Event-triggered quantized filtering of discrete descriptor hybrid systems with incomplete information

Abstract

This paper concentrates on the event-triggered (ET) quantized $H_{\infty }$ filter analysis and design of discrete-time descriptor hybrid network systems with incomplete information. The main contributions of this paper are that quantized parameters and ET filter ones are decoupled, and further, ET $H_{\infty }$ filter and ET gain matrices are co-designed based on filter transfer function equivalent and convex function schemes. Utilizing ET communication and quantized techniques, a singular hybrid model with network-induced delays is initially derived. According to ET strategy and stochastic Lyapunov function approach, sufficient criteria are then established such that the resulting augmented stochastic model is stochastically admissible with an $H_{\infty }$ index. Besides, the derived conditions could be solved in terms of convex optimization method. Ultimately, effectiveness of the proposed approach combined quantization strategy with ET mechanism is verified by two practical examples.