Dynamic Event-Triggered H ∞ Filtering for Fuzzy Markov Jump Systems Subject to Mismatched Quantization

Abstract

This paper is dedicated to a dynamic event-triggered $H_{\infty }$ filtering method of fuzzy Markov jump systems via a mismatched quantization scheme. The system outputs are triggered by a dynamic event-triggered mechanism and then quantized via a mismatched quantizer before being sent to the remote filter. The dynamic triggering scheme with a special diagonal matrix structure threshold is built to reduce the network burden. The quantizer is constructed in a multi-channel paradigm with a time-varying mismatch degree. Then, the remote reduce-order filter is designed to be both fuzzy-rule and mode-dependent. By adopting Finsler’s Lemma and the vertex separation method, sufficient conditions are derived in terms of form matrix inequalities. At last, the effectiveness of the proposed method is demonstrated by a tunnel diode circuit. Note to Practitioners—In practical networked systems, sampled analog signals must be quantized before being transmitted over a digital network. However, limited by imperfect hardware, the parameters of the encoder and decoder may not match. To address this challenge, this paper provides a mismatched quantizer design scheme. Additionally, frequent data transmission consumes limited energy and bandwidth resources. Conserving resources is essential for real industrial production, so a dynamic triggering scheme is proposed to reduce the data exchange frequency. A simulation example with practical background is presented to verify that the proposed scheme achieves satisfactory control performance.