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Finite-Time distributed Identification for Nonlinear Interconnected Systems

IEEE/CAA Journal of Automatica Sinica 2022年第7期9卷 1188-1199页

作者： Farzaneh Tatari Hamidreza Modares Christos Panayiotou Marios Polycarpou Mechanical Engineering Department Michigan State UniversityEast LansingMI 48824 USA KIOS Research and Innovation Center of Excellence and the Department of Electrical and Computer Engineering University of CyprusNicosia 1678Cyprus IEEE

In this paper,a novel finite-time distributed identification method is introduced for nonlinear interconnected systems.A distributed concurrent learning-based discontinuous gradient descent update law is presented to learn uncertain interconnected subsystems’*** concurrent learning approach continually minimizes the identification error for a batch of previously recorded data collected from each subsystem as well as its neighboring *** state information of neighboring interconnected subsystems is acquired through direct *** overall update laws for all subsystems form coupled continuous-time gradient flow dynamics for which finite-time Lyapunov stability analysis is *** a byproduct of this Lyapunov analysis,easy-to-check rank conditions on data stored in the distributed memories of subsystems are obtained,under which finite-time stability of the distributed identifier is *** rank conditions replace the restrictive persistence of excitation(PE)conditions which are hard and even impossible to achieve and verify for interconnected ***,simulation results verify the effectiveness of the presented distributed method in comparison with the other methods.

关键词： distributed concurrent learning finite-time identification nonlinear interconnected systems unknown dynamics

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