In this paper, we propose an approach to public-private collaborative research in predictive modeling and control of complex engineered systems. Society depends intimately on complex systems. The behavior of a simple system can be modeled and the model can be validated by experimental observations, if the behavior of each component and its interface with other components are known and well-defined. In contrast, a complex system cannot be modeled accurately enough to effectively predict and control the behaviors of the overall system. One example of an engineered complex system network (CSN) is the electricity power grid, which encompasses power generation, transmission, distribution, and consumption, as one giant system that includes electric generators, transformers, substation switchyards, transmission lines, consumer devices, and a multitude of new evolving components. The electricity power grid depends on other complex systems, e.g., climate systems that govern wind current for wind turbines, river water levels for thermoelectric cooling, and economic systems for service demand, pricing, revenue collection, and for business capital supply. Operational robustness, reliability, and efficiency of CSN’s are in the interest of all the subsystem owners, end users, and the public welfare of the nation. Conundrum? Who is responsible for the overall CSN’s operational robustness, reliability and efficiency, when so many parts of the system reside in so many different hands with the ultimate beneficiaries of the systems being the general public? Which entities are responsible for funding critical high-risk research, whose ultimate benefits do not reside with any one subset of stakeholders? These questions characterize the challenge of sourcing R&D funds that can be focused on modeling, understanding, and management of CSNs in general. To address such needs for innovative collaborative research, Congress established the Technology Innovation Program (TIP) at the National Institute of Standards and Technology (NIST) as part of the 2007 America COMPETES Act. Its purpose is to “assist United States businesses and institutions of higher education or other organizations, such as national laboratories and nonprofit research institutions, to support, promote, and accelerate innovation in the United States through high-risk, high-reward research in areas of critical national need.” Ongoing efforts by TIP to identify and qualify societal challenges in the critical national need area of Complex System Networks are introduced.
Intelligent Control Approaches for Modeling and Control of Complex Systems