Identification of Input Nonlinear Control Autoregressive Systems Using Fractional Signal Processing Approach
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 squar...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2013-01-01
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| Series: | The Scientific World Journal |
| Online Access: | http://dx.doi.org/10.1155/2013/467276 |
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| author | Naveed Ishtiaq Chaudhary Muhammad Asif Zahoor Raja Junaid Ali Khan Muhammad Saeed Aslam |
| author_facet | Naveed Ishtiaq Chaudhary Muhammad Asif Zahoor Raja Junaid Ali Khan Muhammad Saeed Aslam |
| author_sort | Naveed Ishtiaq Chaudhary |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-e74d88ff1abf48f6b1f0b43f7dd58357 |
| institution | Kabale University |
| issn | 1537-744X |
| language | English |
| publishDate | 2013-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | The Scientific World Journal |
| spelling | doaj-art-e74d88ff1abf48f6b1f0b43f7dd583572025-02-03T01:31:16ZengWileyThe Scientific World Journal1537-744X2013-01-01201310.1155/2013/467276467276Identification of Input Nonlinear Control Autoregressive Systems Using Fractional Signal Processing ApproachNaveed Ishtiaq Chaudhary0Muhammad Asif Zahoor Raja1Junaid Ali Khan2Muhammad Saeed Aslam3Department of Electronic Engineering, International Islamic University, Islamabad 44000, PakistanDepartment of Electrical Engineering, COMSATS Institute of Information Technology, Attock Campus, Attock 43600, PakistanDepartment of Electrical Engineering, COMSATS Institute of Information Technology, Attock Campus, Attock 43600, PakistanPakistan Institute of Engineering and Applied Sciences, Nilore, Islamabad 45650, PakistanA 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.http://dx.doi.org/10.1155/2013/467276 |
| spellingShingle | Naveed Ishtiaq Chaudhary Muhammad Asif Zahoor Raja Junaid Ali Khan Muhammad Saeed Aslam Identification of Input Nonlinear Control Autoregressive Systems Using Fractional Signal Processing Approach The Scientific World Journal |
| title | Identification of Input Nonlinear Control Autoregressive Systems Using Fractional Signal Processing Approach |
| title_full | Identification of Input Nonlinear Control Autoregressive Systems Using Fractional Signal Processing Approach |
| title_fullStr | Identification of Input Nonlinear Control Autoregressive Systems Using Fractional Signal Processing Approach |
| title_full_unstemmed | Identification of Input Nonlinear Control Autoregressive Systems Using Fractional Signal Processing Approach |
| title_short | Identification of Input Nonlinear Control Autoregressive Systems Using Fractional Signal Processing Approach |
| title_sort | identification of input nonlinear control autoregressive systems using fractional signal processing approach |
| url | http://dx.doi.org/10.1155/2013/467276 |
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