Intelligent Control

Professors Thomas, Atassi, Corke, Dunn, Goodwine, Jumper, Nelson, Paolucci, Renaud, Sen, & Snider

Challenges: Robust Sensors, High B/W Actuators, DNS/Modeling, NL Control Theory

This is probably the broadest of the groups, and in many ways is the driving force behind the renaissance of fluid dynamics. It involves the complete tripartite approach of experiments, high-fidelity computation, and modeling. With experiments, it involves sensors and actuators. These may be "smart" in that they are integrated with micro-devices which perform real-time processing to react to changing conditions. The scale of these devices will vary from micro to macro to adapt to the fluid scales to be controlled. High-fidelity numerical simulations are essential and preferentially done before designing the experiment. These can pinpoint the best locations, size and measurement quantities that give the greatest sensitivity to the control states. In most cases, optimum control requires having a model for the response of the flow to actuation.

In most fluid flows, the full governing equations do not generally provide a closed-form solution. This prompts the development of lower-order simplified forms. The generation of these simplified models is a powerful predictive tool, and an essential part of close-loop control.

Our research in the area of flow control presently addresses jet noise control; separation control on helicopter rotors and on blades in the low-pressure turbine stage of jet engines; the control of instabilities on the wings of aircraft; and the control of shear layers to reduce optical distortions. These involve funding from the Air Force Office of Scientific Research, the Army Research Office, NASA Langley and Glenn Research Centers, and the Defense Advanced Research Projects Agency, (DARPA), as well as industry partnerships with the United Technology Research Center, Sikorsky Helicopter, and Boeing Aircraft Corporation.