Note: This content is accessible to all versions of every browser. However, this browser does not seem to support current Web standards, preventing the display of our site's design details.

  

Low-order models for control and estimation of infinite-dimensional systems, with applications to fluid dynamics

Back
Abstract:
One of the main challenges when designing a controller or estimator for an infinite-dimensional system, such as those described by PDEs or time-delay systems, is how to obtain a low order model that captures the dynamics essential for closed-loop design. The standard approach of first obtaining a high-order model, which is typically followed with the computation of a reduced-order model, is computationally expensive and also does not come with guarantees that the closed-loop system will be stable. We will present a novel method, based on the gap metric, for directly obtaining a low-order model without first computing a high-order model, while also providing guarantees on the robustness of the closed-loop system.

The results that we will present have been motivated by recent research done at Imperial College London on the control and estimation of fluid dynamical systems. We will demonstrate the efficacy of our new method by applying it to the design of a perturbation shear stress controller for plane channel flow, where there are arrays of wall mounted shear tress sensors and transpiration actuators. Nonlinear simulations demonstrate robust attenuation of the perturbation shear-stresses across a wide range of Reynolds numbers.

Type of Seminar:
IfA Seminar
Speaker:
Dr. Eric Kerrigan
Electrical and Electronic Engineering and Aeronautics, Imperial College, London
Date/Time:
Jan 11, 2013   11:15
Location:

ETZ E 8, Gloriastr. 35
Contact Person:

Prof. John Lygeros
File Download:

Request a copy of this publication.
Biographical Sketch:
Dr. Eric Kerrigan joined Imperial College London in 2006, where he has a joint faculty appointment in the Department of Electrical and Electronic Engineering and the Department of Aeronautics. From 2001-2005 he was a Research Fellow at the Department of Engineering, University of Cambridge, where he obtained a PhD in 2001.

His current research is focused on the development of efficient numerical methods and computational architectures for solving control, estimation, modeling and optimization problems that arise in a variety of problems in aerospace and renewable energy. His research is funded by the Engineering and Physical Sciences Research Council, the European Commission, Xilinx, The Mathworks, National Instruments and the European Space Agency.

He is a Member of the IEEE, IET and SIAM and is an associate editor of the IEEE Transactions on Control Systems Technology, Control Engineering Practice and Optimal Control Applications and Methods.