Name
Abstract | ||
|---|---|---|
The identification of nonlinear system was the main topics in the current international identification fields. In this paper, an identification approach of a kind of nonlinear system is put forward. First, the idea of the method employed a system model composed with classical models so as to transform the system structure identification problem into a combinational problem. Second, a bacterial chemotaxis optimization (BCO) approach is adopted to implement the identification on the system structure and parameters. Finally, to illustrate the rationality and effectiveness of the presented method, simulation examples are included. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1109/ICNC.2011.6022524 | ICNC |
Keywords | Field | DocType |
optimisation,combinatorial optimization,bco technique,classical model,identification,nonlinear system identification,combinatorial mathematics,bacterial chemotaxis optimization approach,nonlinear control systems,nonlinear system,combinational problem,system structure identification problem,mathematical model,system identification,data models,trajectory,microorganisms,data model,nonlinear systems,optimization | Data modeling,Mathematical optimization,Nonlinear system,Computer science,Nonlinear system identification,Combinatorial optimization,Artificial intelligence,System identification,Trajectory,Machine learning,Parameter identification problem,System model | Conference |
Volume | Issue | ISSN |
3 | null | 2157-9555 |
ISBN | Citations | PageRank |
978-1-4244-9950-2 | 0 | 0.34 |
References | Authors | |
5 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Guangjun Liu | 1 | 41 | 5.97 |
| Xiaoping Xu | 2 | 29 | 3.29 |
| Feng Wang | 3 | 8 | 1.93 |