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A Real-Time Optimization Framework for the Iterative Controller Tuning Problem

Laboratoire d'Automatique, Ecole Polytechnique Fédérale de Lausanne, Lausanne CH-1015, Switzerland
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Processes 2013, 1(2), 203-237; https://doi.org/10.3390/pr1020203
Received: 7 June 2013 / Revised: 1 August 2013 / Accepted: 27 August 2013 / Published: 12 September 2013
(This article belongs to the Special Issue Feature Papers)
We investigate the general iterative controller tuning (ICT) problem, where the task is to find a set of controller parameters that optimize some user-defined performance metric when the same control task is to be carried out repeatedly. Following a repeatability assumption on the system, we show that the ICT problem may be formulated as a real-time optimization (RTO) problem, thus allowing for the ICT problem to be solved in the RTO framework, which is both very flexible and comes with strong theoretical guarantees. In particular, we propose the use of a recently released RTO solver and outline a simple procedure for how this solver may be configured to solve ICT problems. The effectiveness of the proposed method is illustrated by successfully applying it to four case studies—two experimental and two simulated—that cover the tuning of model-predictive, general fixed-order and PID controllers, as well as a system of controllers working in parallel. View Full-Text
Keywords: controller autotuning; real-time optimization; data-driven tuning methods controller autotuning; real-time optimization; data-driven tuning methods
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MDPI and ACS Style

Bunin, G.A.; François, G.; Bonvin, D. A Real-Time Optimization Framework for the Iterative Controller Tuning Problem. Processes 2013, 1, 203-237. https://doi.org/10.3390/pr1020203

AMA Style

Bunin GA, François G, Bonvin D. A Real-Time Optimization Framework for the Iterative Controller Tuning Problem. Processes. 2013; 1(2):203-237. https://doi.org/10.3390/pr1020203

Chicago/Turabian Style

Bunin, Gene A., Grégory François, and Dominique Bonvin. 2013. "A Real-Time Optimization Framework for the Iterative Controller Tuning Problem" Processes 1, no. 2: 203-237. https://doi.org/10.3390/pr1020203

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