Robust ℋ/sub ∞/ filtering for uncertain discrete-time state-delayed systems

Palhares, Reinaldo M.; Souza, Carlos E. de; Peres, Pedro L. D.

doi:10.1109/78.934139

Cited by 188 publications

(108 citation statements)

References 25 publications

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“…In particular, the H ∞ filtering problem has been thoroughly studied for various time-delay systems, see e.g. [9,14,18,25,[27][28][29] for some recent papers. However, the aforementioned results are only concerned with one-dimensional (1-D) time-delay systems.…”

Section: Introductionmentioning

confidence: 99%

Filtering for uncertain 2-D discrete systems with state delays

Wang

Gao

et al. 2007

Signal Processing

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This paper is concerned with the problem of robust H ∞ filtering for two-dimensional (2-D) discrete systems with time delays in states. The 2-D systems under consideration are described in terms of the well-known Fornasini-Marchesini local state-space (FMLSS) models with time-delays. Our attention is focused on the design of a full-order filter such that the filtering error system is guaranteed to be asymptotically stable with a prescribed H ∞ disturbance attenuation performance. Sufficient conditions for the existence of desired filters are established by using a linear matrix inequality (LMI) approach, and the corresponding filter design problem is then cast into a convex optimization problem that can be efficiently solved by resorting to some standard numerical software. Furthermore, the obtained results are extended to more general cases where the system matrices contain either polytopic or norm-bounded parameter uncertainties. A simulation example is provided to illustrate the effectiveness of the proposed design method.

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Section: Introductionmentioning

confidence: 99%

Filtering for uncertain 2-D discrete systems with state delays

Wang

Gao

et al. 2007

Signal Processing

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“…. , r ) (defined in (19)), as established in the LMI constraints proposed in (18), it follows thatẽ(k) T κẽ(k) ≺ 0. Thus, according to the inequality (36), the H ∞ performance as well as the asymptotic stability in (30) is also guaranteed.…”

Section: Stability Conditions and H ∞ Performancementioning

confidence: 99%

Chaotic Synchronization and Information Transmission Experiments: A Fuzzy Relaxed H∞ Control Approach

Mozelli

Campos

Palhares

et al. 2007

Circuits Syst Signal Process

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Abstract. This paper addresses the problem of the synchronization of a class of chaotic oscillators using techniques borrowed from a recently proposed control design based on Takagi-Sugeno (TS) fuzzy modeling. In order to attain better synchronization, this TS fuzzy modeling is combined with the robust H ∞ observer theory based on linear matrix inequalities. A laboratory setup based on Chua's oscillator circuit is used to demonstrate the main ideas of the paper. Information transmission experiments are performed as an index to measure the effectiveness of the proposed approach.

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“…Quadratic matrix inequalities are adopted in the analysis and design of the filter. Note that robust filtering approaches in [60][61][62] have a common presumption that the original system is stable, which may to some extent limit the application scope of the results obtained. As an extension to [59], a robust H ∞ filter has been proposed in [63] to deal with time-varying delay and polytopic type uncertainties using a more efficient BRL.…”

Section: Treatments Of Network-induced Phenomenamentioning

confidence: 99%

“…In [59], a less conservative bounded real lemma (BRL) has been employed in the filter design for systems with known state delay to achieve a smaller overdesign. A robust H ∞ filtering approach has been proposed in [60] for a type of uncertain discrete time-delay systems whose parameter matrices are assumed to belong to a convex bounded polytope. Similarly, the filtering method proposed in [61] also addresses parameter uncertainty and time delay, but in this case continuous-time systems are considered and the delay is assumed to be unknown (only the upper bound is available).…”

Section: Treatments Of Network-induced Phenomenamentioning

confidence: 99%

Particle filtering with applications in networked systems: a survey

Wang

Yuan

2016

Complex Intell. Syst.

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The particle filtering algorithm was introduced in the 1990s as a numerical solution to the Bayesian estimation problem for nonlinear and non-Gaussian systems and has been successfully applied in various fields including physics, economics, engineering, etc. As is widely recognized, the particle filter has broad application prospects in networked systems, but network-induced phenomena and limited computing resources have led to new challenges to the design and implementation of particle filtering algorithms. In this survey paper, we aim to review the particle filtering method and its applications in networked systems. We first provide an overview of the particle filtering methods as well as networked systems, and then investigate the recent progress inThe work of W. Li, Y. Yuan and L.

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Robust ℋ/sub ∞/ filtering for uncertain discrete-time state-delayed systems

Cited by 188 publications

References 25 publications

Filtering for uncertain 2-D discrete systems with state delays

Filtering for uncertain 2-D discrete systems with state delays

Chaotic Synchronization and Information Transmission Experiments: A Fuzzy Relaxed H∞ Control Approach

Particle filtering with applications in networked systems: a survey

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