EAGER:Real-Time:Automated Control-Assisted Data-Based Model Development for Real-Time Feedback Control

Wayne State University, Detroit MI

Investigators

Abstract

The future economic competitiveness of the US process industries requires the successful implementation of next-generation controllers to optimize process economic performance in real time and account for both safety considerations and traditionally-neglected dynamics that can significantly impact control loop performance. The proposed exploratory research aims to develop a novel, automated, control-assisted methodology for building physics-based models from on-line data and formulating next-generation controllers for real-time applications. If successful, the proposed research can potentially have an impact in a broad spectrum of chemical process industries. Techniques for developing models from data are currently limited by the state measurement information provided to a model identification procedure and by the structure assumed to represent the system dynamics. Therefore, the ability to derive physics-based models for control design from process state/input measurements requires methods for obtaining appropriate data from which the correct model structures can be deduced. The proposed research will : a) develop a control-assisted framework for obtaining on-line operating data from a process that is conducive to developing a physics-based model; b) develop methods for relating mathematical function structure to operating data trends; c) explore potential analogy or machine learning-based computation time reduction techniques for partial differential equation models in optimization-based control; d) develop controller update techniques which facilitate automated development of functions or parameters used in the control law design; and e) demonstrate the developed methods utilizing chemical process simulations of high fidelity process models to investigate the potential of the developed techniques to promote automated physics-based model development for use in developing model-based controllers for real-time applications. Interactions with industry are proposed to validate the proposed methodologies and broad dissemination of results via the web is planned. In addition to training graduate and undergraduate students in research, curriculum development and outreach activities to middle- and high-school students as well as the general public are proposed focused on engaging a broader audience and encouraging underrepresented minorities to pursue careers in engineering. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.