Adaptive state estimation for stochastic delay systems with state-dependent Markovian switching

Wang, G.; Zhang, Q.

doi:10.1049/iet-cta.2011.0259

Cited by 30 publications

(17 citation statements)

References 33 publications

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“…Though, α(k) is described by a Markov chain, it is said that system (2) or (3) is not a traditional Markovian jump system. In references [21,22,23,24,44,45,46,47], the system parameters switch synchronously according to a Markov process. Here, all the system parameters are deterministic, in which only the missing data in output is modeled into a Markov process.…”

Section: Problem Formulationmentioning

confidence: 99%

“…Then, it is necessary and important to design observers to estimate state variables. Up to now, the observer design problems for various kinds of systems were considered in [17,18,19,20,21,22,23,24,25,26]. From these references, it is said that the observer design techniques developed for generally dynamical systems may not be suitable for positive systems.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Positive observer design for discrete-time positive system with missing data in output

Wang

Zhang

et al. 2015

Neurocomputing

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Section: Problem Formulationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Positive observer design for discrete-time positive system with missing data in output

Wang

Zhang

et al. 2015

Neurocomputing

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“…This abrupt change may be caused by random failure, random fault-tolerance, environmental change and other random factors [1][2][3]. A class of variable structure system is the so-called Markovian jump systems (MJSs) on account of the abrupt change dominated by a Markov process [4][5][6]. In an MJS, the dynamical system is described by a set of structures, and the structure switching is controlled by a Markov process in a finite space [7][8][9][10][11].…”

Section: Introductionmentioning

confidence: 99%

Sliding Mode Control for Markovian Jump Systems with Generalized Switching

Wang

Tong

2018

Asian Journal of Control

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In this paper, the sliding mode control (SMC) problem for continuous-time Markovian jump systems (MJSs) is considered, in which the transition rate matrix (TRM) is partially unknown and uncertain. Firstly, the sliding mode surface S(t) = 0 is designed, which is mode-dependent. Therefore, ℒ S(t) is used instead ofṠ(t) in the SMC algorithm. Via adopting a linear matrix inequality (LMI) approach, sufficient conditions are proposed to ensure that the reduced order system is exponentially stable in mean square. Furthermore, the reduced order system is completely insensitive to the external disturbance. Secondly, SMC law is designed correspondingly which dominated by a Markov process. It could drive the state trajectories onto the specified sliding mode surface in finite time quickly and maintain them on the surface in subsequently time. Thirdly, a new term in ℒ S(t) will be introduced in the designed SMC and should be handled by a new approach. Finally, a numerical example is provided to show the effectiveness of the proposed method.

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“…The idea of state estimation is to design state estimator, which possesses the ability to reconstruct the immeasurable states and filter the external noise disturbances. So far, there has been an abundant supply of research on this issue, and many state estimation (or called optimal filtering) schemes have been developed in the literature, for example, [21][22][23][24][25]. Among these schemes, it has been recognised that the Kalman filtering and H ∞ filtering are popular and effective, especially for systems with external noise disturbances [26][27][28].…”

Section: Introductionmentioning

confidence: 99%

Finite‐time energy‐to‐peak filtering for Markov jump repeated scalar non‐linear systems with packet dropouts

Shen

Park

2014

IET Control Theory & Applications

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This study is concerned with the finite-time energy-to-peak filtering problem for Markov jump repeated scalar non-linear systems with packet dropouts. The packet dropout phenomenon occurs in a random way and is modelled by a stochastic variable satisfying the Bernoulli distribution. The purpose of the study is to design a filter such that the resulting filtering error system is stochastically finite-time bounded, and a prescribed energy-to-peak performance level is achieved over a finite time interval. By using the mode-dependent diagonally dominant Lyapunov function approach, some strict linear matrix inequality-based conditions are established for the existence of an admissible filter, and a corresponding explicit parameterisation of such a filter is obtained. Finally, a numerical example with simulation is presented to demonstrate the effectiveness of our proposed approach.

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Adaptive state estimation for stochastic delay systems with state-dependent Markovian switching

Cited by 30 publications

References 33 publications

Positive observer design for discrete-time positive system with missing data in output

Positive observer design for discrete-time positive system with missing data in output

Sliding Mode Control for Markovian Jump Systems with Generalized Switching

Finite‐time energy‐to‐peak filtering for Markov jump repeated scalar non‐linear systems with packet dropouts

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