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In this work, a new strategy to minimize the use of the network in a closed loop system over networks is addressed, leading to a co-design procedure of the observer, controller and the policy for message sending. The sensor nodes implement a send-on-delta approach, sending new data only when there is a considerable deviation from the last sent measurement. This strategy is useful to minimize the network usage necessities from wireless sensors in order to reduce the energy consumption and to maximize its useful life. The inferential controller node implements a gain scheduling approach that takes into account the availability of new received data to estimate the state and compute the control action. The performance of the closed loop system is analyzed through H∞ norm, and this norm is used to design the gains of the observer and the controller, as well as the output variations that induce the sensors to send new outputs to the estimator node, while guaranteeing a given level of performance on the RMS norm of the controlled state. The design approach is based on an optimization procedure with linear and bilinear matrix inequalities constraints that is solved iteratively.