Work
NonLinear Programming (NLP): Dynamic optimization
Public DepositedIn this work, we will focus on the “at the same time” or direct transcription approach which allow a simultaneous method for the dynamic optimization problem. In particular, we formulate the dynamic optimization model with orthogonal collocation methods. These methods can also be regarded as a special class of implicit Runge–Kutta (IRK) methods. We apply the concepts and properties of IRK methods to the differential equations directly. With locating potential break points appropriately, this approach can model large-scale optimization formulations with the property of maintaining accurate state and control profiles. We mainly follows Biegler's work.
- Last modified
- 11/30/2018
- Creator
- DOI
- Keyword
- Rights statement
Relationships
- In Collection:
Items
Thumbnail | Title | Date Uploaded | Visibility | Actions |
---|---|---|---|---|
10_Dynamic_optimization_-_optimization.pdf | 2018-11-30 | Public |
|