Partial Sampled-Data State Feedback Control of Markov Jump Linear Systems

This paper aims at designing a partial sampled-data state feedback control law for Markov jump linear systems (MJLS). The interesting feature of the control structure is that only the state variable is sampled, while the stochastic parameter that defines the Markov mode of the system used for control purposes is free to change at any time between samples. The main goal is to provide sufficient convex conditions for the existence of a solution for this class of control design problems in the context of H-infinity and H-2 performances, which are expressed through Differential Linear Matrix Inequalities (DLMI). The proposed method is implemented using LMIs facilities and provides a minimum guaranteed cost control in only one shot. An example is solved for illustration and comparison. (C) 2018, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.