Particle Swarm Optimization Iterative Identification Algorithm and Gradient Iterative Identification Algorithm for Wiener Systems with Colored Noise
This paper considers the parameter identification of Wiener systems with colored noise. The difficulty in the identification is that the model is nonlinear and the intermediate variable cannot be measured. Particle swarm optimization is an artificial intelligence evolutionary method and is effective...
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| Format: | Article |
| Language: | English |
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Wiley
2018-01-01
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| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2018/7353171 |
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| _version_ | 1850209334736191488 |
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| author | Junhong Li Xiao Li |
| author_facet | Junhong Li Xiao Li |
| author_sort | Junhong Li |
| collection | DOAJ |
| description | This paper considers the parameter identification of Wiener systems with colored noise. The difficulty in the identification is that the model is nonlinear and the intermediate variable cannot be measured. Particle swarm optimization is an artificial intelligence evolutionary method and is effective in solving nonlinear optimization problem. In this paper, we obtain the identification model of the Wiener system and then transfer the parameter identification problem into an optimization problem. Then, we derive a particle swarm optimization iterative (PSOI) identification algorithm to identify the unknown parameter of the Wiener system. Furthermore, a gradient iterative identification algorithm is proposed to compare with the particle swarm optimization iterative algorithm. Numerical simulation is carried out to evaluate the performance of the PSOI algorithm and the gradient iterative algorithm. The simulation results indicate that the proposed algorithms are effective and the PSOI algorithm can achieve better performance over the gradient iterative algorithm. |
| format | Article |
| id | doaj-art-910a278dbdf743f7ad36a3ccfaf33b23 |
| institution | OA Journals |
| issn | 1076-2787 1099-0526 |
| language | English |
| publishDate | 2018-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Complexity |
| spelling | doaj-art-910a278dbdf743f7ad36a3ccfaf33b232025-08-20T02:10:02ZengWileyComplexity1076-27871099-05262018-01-01201810.1155/2018/73531717353171Particle Swarm Optimization Iterative Identification Algorithm and Gradient Iterative Identification Algorithm for Wiener Systems with Colored NoiseJunhong Li0Xiao Li1School of Electrical Engineering, Nantong University, Nantong 226019, ChinaSchool of Electrical Engineering, Nantong University, Nantong 226019, ChinaThis paper considers the parameter identification of Wiener systems with colored noise. The difficulty in the identification is that the model is nonlinear and the intermediate variable cannot be measured. Particle swarm optimization is an artificial intelligence evolutionary method and is effective in solving nonlinear optimization problem. In this paper, we obtain the identification model of the Wiener system and then transfer the parameter identification problem into an optimization problem. Then, we derive a particle swarm optimization iterative (PSOI) identification algorithm to identify the unknown parameter of the Wiener system. Furthermore, a gradient iterative identification algorithm is proposed to compare with the particle swarm optimization iterative algorithm. Numerical simulation is carried out to evaluate the performance of the PSOI algorithm and the gradient iterative algorithm. The simulation results indicate that the proposed algorithms are effective and the PSOI algorithm can achieve better performance over the gradient iterative algorithm.http://dx.doi.org/10.1155/2018/7353171 |
| spellingShingle | Junhong Li Xiao Li Particle Swarm Optimization Iterative Identification Algorithm and Gradient Iterative Identification Algorithm for Wiener Systems with Colored Noise Complexity |
| title | Particle Swarm Optimization Iterative Identification Algorithm and Gradient Iterative Identification Algorithm for Wiener Systems with Colored Noise |
| title_full | Particle Swarm Optimization Iterative Identification Algorithm and Gradient Iterative Identification Algorithm for Wiener Systems with Colored Noise |
| title_fullStr | Particle Swarm Optimization Iterative Identification Algorithm and Gradient Iterative Identification Algorithm for Wiener Systems with Colored Noise |
| title_full_unstemmed | Particle Swarm Optimization Iterative Identification Algorithm and Gradient Iterative Identification Algorithm for Wiener Systems with Colored Noise |
| title_short | Particle Swarm Optimization Iterative Identification Algorithm and Gradient Iterative Identification Algorithm for Wiener Systems with Colored Noise |
| title_sort | particle swarm optimization iterative identification algorithm and gradient iterative identification algorithm for wiener systems with colored noise |
| url | http://dx.doi.org/10.1155/2018/7353171 |
| work_keys_str_mv | AT junhongli particleswarmoptimizationiterativeidentificationalgorithmandgradientiterativeidentificationalgorithmforwienersystemswithcolorednoise AT xiaoli particleswarmoptimizationiterativeidentificationalgorithmandgradientiterativeidentificationalgorithmforwienersystemswithcolorednoise |