Strategies for feedback linearisation : a dynamic neural network approach / Freddy Garces and others
Material type:
TextPublication details: New York : Springer, 2003Description: xv, 171p, 23cmISBN: - 1852335017
- 629.8312 GAR
| Item type | Current library | Call number | Status | Date due | Barcode | Item holds | |
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Book
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Calcutta | 629.8312 GAR (Browse shelf(Opens below)) | Available | IIMC-118803 |
One of the most important developments in nonlinear control theory is the model-based method of feedback linearisation in which a nonlinear system is transformed into a linear system by means of state feedback and nonlinear transformations. After feedback linearisation, a system can be dealt with by linear controller design. The extension of these techniques to include MIMO systems allows for the further simplification of controller design by decoupling the system. Strategies for Feedback Linearisation demonstrates this powerful technique in the light of research on neural networks which allow the identification of nonlinear models without the complicated and costly development of models based on physical laws. Dynamic or recurrent neural networks have inherent properties that allow them to approximate nonlinear dynamic systems.This book describes it in a comprehendible way.
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