Abstract
This 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.
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