Online optimization for batch processes given uncertain estimates
A cautious corrector that incorporates uncertainty of state estimates into online batch optimization is presented. Its single scaler tuning parameter represents the desired degree of cautiousness or boldness with which current estimates are used for online correction of open-loop optimized input pro...
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| Format: | Tagungsbericht |
| Sprache: | eng |
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| Zusammenfassung: | A cautious corrector that incorporates uncertainty of state estimates into online batch optimization is presented. Its single scaler tuning parameter represents the desired degree of cautiousness or boldness with which current estimates are used for online correction of open-loop optimized input profiles. In the limiting cases of no information (large uncertainty) and perfect information (certainty), the corrector naturally reduces to optimal open-loop and optimal feedback operation, respectively. |
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| DOI: | 10.1109/ACC.1994.751784 |