Name
Abstract | ||
|---|---|---|
This paper considers the problem of using noisy output data to estimate unknown time-delays and unknown system parameters in a general nonlinear time-delay system. We formulate the problem as a dynamic optimization problem in which the unknown quantities are decision variables to be chosen optimally, with the cost function penalizing the mean and variance of the least-squares error between actual and predicted system output. Since the time-delays and system parameters influence the cost function implicitly through the governing time-delay system, the cost function's gradient-which is required to solve the problem using gradient-based optimization techniques-cannot be computed analytically using standard differentiation rules. We instead develop two computational methods for evaluating this gradient: one involves solving an auxiliary time-delay system forward in time; the other involves solving an auxiliary time-advance system backward in time. On this basis, we propose an efficient optimization algorithm for determining optimal estimates for the time-delays and system parameters. We conclude the paper by examining the performance of this algorithm on a dynamic model of a continuously-stirred tank reactor. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1016/j.automatica.2015.06.028 | Automatica |
Keywords | Field | DocType |
Time-delay,Nonlinear system,Parameter estimation,Dynamic optimization,Nonlinear optimization | Decision variables,Mathematical optimization,Nonlinear system,Control theory,Nonlinear programming,Optimization algorithm,Estimation theory,Optimization problem,Mathematics | Journal |
Volume | Issue | ISSN |
60 | C | 0005-1098 |
Citations | PageRank | References |
6 | 0.47 | 9 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Qun Lin | 1 | 58 | 6.41 |
| R.C. Loxton | 2 | 130 | 16.50 |
| Chao Xu | 3 | 136 | 33.20 |
| K. L. Teo | 4 | 1643 | 211.47 |