IES Webinar Series

Supercapacitor applications

Tuesday, Jan 31, 2023 8:00 AM NZDT (Monday Jan 30, 2023 8:00 PM CET - 2:00 PM EST) by Prof. Nihal Kularatna (University of Waikato, Hamilton, New Zealand) Register now using the link below: https://attendee.gotowebinar.com/register/1601114757658989407 Abstract: Supercapacitors come with one million times larger capacitance for the same canister size as normal capacitors.  They have very low equivalent series resistance (ESR), and this makes them capable of delivering high power. Given that supercapacitors have low ESR and very large capacitance, they could form large time constant circuits, and also act as lossless voltage droppers in power electronic converters. Based on these simple concepts, supercapacitors can help developing uniquely new families of extra low frequency power converters and protection circuits, now identified as Supercapacitor Assisted (SCA) techniques. This presentation summarizes these SCA techniques, and compare them with traditional power electronic building blocks. Presenter's bio: Nihal Kularatna is an associate professor in electronic engineering at the School of Engineering, University of Waikato, New Zealand. He has authored ten reference books for electronic engineers, published by US and British publishers. Latest work is titled Energy storage devices for renewable energy systems”.   He is research active in supercapacitor applications, and he won the New ...
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Learning for Advanced Motion Control

Monday, 16 January 2023 2:00 PM CET (8:00 AM EST) by Prof. Tom Oomen (Eindhoven University of Technology, The Netherlands) Register now using the link below: https://attendee.gotowebinar.com/register/4941532237492244235 Abstract: Do you also have a motion system that has the same error in each task? Iterative Learning Control (ILC) can achieve perfect performance for your system. A general learning framework is presented that exploits measured error signals from previous tasks. By employing very simple models, both fast and safe learning is achieved, guaranteeing a reduction of the error in each experiment. Typically, perfect performance is achieved in only five to ten iterations. A complete design framework for motion systems is provided, while at the same time touching upon the essential theoretical foundations, including non-causality of the optimal design and the connection to traditional feedback and feedforward designs. Finally, recent approaches are explored that facilitate the implementation on industrial systems, including flexibility for a large class of tasks and multivariable systems. Presenter's bio: Tom Oomen is full professor with the Department of Mechanical Engineering at the Eindhoven University of Technology. He is also a part-time full professor with the Delft University of Technology. He received the M.Sc. degree (cum laude) and Ph.D. degree from ...
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