Abstract
A pattern recognition approach to process identification is proposed in this paper. The process identification problem is first formulated using a nonlinear regression model which is solved according to the nonlinear least squares estimator. The method is then extended via the instrumental variable method to cater for possible correlation of residual error with a Jacobian function. The conditions for the identification are derived. Simulation results are also presented for the methods proposed.
Original language | English |
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Pages | 966-970 |
Number of pages | 5 |
Publication status | Published - 1995 |
Event | Proceedings of the 1994 IEEE Region 10's 9th Annual International Conference (TENCON'94). Part 1 (of 2) - Singapore, Singapore Duration: 1994 Aug 22 → 1994 Aug 26 |
Other
Other | Proceedings of the 1994 IEEE Region 10's 9th Annual International Conference (TENCON'94). Part 1 (of 2) |
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City | Singapore, Singapore |
Period | 94/8/22 → 94/8/26 |
All Science Journal Classification (ASJC) codes
- Computer Science Applications
- Electrical and Electronic Engineering