Structured uncertainty modelling for robust control

In safety-critical applications it is expected that stability and performance are guaranteed even if the system dynamics are subjected to disturbances and uncertainties. Mu-synthesis methods are well known, powerful tools of designing robust feedback controllers for complex systems where uncertainties are modelled by structured sets. The book extends the Mu-synthesis framework by addressing the problem from the data-based modelling side. The book tries to characterize the way how to arrive at an efficient description of structured uncertainties and disturbances for complex systems that is not in-validated by experimental data, and is optimized for robust performance. The book leads the reader to the fields of research known as robust control, and iterative identification and control. Based on these disciplines it develops an optimization technique which facilitates both uncertainty modelling and robust feedback control design in order to achieve improved robust performance of the controlled system.

Autorentext

Dr. Gábor Rödönyi, PhD: Studied systems theory at Budapest University of Technology. He is a research fellow in the Systems and Control Laboratory, MTA SZTAKI. He has worked in different research and industrial projects in the field of control and identification of linear parameter-varying systems, applied mainly in automotive and aerospace.