Nonlinear System Identification Using Laguerre Wavelet Models
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P. Aadaleesan
A compact and efficient model that is capable of approximating both the linear and nonlinear components of the process is in high demand. In this paper, a novel black-box modeling technique viz. Wiener type Laguerre-Wavelet model is proposed. The Laguerre-Wavelet model has the capability to approximate a function with moderate/reasonable number of data with appreciable approximation accuracy. The Laguerre filter is used to approximate the linear dynamic components of the process, whereas wavelet structure is used for the static nonlinear components. The ability of wavelets to approximate any square-integrable function to any arbitrary precision by input-output mappings is utilised for the nonlinear approximation following a modified single scaling method. The performance efficiency of the proposed Wiener type model structure, Laguerre-Wavelet model, is demonstrated using simulation case study on a continuous bioreactor.
©2011 Walter de Gruyter GmbH & Co. KG, Berlin/Boston
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Artikel in diesem Heft
- Article
- Editorial: Special Issue Contributed by CITICOMS 2007 - International Conference on Modeling and Simulation, Selected Papers
- Modeling of Phenol Degradation in Spouted Bed Contactor Using Artificial Neural Network (ANN)
- Nonlinear System Identification Using Laguerre Wavelet Models
- Development of Sigmoidnet Based NARX Model for a Distillation Column
- Kinetic Studies on Sorption of Textile Dyes Using Lamina and Petiole Parts of Eichhornia crassipes
- Equilibrium and Kinetic Modeling on Biosorption of Reactive Red 2 Using Tamarindus indica Fruit Hulls
- Removal of Reactive Orange 4 from Aqueous Solution by Waste Eichhornia crassipes Biomass
- Modeling and Simulation of Viscoelastic Behavior of Three-Phase Polymer Blends with Multiple Droplet Morphology
- Dynamic Simulation of Mixing-Limited Pattern Formation in Homogeneous Autocatalytic Reactions
- Modeling Catalytic and Homogenous Combustion of Hydrocarbons in Monolithic Converters
