CAREER: A new generation of scalable intelligent supervisory loop based algorithm for complex system control and optimization

(CAREER Proposal: 0748238, PI: Sukumar Kamalasadan)

Abstract

The objective of this research is to develop a new class of intelligent adaptive control architecture with scalable algorithms for complex systems control and optimization. The approach is to provide a unified control framework using an introduced system supervision concept that coherently incorporates adaptive controller and intelligent learning schemes with special emphasis on control of power system dynamics.

Intellectual Merit:

The intellectual merit is in extensive design, development and evaluation of a next generation intelligent control paradigm. Modern power systems are becoming increasingly stressed, due to growing demand and deregulation. An important solution for the control of modern power network is to provide intelligent hybrid frameworks that are adaptable to dynamic environment (system-centric). The goal of this CAREER program is to develop such a novel architecture based on the concept of supervisory loops that monitor system dynamics. The result is a resilient control framework that can adapt seamlessly to both designed and emergent conditions.

Broader Impact:

The broader impact includes a potential breakthrough in emerging and largely untapped system-centric controllers for seamless integration of renewable and non-renewable energy sources; economic and viable continuous power dispatch; sustainable and transportable next generation energy systems; and security against power disruptions caused by inadvertent events or malicious intent. As these approaches are important in many other areas of scientific applications, they will therefore have global value. This research also present unique opportunities to student researchers, especially from under-represented and minority groups and foster inter- and cross- disciplinary research collaborations with academic and scientific laboratories.