This paper proposes new conditions for the design of a robust partial sampled-data state feedback control law for Markov jump linear systems (MJLS). Although, as usual, the control structure depends on the Markov mode, only the state variable is sampled in order to cope with a specific network control structure. For analysis, an equivalent hybrid system is proposed and a two-point boundary value problem (TPBVP) that ensures minimum H ∞ or H 2 cost is defined. For control synthesis, it is rewritten as a convex set of sufficient conditions leading to minimum guaranteed cost of the mentioned performance classes. The optimality conditions are expressed through differential linear matrix inequalities (DLMIs), a useful mathematical device that can be handled by means of any available LMI solver. Examples are included for illustration.

Imitation dynamics in population games are a class of evolutionary game-theoretic models, widely used to study decision-making processes in social groups. Different from other models, imitation dynamics allow players to have minimal information on the structure of the game they are playing, and are thus suitable for many applications, including traffic management, marketing, and disease control. In this work, we study a general case of imitation dynamics where the structure of the game and the imitation mechanisms change in time due to external factors, such as weather conditions or social trends. These changes are modeled using a continuoustime Markov jump process. We present tools to identify the dominant strategy that emerges from the dynamics through methodological analysis of the function parameters. Numerical simulations are provided to support our theoretical findings.

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Lithium-air batteries performance faces a challenge on the design and development of a functional cathode. Manganese dioxide is a promising material for the air cathode, due to its low cost and ability to catalyse oxygen reactions. In its preparation residues are generated that need to be treated before discard. The present study aims to prepare the manganese dioxide through a precipitation/annealing method, using as raw-material manganese based waste from electrodeposition baths utilized in a previous study, in order to synthesize novel MnOx based electrodes.

The development of new energy storage technologies is the next step toward sustainability, mainly for the automotive environment, which contributes highly to greenhouse -gases emissions. In the present work, an air-cathode for the lithium-oxygen batteries was developed by electrodeposition of manganese oxide on a stainless-steel net, and then cycled at different current densities. The capacity obtained was lower than that of lithium-ion batteries, but the research revealed paths for improvements for future works.