Protocol-based State Estimation for Linear Repetitive Processes with Quantization Effects: A Zonotopic Set-membership Approach

In this paper, the zonotopic state estimation problem is investigated for a class of linear repetitive processes (LRPs) with quantization effects and weighted try-once-discard protocols (WTODPs). The measurements are quantized before entering the network, where the uniform quantization is employed. In consideration of the evolution law of LRPs, a WTODP is introduced by which only the chosen sensor has right to transmit its data through network, thereby effectively curbing data collision and easing bandwidth usage. By harnessing the properties of zonotopic operators, a zonotope that covers all possible states is first constructed which are consistent with both the system model and WTODP-based measurements. Then, the size of the given zonotope is minimized by carefully designing an introduced correlation matrix. Eventually, we valid the effectiveness of proposed estimation method through a simulation example.