The Experts below are selected from a list of 204 Experts worldwide ranked by ideXlab platform
Elkebir Boukas - One of the best experts on this subject based on the ideXlab platform.
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h control for discrete time markovian jump linear systems with partly unknown Transition Probabilities
International Journal of Robust and Nonlinear Control, 2009Co-Authors: Lixian Zhang, Elkebir BoukasAbstract:In this paper, the problem of H∞ control for a class of discrete-time Markovian jump linear system with partly unknown Transition Probabilities is investigated. The class of systems under consideration is more general, which covers the systems with completely known and completely unknown Transition Probabilities as two special cases. Moreover, in contrast to the uncertain Transition Probabilities studied recently, the concept of partly unknown Transition Probabilities proposed in this paper does not require any knowledge of the unknown elements. The H∞ controllers to be designed include state feedback and dynamic output feedback, since the latter covers the static one. The sufficient conditions for the existence of the desired controllers are derived within the matrix inequalities framework, and a cone complementary linearization algorithm is exploited to solve the latent equation constraints in the output-feedback control case. Two numerical examples are provided to show the validness and potential of the developed theoretical results. Copyright © 2008 John Wiley & Sons, Ltd.
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brief paper stability and stabilization of markovian jump linear systems with partly unknown Transition Probabilities
Automatica, 2009Co-Authors: Lixian Zhang, Elkebir BoukasAbstract:In this paper, the stability and stabilization problems of a class of continuous-time and discrete-time Markovian jump linear system (MJLS) with partly unknown Transition Probabilities are investigated. The system under consideration is more general, which covers the systems with completely known and completely unknown Transition Probabilities as two special cases - the latter is hereby the switched linear systems under arbitrary switching. Moreover, in contrast with the uncertain Transition Probabilities studied recently, the concept of partly unknown Transition Probabilities proposed in this paper does not require any knowledge of the unknown elements. The sufficient conditions for stochastic stability and stabilization of the underlying systems are derived via LMIs formulation, and the relation between the stability criteria currently obtained for the usual MJLS and switched linear systems under arbitrary switching, are exposed by the proposed class of hybrid systems. Two numerical examples are given to show the validity and potential of the developed results.
Lixian Zhang - One of the best experts on this subject based on the ideXlab platform.
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h control for discrete time markovian jump linear systems with partly unknown Transition Probabilities
International Journal of Robust and Nonlinear Control, 2009Co-Authors: Lixian Zhang, Elkebir BoukasAbstract:In this paper, the problem of H∞ control for a class of discrete-time Markovian jump linear system with partly unknown Transition Probabilities is investigated. The class of systems under consideration is more general, which covers the systems with completely known and completely unknown Transition Probabilities as two special cases. Moreover, in contrast to the uncertain Transition Probabilities studied recently, the concept of partly unknown Transition Probabilities proposed in this paper does not require any knowledge of the unknown elements. The H∞ controllers to be designed include state feedback and dynamic output feedback, since the latter covers the static one. The sufficient conditions for the existence of the desired controllers are derived within the matrix inequalities framework, and a cone complementary linearization algorithm is exploited to solve the latent equation constraints in the output-feedback control case. Two numerical examples are provided to show the validness and potential of the developed theoretical results. Copyright © 2008 John Wiley & Sons, Ltd.
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brief paper stability and stabilization of markovian jump linear systems with partly unknown Transition Probabilities
Automatica, 2009Co-Authors: Lixian Zhang, Elkebir BoukasAbstract:In this paper, the stability and stabilization problems of a class of continuous-time and discrete-time Markovian jump linear system (MJLS) with partly unknown Transition Probabilities are investigated. The system under consideration is more general, which covers the systems with completely known and completely unknown Transition Probabilities as two special cases - the latter is hereby the switched linear systems under arbitrary switching. Moreover, in contrast with the uncertain Transition Probabilities studied recently, the concept of partly unknown Transition Probabilities proposed in this paper does not require any knowledge of the unknown elements. The sufficient conditions for stochastic stability and stabilization of the underlying systems are derived via LMIs formulation, and the relation between the stability criteria currently obtained for the usual MJLS and switched linear systems under arbitrary switching, are exposed by the proposed class of hybrid systems. Two numerical examples are given to show the validity and potential of the developed results.
Ming Gao - One of the best experts on this subject based on the ideXlab platform.
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stabilization for markovian jump nonlinear systems with partly unknown Transition Probabilities via fuzzy control
Fuzzy Sets and Systems, 2010Co-Authors: Li Sheng, Ming GaoAbstract:Abstract: This paper is concerned with the stability and stabilization problems for a class of nonlinear systems with Markovian jump parameters. The Takagi-Sugeno (T-S) fuzzy model is employed to represent the Markovian jump nonlinear systems with partly unknown Transition Probabilities. In contrast with the certain or uncertain Transition Probabilities investigated recently, the concept of partly unknown Transition Probabilities does not need any knowledge of the unknown elements. Some sufficient conditions for stochastic stability and stabilization conditions with a mode-dependent fuzzy controller are derived for the Markovian jump fuzzy systems in terms of linear matrix inequalities (LMIs). A numerical example is provided to illustrate the design developed in this paper.
Takashi Kanamura - One of the best experts on this subject based on the ideXlab platform.
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on Transition Probabilities of regime switching in electricity prices
Energy Economics, 2008Co-Authors: Kazuhiko Ohashi, Takashi KanamuraAbstract:We analyze the Transition Probabilities of regime switching in electricity prices by explicitly incorporating the underlying demand/supply structure. We show that the Transition Probabilities of electricity prices cannot be constant, and depend on both the current demand level relative to the supply capacity and the trends of demand fluctuation. These results not only contrast with the assumption of constant Transition Probabilities on which many regime-switching models are built, but also provide new insights on the determinants of the state-dependent Transition Probabilities of regime switching.
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On Transition Probabilities of Regime-Switching in Electricity Prices
SSRN Electronic Journal, 2004Co-Authors: Kazuhiko Ohashi, Takashi KanamuraAbstract:We analyze Transition Probabilities of regime-switching in electricity prices based on supply and demand by using the structural model of Kanamura and Ohashi (2004). We show that the Transition Probabilities depend on the demand level and thus are not constant. This result is in sharp contrast to many models of electricity prices that assume constant Transition Probabilities among different regimes. We also estimate the model with a historical data in the PJM market, and analyze empirically the seasonality of the Transition Probabilities. The results obtained here are consistent with the observed characteristics of price spikes in electricity markets where the spikes tend to occur in summer and in winter when the demand level is high. These results support the argument by Lucia and Schwartz (2002) that asserts the importance of seasonality in modeling electricity prices.
Chunhui Wang - One of the best experts on this subject based on the ideXlab platform.
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controller synthesis for markovian jump systems with incomplete knowledge of Transition Probabilities and actuator saturation
Journal of The Franklin Institute-engineering and Applied Mathematics, 2011Co-Authors: Yijing Wang, Chunhui WangAbstract:Abstract This paper is concerned with Markovian jump systems subject to incomplete knowledge of Transition Probabilities and actuator saturation. The system under consideration is more general, which covers the systems with completely known and completely unknown Transition Probabilities. By introducing some free-connection weighting matrices to handle the inaccessible elements of Transition Probabilities, a new criterion is established to guarantee the stochastic stability of the closed-loop system. An optimization problem with LMI constraints is then formulated to determine the largest contractively invariant set in mean square sense. Finally, two numerical examples are provided to illustrate the merits of our method.
