Linear Parameter-Varying System Identification: New Developments and Trends (Advanced Series in Electrical & Computer Engineering)

Linear Parameter-Varying System Identification: New Developments and Trends (Advanced Series in Electrical & Computer Engineering)

By: Carlo Novara (editor), Teresa Paula Azevedo Perdicoul (editor), Paulo Lopes dos Santos (editor)Hardback

1 - 2 weeks availability

Description

This review volume reports the state-of-the-art in Linear Parameter Varying (LPV) system identification. Written by world renowned researchers, this book contains twelve chapters, focusing on the most recent LPV identification methods for both discrete-time and continuous-time models, using different approaches such as optimization methods for input/output LPV models Identification, set membership methods, optimization methods and subspace methods for state-space LPV models identification and orthonormal basis functions methods. Since there is a strong connection between LPV systems, hybrid switching systems and piecewise affine models, identification of hybrid switching systems and piecewise affine systems will be considered as well.

Create a review

Contents

An Unified Framework for LPV, Switching and Affine Models Identification (B Bamieh et al.); Set-Membership Identification of LPV Models with Uncertain Time-Varying Parameters (V Cerone et al.); Set Membership Identification of State Space LPV Systems (C Novara); Identification of Discrete-Time and Continuous-Time Input/Output LPV Models (V Laurain et al.); Reducing the Dimensions of Data Matrices Involved in LPV Subspace Identification Methods (V Verdult & M Verhaegen); An Open Loop and Closed Loop LPV Subspace Identification Algorithm (J-W van Wingerden & M Verhaegen); Subspace Identification of Continuous-Time State-Space LPV Models (M Bergamasco & M Lovera); Identification of Continuous-Time LPV Systems Using the Subspace Successive Approximations Algorithm (P L dos Santos et al.); LPV Identification using Series-Expansion Models (R Toth et al.); Expectation Maximization and Gradient Methods for LPV State-Space Models Identification (A Wills et al.); Piecewise Affine Identification of Interconnected Systems with LFR Structure (S Paoletti & A Garulli); Identification and Model (In)validation of Switched Affine Systems (C Feng et al.).

Product Details

  • publication date: 04/01/2012
  • ISBN13: 9789814355445
  • Format: Hardback
  • Number Of Pages: 420
  • ID: 9789814355445
  • weight: 703
  • ISBN10: 9814355445

Delivery Information

  • Saver Delivery: Yes
  • 1st Class Delivery: Yes
  • Courier Delivery: Yes
  • Store Delivery: Yes

Prices are for internet purchases only. Prices and availability in WHSmith Stores may vary significantly

Close