Direct Control Design via Controller Unfalsification

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.