Adaptive Differentiating Filter: a solution to the sensitivity trade-off
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Abstract: In many control and process monitoring applications, one needs to estimate the derivative of a signal. Standard differentiating filters commonly suffer from the trade-off: reducing the filter bandwidth to improve noise sensitivity also reduces it for the useful signal, leading to smoothed-out high-frequency peaks of the useful signal. In this talk, we present the Adaptive Differentiating Filter (ADF) – a causal real-time filter which solves this trade-off problem. It demonstrates low sensitivity to low-amplitude/high frequency measurement noise, while preserving a wide bandwidth for large-amplitude changes in the process signal. The presentation discusses and demonstrates the filter's favourable performance properties in two practical case-studies: 1) a PID feedback controller for a mechatronic application and 2) monitoring of industrial process signals. It also compares it experimentally with a standard linear low-pass filter-based differentiator and a state-of-the-art robust sliding-mode-based homogeneous differentiator. Bio: Alexey Pavlov obtained his M.Sc. degree (cum laude) in Applied Mathematics from St. Petersburg State University, Russia, and Ph.D. degree in Mechanical Engineering from Eindhoven University of Technology, The Netherlands in 1998 and 2004, respectively. Currently, he holds a full professor position at the Department of Geosciences of the Norwegian University of Science and Technology (NTNU). Prior to that, he held various academic and industrial positions at the Institute for Problems of Mechanical Engineering, Russia (1999), Ford Research Laboratory, USA (2000), Eindhoven University of Technology (2005), NTNU (2005–2009), Equinor Research Centre, Norway (2009–2016). He published the book ’Uniform Output Regulation of Nonlinear Systems: A convergent Dynamics Approach’ with N. van de Wouw and H. Nijmeijer (Birkhauser, 2005). Alexey received the IEEE Control Systems Technology Award (2015) ‘‘For the development and application of variable-gain control techniques for high-performance motion systems’’ (together with M. Heertjes, H. Nijmeijer and N. van de Wouw), and the IFAC World Congress Best Application Paper Award (2011) for the work ‘‘Drilling seeking automatic control solutions”. His inventions within automatic optimization are implemented and used in several offshore fields. His current research interests include control of nonlinear systems, control and optimization of highly uncertain systems, automation and digitalization in the energy industry and various industrial applications of automatic control and optimization.
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