December 11, 2014, ESB 2001

Continuous-time adaptation algorithms in general either introduce robustness or provide convergence to the true value: Robustness is usually achieved by a forgetting factor, which causes ultimate boundedness in estimation or control, while convergence to the true parameter values is strictly not possible. The removal of this forgetting factor renders the adaptation algorithm to be semi-stable while the existence of persistent excitation permits the convergence to the true parameters. This talk will present the theoretical framework of an adaptation algorithm which permits a data forgetting mechanism and robustness to bounded disturbances and uncertainty, while achieving convergence to the true parameter in the absence of disturbances. The algorithm can be easily modified to achieve exponential or finite-time convergence under the assumption of persistent excitation or under the weaker assumption of sufficient richness in the demand. The talk will provide examples of this algorithm in application to a novel adaptive finite-time leader-following control, where leader-following control and parameter adaptation are achieved both within finite time. A second example will show how this adaptation algorithm, now in an exponential stability setting, can be used for a novel adaptive approximate optimal tracking control. Practical implementations, both in the field of humanoid robotics, will provide experimental proof of the robustness of the suggested adaptation algorithm.

Dr Guido Herrmann received the German degree “Diplom-Ingenieur der Elektrotechnik” (with highest honours) from the Technische Universität zu Berlin, Germany, and the Ph.D. degree from the University of Leicester, UK, in 1997 and 2001, respectively. From 2001 to 2003, he was a Senior Research Fellow at the Data Storage Institute in Singapore. From 2003 until 2005, he was a Research Associate, Fellow, and Lecturer at the University of Leicester. He joined the University of Bristol, Bristol, UK, as a Lecturer in March 2007, and was a Senior Lecturer from August 2009 until August 2012. In August 2012, he was promoted to the position of a Reader in Control and Dynamics (Associate Professor). He was at several occasions invited to visit Universities and research institutes in the USA, China, Malaysia and Singapore to work with academics such as Professors Frank L Lewis and Sam S Ge. His research considers the development and application of novel, robust and nonlinear control systems. He published more than 150 papers. He is editor of two books and author of one book on “Optimal and Robust Scheduling for Networked Control Systems” (Mar 20, 2013). Dr Herrmann’s PhD-student Dr S Stefano Longo, first author of the latter book, received the IET 2011 Control PhD Award for his work in the area of networked control systems. Dr Herrmann was main advisor of seven Doctorate Degree holders and co-advisor of another six Doctorate Degree holders. His research portfolio as principal investigator amounts to £ ~1,000,000 (£ 3,272,200 as co-investigator). He is a Senior Member of the IEEE, a Technical Editor of the IEEE/ASME Transactions on Mechatronics and an Associate Editor of the International Journal on Social Robotics. He is leading the Nonlinear Robotics Control Group (NRCG) at the Bristol Robotics Laboratory.