Finite-time boundedness of Markovain jump nonlinear systems with incomplete information

This paper deals with the finite-time $ H_{\infty } $ H ∞ bounded control problem of a class of uncertain Markovian jump nonlinear systems with partially unknown transition probabilities and norm-bounded disturbances. The purpose of the paper is to derive a stochastic finite-time controller such tha...

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Published inInternational journal of systems science Vol. 49; no. 16; pp. 3296 - 3306
Main Authors Zhang, Yingqi, Yang, Yang, Shi, Peng, Pan, Jeng-Shyang
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Published London Taylor & Francis 10.12.2018
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Abstract This paper deals with the finite-time $ H_{\infty } $ H ∞ bounded control problem of a class of uncertain Markovian jump nonlinear systems with partially unknown transition probabilities and norm-bounded disturbances. The purpose of the paper is to derive a stochastic finite-time controller such that the resulting nominal or uncertain stochastic nonlinear model is stochastically finite-time $ H_{\infty } $ H ∞ bounded by applying stochastic analysis techniques and free connection weighting matrix approach. We also provide stochastic finite-time stability and stochastic finite-time boundedness criteria of the class of nominal or uncertain stochastic nonlinear dynamics. Moreover, the derived criteria can be simplified into linear matrix inequalities (LMIs), which could be solved by employing Matlab LMI toolbox. Finally, the effectiveness of proposed approaches is demonstrated by a practical example.
AbstractList This paper deals with the finite-time $ H_{\infty } $ H ∞ bounded control problem of a class of uncertain Markovian jump nonlinear systems with partially unknown transition probabilities and norm-bounded disturbances. The purpose of the paper is to derive a stochastic finite-time controller such that the resulting nominal or uncertain stochastic nonlinear model is stochastically finite-time $ H_{\infty } $ H ∞ bounded by applying stochastic analysis techniques and free connection weighting matrix approach. We also provide stochastic finite-time stability and stochastic finite-time boundedness criteria of the class of nominal or uncertain stochastic nonlinear dynamics. Moreover, the derived criteria can be simplified into linear matrix inequalities (LMIs), which could be solved by employing Matlab LMI toolbox. Finally, the effectiveness of proposed approaches is demonstrated by a practical example.
This paper deals with the finite-time [Formula omitted.] bounded control problem of a class of uncertain Markovian jump nonlinear systems with partially unknown transition probabilities and norm-bounded disturbances. The purpose of the paper is to derive a stochastic finite-time controller such that the resulting nominal or uncertain stochastic nonlinear model is stochastically finite-time [Formula omitted.] bounded by applying stochastic analysis techniques and free connection weighting matrix approach. We also provide stochastic finite-time stability and stochastic finite-time boundedness criteria of the class of nominal or uncertain stochastic nonlinear dynamics. Moreover, the derived criteria can be simplified into linear matrix inequalities (LMIs), which could be solved by employing Matlab LMI toolbox. Finally, the effectiveness of proposed approaches is demonstrated by a practical example.
Author Shi, Peng
Zhang, Yingqi
Yang, Yang
Pan, Jeng-Shyang
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Snippet This paper deals with the finite-time $ H_{\infty } $ H ∞ bounded control problem of a class of uncertain Markovian jump nonlinear systems with partially...
This paper deals with the finite-time [Formula omitted.] bounded control problem of a class of uncertain Markovian jump nonlinear systems with partially...
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SubjectTerms boundedness
Dynamical systems
H_{\infty }
incomplete transition probabilities
Linear matrix inequalities
Markov processes
Markovian jump nonlinear systems
Mathematical analysis
Matrix methods
Nonlinear dynamics
Nonlinear systems
stochastic finite-time
stochastic finite-time boundedness
Transition probabilities
Title Finite-time boundedness of Markovain jump nonlinear systems with incomplete information
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Volume 49
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