Identification of Input Nonlinear Control Autoregressive Systems Using Fractional Signal Processing Approach. (17th June 2013)

• Record Type: Journal Article
• Authors: Chaudhary, Naveed Ishtiaq; Raja, Muhammad Asif Zahoor; Khan, Junaid Ali; Aslam, Muhammad Saeed
• Other Names: Penedo Manuel F. Gonzalez Academic Editor.; Ruano Antonio Academic Editor.
• Is Part Of: TheScientificWorldjournal. Volume 2013(2013)
• Publication Date: 2013-06-17
• Subjects: Science -- Periodicals; Technology -- Periodicals; Medicine -- Periodicals; 505
• DOI: 10.1155/2013/467276
• Languages: English
• ISSNs: 2356-6140

Abstract

Abstract : A novel algorithm is developed based on fractional signal processing approach for parameter estimation of input nonlinear control autoregressive (INCAR) models. The design scheme consists of parameterization of INCAR systems to obtain linear-in-parameter models and to use fractional least mean square algorithm (FLMS) for adaptation of unknown parameter vectors. The performance analyses of the proposed scheme are carried out with third-order Volterra least mean square (VLMS) and kernel least mean square (KLMS) algorithms based on convergence to the true values of INCAR systems. It is found that the proposed FLMS algorithm provides most accurate and convergent results than those of VLMS and KLMS under different scenarios and by taking the low-to-high signal-to-noise ratio.