Dynamic flexibility analysis aims to describe the operability (controllability, resiliency) of dynamic process systems subject to uncertainties, thus facilitating the integration of process design and control. However, the intrinsic limitations of controllability indices and the computational intractability of the optimization formulations in the state-of-the-art approaches largely prohibit their applicability to large-scale nonlinear processes. In this work, we propose a new framework for dynamic flexibility analysis, where a Lyapunov function is considered as an artificial design decision, so that the feasibility and cost of process operation can be evaluated based on estimating the effect of the uncertainties on the Lyapunov function value. The proposed approach leads to computationally efficient optimization formulations for the flexibility test, flexibility index and optimal process design problems under nonlinear dynamics. A preliminary case study is performed on a two-reactor system.
|Original language||English (US)|
|Title of host publication||Computer Aided Chemical Engineering|
|Number of pages||6|
|State||Published - 2019|
|Name||Computer Aided Chemical Engineering|
Bibliographical noteFunding Information:
Financial support from NSF-CBET and Doctoral Dissertation Fellowship of University of Minnesota is gratefully acknowledged.
© 2019 Elsevier B.V.
- Dynamic flexibility
- Integrated design and control
- Lyapunov function