Regular biography
Professor Alexander Lanzon is a Professor of Control Engineering and Head of Department at the University of Manchester's Department of Electrical and Electronic Engineering. His research interests include robust feedback stability analysis and control, input/output nonlinear control theory, dissipativity, passivity, and negative imaginary systems theory, as well as applications of advanced control methods in robotics, UAVs, and motion systems. He is also the Director of the Control, Dynamics and Robotics Laboratory. Prior to joining the University of Manchester, he held academic and research positions at Georgia Institute of Technology and the Australian National University, as well as industrial roles at ST-Microelectronics Ltd., Yaskawa Denki (Tokyo) Ltd., and National ICT Australia Ltd. He received his Ph.D. and M.Phil. degrees in Control Engineering and Robot Control from the University of Cambridge, and his B.Eng.(Hons) degree in Electrical and Electronic Engineering from the University of Malta. He is a Chartered Engineer and a Fellow of several professional institutions, including the Institute of Mathematics and its Applications, the Institute of Measurement and Control, and the Institution of Engineering and Technology.
Scholar-generated biography
Alexander Lanzon is a Professor of Control Engineering at the University of Manchester, specializing in control systems and their applications. His research focuses on the stability and robustness of interconnected systems, particularly those involving negative imaginary frequency responses. He has contributed significantly to the development of control strategies for multi-agent systems, distributed control, and fault-tolerant control in aerospace and robotics. His work includes the analysis of negative imaginary systems, feedback linearization, and the design of adaptive control approaches for complex dynamic systems such as quadrotor vehicles and multirobot systems. His research has implications for improving the reliability and performance of autonomous systems in challenging environments.