant conclusion, the Modulating Function method for identification and modelling reveals its effectiveness even in the critical case of resonant converters, where all traditional averaging techniques fail.
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Parameter identification of continuous systems with multiple-input time delays via Modulating Functions
IEE Proceedings - Control Theory and Applications, 2000Co-Authors: Alessandro Balestrino, A. Landi, L. SaniAbstract:The identification of continuous systems with multiple-input delays is discussed. A batch algorithm for parametric identification of both multiple time delays and unknown parameters is proposed using the Modulating Function approach. If the unknown delay is expressed as a linear combination of a bank of known delays, it is proven that the distribution of the identified coefficients is a sampling centred on the unknown delays; the result is then extended to the multiple delay case. The Modulating Function method guarantees a continuous-time approach and robustness for a high value of noise-to-signal ratio. Simulation results are included to illustrate the proposed technique.
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Identification of Hammerstein systems with input/output time delay via Modulating Functions
IFAC Proceedings Volumes, 2000Co-Authors: Alessandro Balestrino, A. Landi, L. SaniAbstract:Abstract Hammerstein processes are represented by a static nonlinear element followed by a dynamic linear system. This paper proposes the application of Modulating Function method to identify Hammerstein models, in the hypothesis of a nonlinear element approximated by a polynomial Function. The linear dynamic system can include the presence of unknown time delays. The use of the Modulating Function method guarantees a continuous-time approach and robustness for high value of the noise-to-output signal ratio (NSR).