Informatik, TU Wien

Active Fault Diagnosis for Uncertain Systems

Component malfunctions and other faults pose a significant threat to the safety and efficiency of complex systems, such as aircrafts, power systems, and chemical plants.

Abstract

Component malfunctions and other faults pose a significant threat to the safety and efficiency of complex systems, such as aircrafts, power systems, and chemical plants. For these reasons, many methods have been developed to determine whether or not a fault has occured (fault detection) and, if so, the nature of the fault (fault diagnosis). The vast majority of these methods are passive, meaning that the fault status is decided on the basis of input-output data acquired during normal control operation. However, faults are not always detectable at normal operating conditions, or are obscured by the action of the control system itself. Active fault diagnosis involves injecting a suitably designed input into the system to improve the detectability and diagnosability of potential faults. The use of such inputs has clear potential for overcoming a central difficulty in fault detection, which is to distinguish the effects of faults from those of disturbances, process uncertainties, etc.

This presentation discusses new methods for computing active inputs that guarantee that the input-output data of a process will be sufficient to correctly identify a fault from a given library of possible faults. To address this problem, a new formulation is considered, along with related approximations, that is amenable to efficient solution using standard optimization packages (e.g. CPLEX). The theoretical contributions combine ideas from reachability analysis, set-based computations, and optimization theory to exploit detailed problem structure and thereby manage the problem complexity.

Biography

Davide M. Raimondo was born in Pavia, Italy, in 1981. He received the B.Sc. and M.Sc. in Computer Engineering, and the Ph.D. in Electronic, Computer Science and Electric Engineering from the University of Pavia, Italy, in 2003, 2005, and 2009, respectively. As a Ph.D. student he held a visiting position at the Department of Automation and Systems Engineering, University of Seville, Spain. From January 2009 to December 2010 he was a postdoctoral fellow in the Automatic Control Laboratory, ETH Zürich, Switzerland. From March 2012 to June 2012 and from August 2013 to September 2013 he was visiting scholar in Prof. Braatz Group, Department of Chemical Engineering, MIT, USA. Since December 2010 he is Assistant Professor at University of Pavia, Italy.

He is the author or co-author of more than 50 papers published in refereed journals, edited books, and refereed conference proceedings. His current research interests include control of nonlinear constrained systems, robust control, networked control, fault-tolerant control, autonomous surveillance and control of glycaemia in diabetic patients.

Dr. Raimondo co-organized the NMPC Workshop on Assessment and Future Direction, Pavia, Italy, in 2008. He was also co-organizer of the invited sessions Nonlinear Model Predictive Control, for IFAC NOLCOS 2010, and New Developments in Nonlinear Model Predictive Control, for IFAC NOLCOS 2007. He served as an Associate Editor of IFAC NOLCOS 2010 and as member of the Nonlinear Model Predictive Control 2012 (NMPC'12) and European Control Conference 2013 (ECC'13) and 2014 (ECC'14) International Program Committees.
 

Note

This talk is organized by the Vienna PhD School of Informatics and part of the lecture series "Current Trends in Computer Science".