Name
Abstract | ||
|---|---|---|
To solve the problem caused by the lack of the structure of the nonlinearity in Wiener systems identification, we propose a new approach to identify the linear part and the nonlinear part of a Wiener system in sequence by using the limited information on the nonlinearity. The linear part of the system is identified firstly based on the limited information of the nonlinearity, such as sign information, monotonic information and then, we construct the internal signals to identify the structure and the parameters of the Wiener systems. A novel Particle Swarm Optimization–Rosenbrock (PSO–Rosenbrock) algorithm is developed and the numerical simulation shows that the identification procedure proposed in this paper is effective. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1016/j.mcm.2013.06.005 | Mathematical and Computer Modelling |
Keywords | Field | DocType |
Identification,Nonlinear systems,Wiener system,PSO–Rosenbrock,Limited information | Particle swarm optimization,Monotonic function,Mathematical optimization,Nonlinear system,Computer simulation,Mathematics | Journal |
Volume | Issue | ISSN |
58 | 7 | 0895-7177 |
Citations | PageRank | References |
0 | 0.34 | 12 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Qibing Jin | 1 | 19 | 11.28 |
| Jun Dou | 2 | 0 | 0.34 |
| Feng Ding | 3 | 0 | 0.34 |
| Liting Cao | 4 | 0 | 1.69 |