Zobrazeno 1 - 10
of 27
pro vyhledávání: '"Abhinav Narasingam"'
Publikováno v:
Journal of Process Control. 118:26-36
Publikováno v:
International Journal of Control. 96:770-781
Publikováno v:
Fluids, Vol 4, Iss 3, p 138 (2019)
Learning reservoir flow dynamics is of primary importance in creating robust predictive models for reservoir management including hydraulic fracturing processes. Physics-based models are to a certain extent exact, but they entail heavy computational
Externí odkaz:
https://doaj.org/article/ffc68c2fbf3f47fe859b5c7855b14b4d
Publikováno v:
Journal of Process Control. 91:25-36
This work explores the application of the recently developed Koopman operator approach for model identification and feedback control of a hydraulic fracturing process. Controlling fracture propagation and proppant transport with precision is a challe
Publikováno v:
Chemical Engineering Research and Design. 152:372-383
Many of the existing offline system identification methods cannot completely comprehend the dynamics of an evolving complex process without relying on impractically large data sets. As a solution to this, a systematic procedure capable of identifying
Publikováno v:
Industrial & Engineering Chemistry Research. 58:5588-5601
The local dynamic mode decomposition with control (LDMDc) technique combines the concept of unsupervised learning and the DMDc technique to extract the relevant local dynamics associated with highly nonlinear processes to build temporally local reduc
Publikováno v:
ACC
Koopman operator is an infinite-dimensional linear operator that governs the evolution of observable functions along trajectories of a given nonlinear dynamical system. Recently, several predictive control methods utilizing data-driven approximation
Closed-loop stabilization of nonlinear systems using Koopman Lyapunov-based model predictive control
Publikováno v:
CDC
This work considers the problem of stabilizing feedback control design for nonlinear systems. To achieve this, we integrate Koopman operator theory with Lyapunov-based model predictive control (LMPC). A bilinear representation of the nonlinear dynami
Publikováno v:
AIChE Journal. 66
Publikováno v:
ACC
The moving boundary nature of hydraulic fracturing process makes it extremely difficult to approximate using local models (i.e., approximate models whose validity is limited by the training data). In this work, we implement the Koopman operator metho