Position Estimation and Smooth Tracking with a Fuzzy-Logic-Based Adaptive Strong Tracking Kalman Filter for Capacitive Touch Panels

Chih Lung Lin, Yi Ming Chang, Chia Che Hung, Chun Da Tu, Cheng Yan Chuang

Research output: Contribution to journalArticle

48 Citations (Scopus)


This paper presents a novel 7-in capacitive touch panel (CTP) system with a smooth tracking algorithm that accurately estimates the position where the panel is touched and tracks the trajectory of touch. The proposed CTP system consists of a microcontroller unit, a sensor IC, and an interface board. When a user draws at different speeds, the measurement noise caused by the sensor IC induces an error in the touched position and zigzag trajectory, especially when the motion is slow. The fuzzy-logic-based adaptive strong tracking Kalman filter method is implemented in a CTP system to mitigate the effect of measurement noise and provide a smooth tracking trajectory at different speeds. Moreover, the approach effectively measures and quantifies the 'smoothness' of the touched trajectory. Experimental results indicate that the proposed method reduces the measurement noise and decreases the mean tracking error by 85.4% over that achieved using the moving average filter.

Original languageEnglish
Article number7027798
Pages (from-to)5097-5108
Number of pages12
JournalIEEE Transactions on Industrial Electronics
Issue number8
Publication statusPublished - 2015 Aug 1


All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Electrical and Electronic Engineering

Cite this