Results 141 to 150 of about 1,110 (179)
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Identification of a Benchmark Wiener–Hammerstein: A bilinear and Hammerstein–Bilinear model approach
Control Engineering Practice, 2012Abstract In this paper the Wiener–Hammerstein Benchmark is identified as a bilinear discrete system. The bilinear approximation relies on both facts that the Wiener–Hammerstein system can be described by a Volterra series which can be approximated by bilinear systems.
Ramos, Jose A. +2 more
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Hammerstein Models for Identification of Stochastic Systems
Automation and Remote Control, 2003zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Modeling of a distillation column based on NARMAX and Hammerstein models
International Journal of Modeling, Simulation, and Scientific Computing, 2017The modeling of distillation column process is a very challenging problem because of the complex dynamic behavior. This paper investigates a Nonlinear Autoregressive Moving Average with eXogenous input (NARMAX) model, and a Hammerstein model to approximate the evolution of the overhead temperature in a separation system.
Lakhdar Aggoune, Yahya Chetouani
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Parametric Hammerstein-Wiener model estimation via dual Hammerstein identification
2013 IEEE Digital Signal Processing and Signal Processing Education Meeting (DSP/SPE), 2013In this paper, we propose an approach to identify parametric Hammerstein-Wiener models. The approach identifies two Hammerstein models alternately, recovering the intermediate signal and parameters in both linear dynamic blocks and static nonlinear blocks.
Jianrui Long, Geoffrey A. Williamson
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Hammerstein-Wiener model research for a Stewart platform
2012 IEEE International Conference on Robotics and Biomimetics (ROBIO), 2012The Hammerstein-Wiener model for the Stewart platform driven by a DC motor is formulation, meanwhile the model's parameters are identified by experiments. By comparing the identification results of ARX model and Ham-merstein-Wiener model, it concludes that the Hammer-stein-Wiener model can describe the actual system's movement more accurately.
Xuewei Wang, Wensheng Zhang, Baolin Wu
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Model-based predictive control for Hammerstein systems
Proceedings of the 39th IEEE Conference on Decision and Control (Cat. No.00CH37187), 2002Hammerstein systems are a class of systems represented by a static nonlinearity at the input followed by a linear dynamic block. In the paper the static input nonlinearity is transformed into a polytopic description. The remaining uncertain linear model is used in a MPC algorithm of which the optimization problem involves minimization of a linear ...
Hayco H. J. Bloemen +2 more
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Non-parametric identification of generalized Hammerstein models
International Journal of Systems Science, 1998The Hammerstein model is considered in a generalized form, where its nonlinear element can have multi-inputs and a finite memory. The identification of the multi-input finite memory nonimearity and the impulse response sequence of the model is treated using a non-parametric approach. A numerical example is given.
Hosam E. Emara-Shabaik +1 more
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Identification of Hammerstein Models With Cubic Spline Nonlinearities
IEEE Transactions on Biomedical Engineering, 2004This paper considers the use of cubic splines, instead of polynomials, to represent the static nonlinearities in block structured models. It introduces a system identification algorithm for the Hammerstein structure, a static nonlinearity followed by a linear filter, where cubic splines represent the static nonlinearity and the linear dynamics are ...
Erika J. Dempsey, David T. Westwick
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On Model Complexity Control in Identification of Hammerstein Systems
Proceedings of the 44th IEEE Conference on Decision and Control, 2006Model complexity control and regularization play a crucial role in statistical learning theory and also for problems in system identification. This text discusses the potential of the issue of regularization in identification of Hammerstein systems in the context of primal-dual kernel machines and Least Squares Support Vector Machines (LS-SVMs) and ...
Kristiaan Pelckmans +3 more
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Blind Hammerstein Identification for MR Damper Modeling
2007 American Control Conference, 2007This paper proposes a new blind approach to identification of Hammerstein systems, where a static nonlinearity precedes a linear dynamic system. By exploiting input's piece-wise constant property, the denominator of the linear system is identified first together with the order and time delay.
Jiandong Wang +3 more
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