Model-based iterative learning control with a quadratic criterion for time-varying linear systems (Q1973994)
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scientific article; zbMATH DE number 1441452
| Language | Label | Description | Also known as |
|---|---|---|---|
| English | Model-based iterative learning control with a quadratic criterion for time-varying linear systems |
scientific article; zbMATH DE number 1441452 |
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Model-based iterative learning control with a quadratic criterion for time-varying linear systems (English)
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26 April 2001
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New model-based Iterative Learning Control (ILC) algorithms for time-varying constrained batch chemical processes with disturbances and noises are presented. A sophisticated error transition model between two adjacent batches is introduced. Based on this model, one-batch-ahead optimal control algorithms are derived for unconstrained and constrained cases. In addition, a robust ILC algorithm which minimizes the worst-case tracking error for the next batch is proposed. For each algorithm, relevant basic properties such as the convergence, robustness, and noise sensitivity are investigated. Several examples are selected to demonstrate the advantages of the proposed ILC algorithms.
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predictive control
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iterative learning control
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error transition model
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optimal control
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tracking
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robustness
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sensitivity
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0.90941364
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0.9084579
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0.9079539
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0.90732175
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0.90662783
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