Name
Title | ||
|---|---|---|
Auxiliary model based multi-innovation algorithms for multivariable nonlinear systems |
Abstract | ||
|---|---|---|
This paper considers the identification problem for multi-input multi-output nonlinear systems. The difficulty of the parameter identification of such systems is that the information vector in the identification model contains unknown variables. The solution is using the auxiliary model identification idea to overcome the difficulty. An auxiliary model based multi-innovation extended stochastic gradient algorithm is presented by expanding the innovation vector to an innovation matrix. The proposed algorithm uses not only the current innovation but also the past innovations at each recursion and thus the parameter estimation accuracy can be improved. The numerical example shows that the proposed algorithm is effective. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1016/j.mcm.2010.05.026 | Mathematical and Computer Modelling |
Keywords | Field | DocType |
innovation matrix,multi-innovation identification,multi-input multi-output systems,identification model,innovation vector,multivariable nonlinear system,proposed algorithm,identification problem,auxiliary model,parameter identification,parameter estimation,auxiliary model identification idea,auxiliary model identification,multi-innovation algorithm,stochastic gradient,current innovation,past innovation,nonlinear system,model identification | Information system,Mathematical optimization,Nonlinear system,Multivariable nonlinear system,Matrix (mathematics),Algorithm,Estimation theory,System identification,Recursion,Parameter identification problem,Mathematics | Journal |
Volume | Issue | ISSN |
52 | 9-10 | Mathematical and Computer Modelling |
Citations | PageRank | References |
26 | 0.76 | 31 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jing Chen | 1 | 89 | 5.41 |
| Yan Zhang | 2 | 26 | 0.76 |
| Ruifeng Ding | 3 | 261 | 11.82 |