Neural Network Based Finite-Time Stabilization for Discrete-Time Markov Jump Nonlinear Systems with Time Delays | Zendy

Fei Chen | Zendy; Fei Liu | Zendy; Hamid Reza Karimi | Zendy

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Neural Network Based Finite-Time Stabilization for Discrete-Time Markov Jump Nonlinear Systems with Time Delays

Author(s) -

Fei Chen,

Fei Liu,

Hamid Reza Karimi

Publication year - 2013

Publication title -

abstract and applied analysis

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.228

H-Index - 56

eISSN - 1687-0409

pISSN - 1085-3375

DOI - 10.1155/2013/359265

Subject(s) - mathematics , parameterized complexity , discrete time and continuous time , nonlinear system , control theory (sociology) , artificial neural network , bounded function , jump , norm (philosophy) , state space , computer science , algorithm , mathematical analysis , control (management) , statistics , physics , quantum mechanics , artificial intelligence , machine learning , political science , law

This paper deals with the finite-time stabilization problem for discrete-time Markov jump nonlinear systems with time delays and norm-bounded exogenous disturbance. The nonlinearities in different jump modes are parameterized by neural networks. Subsequently, a linear difference inclusion state space representation for a class of neural networks is established. Based on this, sufficient conditions are derived in terms of linear matrix inequalities to guarantee stochastic finite-time boundedness and stochastic finite-time stabilization of the closed-loop system. A numerical example is illustrated to verify the efficiency of the proposed technique

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