Professor John Norton

John Norton graduated from Cambridge in 1962, worked in industry as a digital designer then carried out research on control of high-voltage dc power systems for a PhD at Imperial College. From 1967 to 1971 he was a research fellow at the National Physical Laboratory and Warren Spring Laboratory, working on process-control problems in the steel and paper industries. 

This strengthened an interest in techniques for identifying mathematical models of dynamical systems. A period in the Dept. of Electrical Engineering at the University of Tasmania between 1971 and 1979 included hydrological modelling for the Hydro-Electric Commission of Tasmania, leading to new methods of handling complex dynamics by identifying linear, time-varying models. 

Since 1979 he has been at the University of Birmingham, forming the Estimation and Control Group in 1985. Applied work has included long-term research with Rolls-Royce, Derby on gas turbine modelling, and with BAE Systems, Filton and QinetiQ/dstl (formerly DERA) at Malvern and Farnborough on target tracking, guidance and related topics. Since 1992 collaboration with the Centre for Resource and Environmental Studies at the Australian National University has covered a range of environmental modelling applications. 

He is an Adjunct Professor at ANU and is currently acting as an interface between the Mathematical Sciences Institute and the Integrated Catchment Assessment & Management Centre.

He has been Editor for Adaptive Control of Int. J. of Adaptive Control & Signal Processing and editorial board member of that journal, J. of System & Control Engineering and Environmental Modelling & Software. Since 1995 he has been a member of the IFAC Technical Committee on Modelling, Identification and Signal Processing.

Recent and current research interests:

• state bounding

• Bayesian recursive state estimation by Monte Carlo methods

• robust state estimation and incorporation of collateral knowledge (e.g. of target manoeuvre capability) into state estimation

• identification of abrupt changes in input or state of dynamical systems

• identification of gas-turbine dynamics

• estimators insensitive to outliers

• sensitivity assessment of integrated hydrological/land-use/economics models

• quantification of uncertainty in prediction models

Pulications (since 1990) List