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        A New Decentralized Implicit Adaptive Regulator for Large-scale Systems Described by Discrete-time State-space Mathematical Models

        Samira Kamoun,Mohamed Kamoun 제어·로봇·시스템학회 2016 International Journal of Control, Automation, and Vol.14 No.3

        In this paper, we treat the problem of decentralized implicit adaptive regulation for large-scale stochasticsystems composed into a set of interconnected systems that are described by discrete-time state-space mathematicalmodels with unknown parameters. The key idea in the decentralized regulation method is to design localregulator using only local information such that the state of each interconnected system is regulated to a certainconstant reference signal. The main contribution is the proposition of a decentralized implicit adaptive regulatorbased on state-feedback strategy that can be applied to stochastic interconnected systems with unknown parameters. Furthermore, the practical implementation of the proposed decentralized implicit adaptive regulator can be madeeasily (low-cost implementation of the electronic components, short computation of the decentralized control law,etc.). A theorem is established and proved which gives sufficient stability conditions of the resulting closed-loopinterconnected systems by using the Lyapunov method. An example of numerical simulation is treated to test theperformance of the proposed decentralized implicit adaptive regulator.

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