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. Copyright (c) 2017 John Wiley & Sons, Ltd.
Direct Control Design via Controller Unfalsification
2018-08-01
Battistelli , G , Mari , D , Selvi , D & Tesi , P 2018 , ' Direct Control Design via Controller Unfalsification ' , International Journal of Robust and Nonlinear Control , vol. 28 , no. 12 , pp. 3694-3712 . https://doi.org/10.1002/rnc.3778
Article (Journal)
Electronic Resource
English
DDC: | 629 |
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