Identification of Continuous-Time Hammerstein Systems by Simultaneous Perturbation Stochastic Approximation
This paper proposes an identification method for Hammerstein systems using simultaneous perturbation stochastic approximation (SPSA). Here, the structure of nonlinear subsystem is assumed to be unknown, while the structure of linear subsystem, such as the system order, is assumed to be available. Th...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2016
|
| Subjects: | |
| Online Access: | http://umpir.ump.edu.my/id/eprint/11129/ http://umpir.ump.edu.my/id/eprint/11129/1/Identification%20of%20continuous1.pdf |
| _version_ | 1848818932097482752 |
|---|---|
| author | Mohd Ashraf, Ahmad Azuma, Shun-ichi Sugie, Toshiharu |
| author_facet | Mohd Ashraf, Ahmad Azuma, Shun-ichi Sugie, Toshiharu |
| author_sort | Mohd Ashraf, Ahmad |
| building | UMP Institutional Repository |
| collection | Online Access |
| description | This paper proposes an identification method for Hammerstein systems using simultaneous perturbation stochastic approximation (SPSA). Here, the structure of nonlinear subsystem is assumed to be unknown, while the structure of linear subsystem, such as the system order, is assumed to be available. The main advantage of the SPSA-based method is that it can be applied to identification of Hammerstein systems with less restrictive assumptions. In order to clarify this point, piecewise affine functions with a large number of parameters are adopted to approximate the unknown nonlinear subsystems. Furthermore, the linear subsystems are supposed to be described in continuous-time. Though this class of systems closely reflects the actual systems, there are few methods to identify such models. Hence, the SPSA-based method is utilized to identify the parameters in both linear and nonlinear subsystems simultaneously. The effectiveness of the proposed method is evaluated through several numerical examples. The results demonstrate that the proposed algorithm is useful to obtain accurate models, even for high-dimensional parameter identification. |
| first_indexed | 2025-11-15T01:45:31Z |
| format | Article |
| id | ump-11129 |
| institution | Universiti Malaysia Pahang |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T01:45:31Z |
| publishDate | 2016 |
| publisher | Elsevier |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | ump-111292020-03-25T23:45:16Z http://umpir.ump.edu.my/id/eprint/11129/ Identification of Continuous-Time Hammerstein Systems by Simultaneous Perturbation Stochastic Approximation Mohd Ashraf, Ahmad Azuma, Shun-ichi Sugie, Toshiharu TK Electrical engineering. Electronics Nuclear engineering This paper proposes an identification method for Hammerstein systems using simultaneous perturbation stochastic approximation (SPSA). Here, the structure of nonlinear subsystem is assumed to be unknown, while the structure of linear subsystem, such as the system order, is assumed to be available. The main advantage of the SPSA-based method is that it can be applied to identification of Hammerstein systems with less restrictive assumptions. In order to clarify this point, piecewise affine functions with a large number of parameters are adopted to approximate the unknown nonlinear subsystems. Furthermore, the linear subsystems are supposed to be described in continuous-time. Though this class of systems closely reflects the actual systems, there are few methods to identify such models. Hence, the SPSA-based method is utilized to identify the parameters in both linear and nonlinear subsystems simultaneously. The effectiveness of the proposed method is evaluated through several numerical examples. The results demonstrate that the proposed algorithm is useful to obtain accurate models, even for high-dimensional parameter identification. Elsevier 2016 Article PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/11129/1/Identification%20of%20continuous1.pdf Mohd Ashraf, Ahmad and Azuma, Shun-ichi and Sugie, Toshiharu (2016) Identification of Continuous-Time Hammerstein Systems by Simultaneous Perturbation Stochastic Approximation. Expert Systems with Applications, 43. pp. 51-58. ISSN 0957-4174. (Published) http://dx.doi.org/10.1016/j.eswa.2015.08.041 DOI: 10.1016/j.eswa.2015.08.041 |
| spellingShingle | TK Electrical engineering. Electronics Nuclear engineering Mohd Ashraf, Ahmad Azuma, Shun-ichi Sugie, Toshiharu Identification of Continuous-Time Hammerstein Systems by Simultaneous Perturbation Stochastic Approximation |
| title | Identification of Continuous-Time Hammerstein Systems by Simultaneous Perturbation Stochastic Approximation |
| title_full | Identification of Continuous-Time Hammerstein Systems by Simultaneous Perturbation Stochastic Approximation |
| title_fullStr | Identification of Continuous-Time Hammerstein Systems by Simultaneous Perturbation Stochastic Approximation |
| title_full_unstemmed | Identification of Continuous-Time Hammerstein Systems by Simultaneous Perturbation Stochastic Approximation |
| title_short | Identification of Continuous-Time Hammerstein Systems by Simultaneous Perturbation Stochastic Approximation |
| title_sort | identification of continuous-time hammerstein systems by simultaneous perturbation stochastic approximation |
| topic | TK Electrical engineering. Electronics Nuclear engineering |
| url | http://umpir.ump.edu.my/id/eprint/11129/ http://umpir.ump.edu.my/id/eprint/11129/ http://umpir.ump.edu.my/id/eprint/11129/ http://umpir.ump.edu.my/id/eprint/11129/1/Identification%20of%20continuous1.pdf |