Variance‐constrained resilient H_∞ filtering for mobile robot localization under dynamic event‐triggered communication mechanism

Abstract

This paper is concerned with the mobile robot localization problem subject to filter gain uncertainty under dynamic event-triggered communication mechanism, and meanwhile, the H ∞ filtering performance and the error variance constraint are guaranteed. For saving the sensor energy, a dynamic event-triggered communication mechanism is introduced to manage the transmission of the measurement data from the sensor to the filter. To characterize the possible fluctuations of the desired filter gain, a resilient filter is constructed for the mobile robot localization. The aim of this paper is to find a solution to the mobile robot localization problem by designing a nonlinear resilient filter such that the filtering error dynamics satisfies both the H ∞ performance requirement and the error variance constraint over a finite time horizon simultaneously. By resorting to the Lyapunov theory and the stochastic analysis technique, the sufficient conditions are established to guarantee that the error dynamic system satisfies both the H ∞ performance requirement and the error variance constraint. Then, a recursive linear matrix inequality (RLMI) approach is employed to design the desired filter. Based on the proposed filter design scheme, the corresponding localization algorithm is presented. Finally, an experiment is conducted in the simulation environment to verify the effectiveness of the proposed localization algorithm. KEYWORDS dynamic event-triggered communication mechanism, error variance constraint, H ∞ filtering, mobile robot localization, nonlinear resilient filter This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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