The paper deals with the problem of designing controllers from experimental data. We propose a non-iterative direct approach in which the parameters of a controller of a prescribed order and structure are optimized with respect to a relevant performance criterion. The proposed approach builds upon the so-called unfalsified control theory. This is the key point which makes it possible to derive simple and intuitive relations between the choice of the performance criterion to optimize and closed-loop stability conditions, thus making it possible to derive a data-driven controller tuning procedure incorporating simple stability tests. An example is presented to substantiate the analysis.
Unfalsified Approach to Data-Driven Control Design / G. Battistelli; D. Mari; D. Selvi; P. Tesi. - ELETTRONICO. - (2014), pp. 6003-6008. (Intervento presentato al convegno 53rd IEEE Conference on Decision and Control, CDC 2014 tenutosi a Los Angeles, California, USA nel December 15-17, 2014) [10.1109/CDC.2014.7040329].
Unfalsified Approach to Data-Driven Control Design
BATTISTELLI, GIORGIO;MARI, DANIELE;SELVI, DANIELA;TESI, PIETRO
2014
Abstract
The paper deals with the problem of designing controllers from experimental data. We propose a non-iterative direct approach in which the parameters of a controller of a prescribed order and structure are optimized with respect to a relevant performance criterion. The proposed approach builds upon the so-called unfalsified control theory. This is the key point which makes it possible to derive simple and intuitive relations between the choice of the performance criterion to optimize and closed-loop stability conditions, thus making it possible to derive a data-driven controller tuning procedure incorporating simple stability tests. An example is presented to substantiate the analysis.
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