Name
Title | ||
|---|---|---|
A direct maximum likelihood optimization approach to identification of LPV time-delay systems. |
Abstract | ||
|---|---|---|
This paper is concerned with parameter estimation for a single-input single-output (SISO) linear parameter varying (LPV) system in an input–output setting with output-error (OE) time-delay model structure. Since the practical industrial processes are inherently nonlinear and are often operated over several working points with transition dynamic periods between different working points, the multiple-model LPV model is considered in this paper. A global maximization method is firstly used to estimate an autoregressive with exogenous input (ARX) time-delay model for each local process in a noniterative way. Then the Maximum Likelihood (ML) estimator is developed to identify a global LPV OE model based on the local process data and the transition data with the parameters initialized based on the local parameter estimates for the ARX time-delay models. One numerical example and two practical simulation examples are presented to demonstrate the effectiveness of the proposed method. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1016/j.jfranklin.2016.03.005 | Journal of the Franklin Institute |
Field | DocType | Volume |
Autoregressive model,Local parameter,Mathematical optimization,Nonlinear system,Control theory,Maximum likelihood,Estimation theory,Maximization,Mathematics,Estimator | Journal | 353 |
Issue | ISSN | Citations |
8 | 0016-0032 | 0 |
PageRank | References | Authors |
0.34 | 0 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| xianqiang yang | 1 | 59 | 10.79 |
| Biao Huang | 2 | 39 | 4.60 |
| Huijun Gao | 3 | 8923 | 416.93 |