<i>H<sub>∞</sub>
                  </i> Proportional-Integral State Estimation for T–S Fuzzy Systems Over Randomly Delayed Redundant Channels With Partly Known Probabilities

Wang, Yezheng; Wang, Zidong; Zou, Lei; Dong, Hongli

doi:10.1109/tcyb.2020.3036364

Cited by 17 publications

(6 citation statements)

References 50 publications

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“…According to the symbol defined-above, it is easy to have inequality (21) based on (29). Thus, error dynamic (19) with d(k) = 0 is asymptotically stable provided that (21) holds.…”

Section: Stability Analysismentioning

confidence: 99%

“…In light of such models, a close relationship between the fuzzy logic theory and the sophisticated linear systems theory can be established to realize the control design for nonlinear systems. As a result, a series of topics on T-S fuzzy systems have been well discussed [21][22][23][24][25][26][27][28][29][30]. Although many interesting observer design methods have been explored for T-S fuzzy systems, they are not directly applicable for T-S fuzzy singular systems (TSFSSs).…”

Section: Introductionmentioning

confidence: 99%

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Robust observer design for T-S fuzzy singular systems with unmeasurable premise variables and partially decoupled disturbances

Cai

et al. 2022

Preprint

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This article makes some efforts towards discussing the problem of observer design for a kind of discrete-time T-S fuzzy singular systems corrupted by process disturbances and measurement noises. To situate our design scheme in a more practical context, the premise variables of fuzzy systems under consideration are unmeasurable, and the process disturbances are only partially decoupled rather than completely decoupled. By integrating the fuzzy Lyapunov function method and the linear matrix inequality technique, an unknown input observer which can not only decouple partial process disturbances, but also attenuate the influence of measurement noises and non-decoupled process disturbances is proposed to achieve state reconstruction. Particularly, to reduce the conservatism, some slack matrices and scalars are utilized in observer design to obtain extra degrees of freedom. Finally, the performance of theoretical results is fully verified via two numerical simulations.

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“…According to the symbol defined-above, it is easy to have inequality (21) based on (29). Thus, error dynamic (19) with d(k) = 0 is asymptotically stable provided that (21) holds.…”

Section: Stability Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Robust observer design for T-S fuzzy singular systems with unmeasurable premise variables and partially decoupled disturbances

Cai

et al. 2022

Preprint

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“…The fuzziness and uncertainty in fuzzy rules can be better handled. Among the now available results in the literature, [6][7][8][9][10] have given specific analysis and constraints on the stability problem of T-S and demonstrated the superiority of T-S fuzzy model fitting in simulation experiments. The literature [11] investigates the output-feedback control problem for a class of discrete-time T-S fuzzy systems with randomly occurring infinitely distributed delays and channel superposition and introduces a random variable obeying Bernoulli distribution to explain the probabilistic infinitely distributed delays.…”

Section: Introductionmentioning

confidence: 99%

A control scheme for interval type‐2 T‐S fuzzy systems at constrained bit rates: A coding and decoding scheme

Yan,

Zhang,

2024

Asian Journal of Control

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SummaryThis study focuses on a class of interval type‐2 T‐S fuzzy systems under bit rate constraint(BRC), which can adapt to complex systems more flexibly than the traditional interval type‐1 T‐S fuzzy model. In order to guarantee the security of data transmission, and considering that the channel is affected by the bit rate during transmission, this study introduces a codec scheme in the interval type‐2 T‐S fuzzy system and applies it to the channel from the sensor to the controller. With the support of the codec scheme, this study explores the sufficient conditions to satisfy the data recoverability, and based on the satisfaction of these conditions, the system is proposed to satisfy the sufficient conditions for input‐to‐state stability (ISS) and the controller gain. Through the in‐depth analysis in this paper, this study proposes a control scheme that can fit complex systems more accurately and also confirms the importance of considering bit rate constraints in communication systems. Finally, the paper is validated by simulation with two specific examples, which fully demonstrate the superiority and effectiveness of the proposed control scheme.

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“…[6], [7], [13], [23], [32], [33]. In order to deal with different types of exogenous disturbances, a variety of SE techniques have been developed with examples including Kalman estimation approach [4], [18], [37], variance-constrained estimation method [16], [17], [23], H ∞ estimation scheme [38], [40], [46] and set-membership estimation technique [28], [41], [43], [48]. In these SE strategies, it is typically required that all inputs (e.g.…”

Section: Introductionmentioning

confidence: 99%

“…Recently, the redundant channel schemes have been widely applied in networked systems [40], [47], sensor networks and multiagent systems [42] to deal with the sliding mode control, the distributed filtering and the H ∞ consensus problems, respectively. Regarding CNs, the generalized SE method has been presented in [36], where both the redundant channels and Round-Robin protocol have been taken into consideration.…”

Section: Introductionmentioning

confidence: 99%

Simultaneous State and Unknown Input Estimation for Complex Networks With Redundant Channels Under Dynamic Event-Triggered Mechanisms

Wang

et al. 2022

IEEE Trans. Neural Netw. Learning Syst.

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This paper addresses the simultaneous state and unknown input estimation problem for a class of discrete timevarying complex networks (CNs) under redundant channels and dynamic event-triggered mechanisms (ETMs). The redundant channels, modeled by an array of mutually independent Bernoulli distributed stochastic variables, are exploited to enhance the transmission reliability. For energy-saving purposes, a dynamic event-triggered transmission scheme is enforced to ensure that every sensor node sends its measurement to the corresponding estimator only when a certain condition holds. The primary objective of the investigation carried out is to construct a recursive estimator for both the state and the unknown input such that certain upper bounds on the estimation error covariances are first guaranteed and then minimized at each time instant in the presence of dynamic event-triggered strategies and redundant channels. By solving two series of recursive difference equations, the desired estimator gains are computed. Finally, an illustrative example is presented to show the usefulness of the developed estimator design method.

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H_∞ Proportional-Integral State Estimation for T–S Fuzzy Systems Over Randomly Delayed Redundant Channels With Partly Known Probabilities

Cited by 17 publications

References 50 publications

Robust observer design for T-S fuzzy singular systems with unmeasurable premise variables and partially decoupled disturbances

Robust observer design for T-S fuzzy singular systems with unmeasurable premise variables and partially decoupled disturbances

A control scheme for interval type‐2 T‐S fuzzy systems at constrained bit rates: A coding and decoding scheme

Simultaneous State and Unknown Input Estimation for Complex Networks With Redundant Channels Under Dynamic Event-Triggered Mechanisms

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H∞ Proportional-Integral State Estimation for T–S Fuzzy Systems Over Randomly Delayed Redundant Channels With Partly Known Probabilities

Cited by 17 publications

References 50 publications

Robust observer design for T-S fuzzy singular systems with unmeasurable premise variables and partially decoupled disturbances

Robust observer design for T-S fuzzy singular systems with unmeasurable premise variables and partially decoupled disturbances

A control scheme for interval type‐2 T‐S fuzzy systems at constrained bit rates: A coding and decoding scheme

Simultaneous State and Unknown Input Estimation for Complex Networks With Redundant Channels Under Dynamic Event-Triggered Mechanisms

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H_∞ Proportional-Integral State Estimation for T–S Fuzzy Systems Over Randomly Delayed Redundant Channels With Partly Known Probabilities