Performance evaluation of sampled-data control of Markov jump linear systems. (December 2017)

• Record Type: Journal Article
• Authors: Gabriel, Gabriela W.; Geromel, José C.
• Is Part Of: Automatica. Volume 86(2017)
• Page Start: 212
• Page End: 215
• Publication Date: 2017-12
• Subjects: Sampled-data control -- Hybrid systems -- Markov processes -- Optimal control; Automatic control -- Periodicals; Automation -- Periodicals; 629.805
• DOI: 10.1016/j.automatica.2017.08.015
• Languages: English
• ISSNs: 0005-1098

Abstract

Abstract: This technical communique extends the recent results of Geromel and Gabriel (2015) to H ∞ sampled-data control design of Markov jump linear systems (MJLS). It fulfills a lack of a specific necessary and sufficient result in the literature of sampled-data control of MJLS in the context of H ∞ performance. Mean square stabilizability and performance determination are addressed and discussed in a unified theoretical viewpoint. As a natural consequence, it is shown that the previous result of Geromel and Gabriel (2015) is obtained as a particular case. A globally uniformly convergent algorithm is proposed to solve the design conditions. The theory is illustrated by means of an example.