Comparison of Gradient Estimation Methods for Real-time Optimization

Bala Srinivasan*, Grégory François, Dominique Bonvin

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review


Various real-time optimization techniques proceed by controlling the gradient to zero. These methods primarily differ in the way the gradient is estimated. This paper compares various gradient estimation methods. It is argued that methods with model-based gradient estimation converge faster but can be inaccurate in the presence of plant-model mismatch. In contrast, model-free methods are accurate but typically take longer to converge.

Original languageEnglish
Pages (from-to)607-611
Number of pages5
JournalComputer-Aided Chemical Engineering
Publication statusPublished - 2011


  • Extremum-seeking control
  • Gradient estimation
  • Neighboring extremals
  • Real-time optimization
  • Self-optimizing control

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