A new design of delay‐dependent robust ℋ︁_∞ filtering for continuous‐time polytopic systems with time‐varying delay

Abstract

SUMMARYThis paper revisits the problem of delay-dependent robust H ∞ filtering design for a class of continuous-time polytopic linear systems with a time-varying state delay. Based on a newly developed parameter-dependent Lyapunov-Krasovskii functional combined with Projection Lemma and an improved free-weighting matrix technique for delay-dependent criteria, a new sufficient condition for robust H ∞ performance analysis is first derived and then the filter synthesis is developed by using a simple matrix inequality linearization technique. It is shown that the desired filters can be constructed by solving a set of linear matrix inequalities. Finally, two simulation examples are given to show the effectiveness and less conservatism of the proposed method in comparison with the existing approaches.

Mode-dependent nonrational output feedback control for continuous-time semi-Markovian jump systems with time-varying delay

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Fault detection reduced-order filter design for discrete-time Markov jump system with deficient transition information

“…Many important results have been reported, such as a number of studies on the Markovian jump system on the filter design [3][4][5], controller design [6], output feedback control [7][8][9][10], stability analysis and synthesis [11][12][13]. In fact, MJLSs are very appropriate to dynamical model systems whose property is subject to random sudden variant due to abrupt external disturbance, shifting of the action spots of a nonlinear system, and repairs of components, thus, in order to ensure the nonlinear system stochastically exponentially stable, the author in [9] proposed a Markovian Lyapunov functional which was been successfully used in the nonlinear systems.…”

Co-design ofH∞jump observers for event-based measurements over networks

“…The use of a jump linear estimation instead of a time varying one, and the use of LMI formulation of the problem would allow to easily extend the proposal of this work to face, for instance, model uncertainties, models depending on time-varying parameters or sector-bounded nonlinearities, time-delays, packet dropouts or quantization (see, for instance, Qiu et al (2010Qiu et al ( , 2015Qiu et al ( , 2009). The LMI formulation of the problem results in the calculation of a bound on the state estimation error and the possibility of extending the observer design presented in this work to the design of inferential controllers or fault diagnosis systems.…”