This paper proposes a non-iterative direct approach for controller design from experimental data; the parameters of a controller of a prescribed order and structure are optimized with respect to a relevant performance criterion. The proposed design method enjoys the following features: (i) It does not involve the identification of the process to be controlled; (ii) it only requires a single experiment; (iii) in the case of stable plants, no initial controller is needed even when the process to be controlled is non-minimum phase; and (iv) it provides sufficient conditions for the resulting closed-loop system to be stable. The approach builds upon the so-called unfalsified control theory; this key point makes it possible to derive simple and intuitive relations between the choice of the performance criterion to be optimized and closed-loop stability conditions. The analysis is supported by numerical examples.
Direct Control Design via Controller Unfalsification / Battistelli, Giorgio; Mari, Daniele; Selvi, Daniela; Tesi, Pietro. - In: INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL. - ISSN 1049-8923. - STAMPA. - 28:(2018), pp. 3694-3712. [10.1002/rnc.3778]
Direct Control Design via Controller Unfalsification
BATTISTELLI, GIORGIO;MARI, DANIELE;SELVI, DANIELA;TESI, PIETRO
2018
Abstract
This paper proposes a non-iterative direct approach for controller design from experimental data; the parameters of a controller of a prescribed order and structure are optimized with respect to a relevant performance criterion. The proposed design method enjoys the following features: (i) It does not involve the identification of the process to be controlled; (ii) it only requires a single experiment; (iii) in the case of stable plants, no initial controller is needed even when the process to be controlled is non-minimum phase; and (iv) it provides sufficient conditions for the resulting closed-loop system to be stable. The approach builds upon the so-called unfalsified control theory; this key point makes it possible to derive simple and intuitive relations between the choice of the performance criterion to be optimized and closed-loop stability conditions. The analysis is supported by numerical examples.File | Dimensione | Formato | |
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