A simple discrete-time tracking differentiator and its application to speed and position detection system for a maglev train

Abstract

In this brief, a novel tracking differentiator (TD) based on discrete time optimal control (DTOC) is presented. In particular, using the state back-stepping method, a DTOC law for a discrete-time, double-integral system is determined by linearized criterion, which equips the TD with a simple structure. The analysis of the proposed TD reveals its filtering mechanism. Simulation results show that it performs well in signal tracking and differentiation acquisition, and reduces the computational resources needed. Experiments conducted on the speed and position detection system for a maglev train demonstrate that the proposed TD group, with moving average algorithm, can filter noises, amend distortion signals effectively, and compensate for phase delays when the train is passing over track joints.