filtering for time-delay T–S fuzzy systems with intermittent measurements and quantization

You, Jia; Yin, Shen

doi:10.1016/j.jfranklin.2013.01.024

Cited by 10 publications

(4 citation statements)

References 27 publications

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“…The state estimation for the fuzzy systems with packet dropouts was discussed in [23], and the main results have been extended to the multiple channels case (see [24]). You and Yin [25] investigated the state estimation for time-delay fuzzy systems with quantization and packet dropouts, and an optimization problem was proposed to design the filter gains. Very recently, the distributed filtering for fuzzy time-delay systems with packet dropouts and redundant channels was studied in [26], and sufficient conditions on the existence of the desired distributed filters are established by employing the scaled small gain theorem, which ensures that the closed-loop system is stochastically stable and achieves a prescribed average H ∞ performance index.…”

Section: B Related Workmentioning

confidence: 99%

Robust Fuzzy-Model-Based Filtering for Nonlinear Cyber-Physical Systems With Multiple Stochastic Incomplete Measurements

Zhang

Song

2017

IEEE Trans. Syst. Man Cybern, Syst.

102

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This paper is concerned with the state estimation problem for a class of nonlinear cyber-physical systems (CPSs) where the nonlinear dynamical physical process is approximated by a Takagi-Sugeno fuzzy model. The physical plant is measured by a set of wireless sensors and the sensors communicate with the remote estimator via a communication channel. In the considered CPS, the randomly occurring sensor saturation, signal quantization, packet dropouts as well as the medium access constraint are studied in a unified framework. We develop a sufficient condition such that the filtering error system is asymptotically stable in the mean-square sense and also with a prescribed H ∞ performance level. The filter gain parameters are determined by solving a convex optimization problem. Finally, the simulation study on the networked truck-trailer system is presented to show the effectiveness of the proposed estimator design. Index Terms-Communication constraint, cyber-physical systems (CPSs), H ∞ filtering, incomplete measurement, state estimation, Takagi-Sugeno (T-S) systems.

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Section: B Related Workmentioning

confidence: 99%

Robust Fuzzy-Model-Based Filtering for Nonlinear Cyber-Physical Systems With Multiple Stochastic Incomplete Measurements

Zhang

Song

2017

IEEE Trans. Syst. Man Cybern, Syst.

102

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“…Especially in 1985, when Takagi and Sugeno established the basis of T-S fuzzy model (Takagi and Sugeno, 1985), the theories as well as the approaches used to analyze linear systems could be extended to nonlinear systems, since nonlinear systems can be expressed as combinations of a series of linear subsystems using membership functions (MFs) in the form of IF-THEN rules. So far, the theoretical system of T-S fuzzy model has been huge and mature with studies on system modeling (Hadjili and Wertz (2002)), stability analysis (Rhee and Won, 2006; Tanaka et al, 1998, 2003), observer design (Li and Zhang, 2018; Wang et al, 2011), filter design (You and Yin, 2014; Li et al, 2015), fault detection (Li et al, 2017; Zhuang et al, 2015), and so on.…”

Section: Introductionmentioning

confidence: 99%

Polynomial fault detection filter design under adaptive event-triggered scheme via line-integral Lyapunov functions

Ding

Liu

Yang

2021

Transactions of the Institute of Measurement and Control

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This paper investigates the problem of polynomial fault detection filter design under an adaptive event-triggered scheme for continuous-time networked polynomial fuzzy model–based (PFMB) systems considering network transmission delays. The proposed adaptive polynomial event-triggered scheme is checked only at the sampling instant to eliminate the Zeno behavior as well as save the network bandwidth. With the consideration of the mismatched membership functions (MFs), the asynchronous problem between the physical plant and the polynomial fault detection filter (PFDF) is examined. A Lyapunov–Krasovskii (L-K) function is introduced to deal with the time delays caused by the network transmission and the zero-order holder (ZOH), and a proper line-integral Lyapunov function is also introduced to reduce the conservation of the design constraints, whose analytical procedure is rule-dependent. The design constraints are given in the form of sum of squares (SOS) to keep the PFMB fault detection system asymptotically stable with [Formula: see text] performance [Formula: see text]. Finally, an inverted pendulum example together with a numerical example is given to verify the effectiveness and superiority of the proposed scheme in terms of transfer rate and conservatism.

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“…As a branch of state estimation theory, ∞ filter can process the estimation problem without exact statistical data for the external noise. This problem for the T-S fuzzy system has been addressed in [22][23][24][25][26][27]; and the robust filters for stochastic systems are designed in [28,29]. During the filter design, gain perturbations are usually unavoidable.…”

Section: Introductionmentioning

confidence: 99%

Nonfragile RobustH∞Filter Design for a Class of Fuzzy Stochastic Systems with Stochastic Input-to-State Stability

et al. 2015

Mathematical Problems in Engineering

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The nonfragileH∞filtering problem for a kind of Takagi-Sugeno (T-S) fuzzy stochastic system which has a time-varying delay and parameter uncertainties has been studied in this paper. Sufficient conditions for stochastic input-to-state stability (SISS) of the fuzzy stochastic systems are obtained. Attention is focused on the design of a nonfragileH∞filter such that the filtering error system can tolerate some level of the gain variations in the filter and theH∞performance level also could be satisfied. By using the SISS result, the approach to design the nonfragile filter is proposed in terms of linear matrix inequalities. Finally, an illustrative example is given to demonstrate the effectiveness of the proposed method.

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filtering for time-delay T–S fuzzy systems with intermittent measurements and quantization

Cited by 10 publications

References 27 publications

Robust Fuzzy-Model-Based Filtering for Nonlinear Cyber-Physical Systems With Multiple Stochastic Incomplete Measurements

Robust Fuzzy-Model-Based Filtering for Nonlinear Cyber-Physical Systems With Multiple Stochastic Incomplete Measurements

Polynomial fault detection filter design under adaptive event-triggered scheme via line-integral Lyapunov functions

Nonfragile RobustH∞Filter Design for a Class of Fuzzy Stochastic Systems with Stochastic Input-to-State Stability

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