Francisco R. RubioPablo MillánLuís OrihuelaCarlos Vivas2026-03-222026-03-22201410.1016/j.riai.2014.08.001https://doi.org/10.1016/j.riai.2014.08.001https://andeanlibrary.org/handle/123456789/50687Citaciones: 5This paper's aim is to present a novel design technique for distributed control and estimation in networked systems. The proposed problem considers a large scale, discrete LTI process controlled by a network of agents that may both, collect information about the evolution of the plant, and apply control actions to drive its behavior. The problem makes full sense when local observability/controllability is not assumed and the communication between agents can be exploited to reach system-wide goals, including energy efficiency in these communications. The objective is to provide a fully distributed estimation&control scheme that stabilizes the plant while the upper bound of a given quadratic performance index is minimized.The paper analyzes two different sampling schemes, periodic and event-driven, providing stability proofs based on Lyapunov theory and design methods in terms of LMIs. Experimental results on a four couple tanks system are provided to show the performance of the proposed methodologies.esObservabilityControllabilityComputer scienceStability (learning theory)Control theory (sociology)Scheme (mathematics)Control (management)Mathematical proofController (irrigation)Lyapunov functionarticle