Non-Linear Estimation using the Weighted Average Consensus-Based Unscented Filtering for Various Vehicles Dynamics towards Autonomous Sensorless Design

Bambang L. Widjiantoro, Moh Kamalul Wafi*, Katherin Indriawati

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

The concerns to autonomous vehicles have been becoming more intriguing in coping with the more environmentally dynamics non-linear systems under some constraints and disturbances. These vehicles connect not only to the self-instruments yet to the neighborhoods components, making the diverse interconnected communications which should be handled locally to ease the computation and to fasten the decision. To deal with those interconnected networks, the distributed estimation to reach the untouched states, pursuing sensorless design, is approached, initiated by the construction of the modified pseudo measurement which, due to approximation, led to the weighted average consensus calculation within unscented filtering along with the bounded estimation errors. Moreover, the tested vehicles are also associated to certain robust control scenarios subject to noise and disturbance with some stability analysis to ensure the usage of the proposed estimation algorithm. The numerical instances are presented along with the performances of the control and estimation method. The results affirms the effectiveness of the method with limited error deviation compared to the other centralized and distributed filtering. Beyond these, the further research would be the directed sensorless design and fault-tolerant learning control subject to faults to negate the failures.

Original languageEnglish
Pages (from-to)95-107
Number of pages13
JournalJournal of Robotics and Control (JRC)
Volume4
Issue number1
DOIs
Publication statusPublished - Jan 2023

Keywords

  • Autonomous vehicles
  • Estimation method
  • Unscented Kalman filtering
  • Weighted average consensus filtering

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