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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Budman, H.M. Holcomb, T. Morari, M. |
| Copyright Year | 1991 |
| Description | Author affiliation: Chemical Engineering 210-41, California Institute of Technology, Pasadena CA 91125. phone (818)356-4186, fax (818)568-8743, e-mail mm@imc.caltech.edu (Morari, M.) || Chemical Engineering 210-41, California Institute of Technology, Pasadena CA 91125 (Budman, H.M.; Holcomb, T.) |
| Abstract | This paper compares the performance of two different inferential schemes when applied to an experimental packed-bed reactor. The first scheme, proposed initially by Brosilow, is designed based on Kalman filter estimation. The second less traditional design uses an estimator computed from the Partial Least Squares regression method (PLS). The second approach was found to give superior performance when the nonlinear system under study is operated is a wide range of operating points. Due to the nonlinearity of the system it is essential to address the issue of robustness of the proposed schemes. This is formally done in this work using Structured Singular Value Theory. For the robustness analysis it is crucial to develop a realistic but not overly conservative uncertainty description. Since the PLS estimator uses a large number of measurements, a robust design based on the uncertainty associated with each one of the measurements would be very conservative. To overcome this problem a lumped uncertainty description is proposed which is identified directly from experiments. |
| Starting Page | 256 |
| Ending Page | 261 |
| File Size | 712939 |
| Page Count | 6 |
| File Format | |
| ISBN | 0879425652 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 1991-06-26 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | American Automatic Control Council(AACC) |
| Subject Keyword | Robust control Inductors Uncertainty Robustness Temperature measurement Chemical engineering Chemical technology Kalman filters Tellurium Electrical equipment industry |
| Content Type | Text |
| Resource Type | Article |
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