An adaptive observer-based parameter estimation algorithm with application to road gradient and vehicle's mass estimation

Muhammad Nasiruddin Mahyuddin, Jing Na, Guido Herrmann, Xuemei Ren, Phil Barber

Research output: Chapter in Book/Report/Conference proceedingConference Contribution (Conference Proceeding)

16 Citations (Scopus)
289 Downloads (Pure)

Abstract

A novel observer-based parameter estimation algorithm with sliding mode term has been developed to estimate the road gradient and vehicle weight using only the vehicle's velocity and the driving torque from the engine. The estimation algorithm exploits all known terms in the system dynamics and a low pass filtered representation to derive an explicit expression of the parameter estimation error without measuring the acceleration. The proposed algorithm which features a sliding-mode term to ensure the fast and robust convergence of the estimation in the presence of persistent excitation is augmented to an adaptive observer and analyzed using Lyapunov Theory. The analytical results show that the algorithm is stable and ensures finite-time error convergence to a bounded error even in the presence of disturbances. A simple practical method for validating persistent excitation is provided using the new theoretical approach to estimation. This is validated by the practical implementation of the algorithm on a small-scaled vehicle, emulating a car system. The slope gradient as well as the vehicle's mass/weight are estimated online. The algorithm shows a significant improvement over a previous result.
Original languageEnglish
Title of host publication2012 UKACC International Conference on Control (CONTROL)
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages102-107
Number of pages7
ISBN (Print)9781467315593
DOIs
Publication statusPublished - Sep 2012
EventUKACC International Conference on Control 2012 - Cardiff, United Kingdom
Duration: 3 Sep 20125 Sep 2012

Conference

ConferenceUKACC International Conference on Control 2012
CountryUnited Kingdom
CityCardiff
Period3/09/125/09/12

Keywords

  • Observers
  • Parameter estimation
  • Roads
  • Vectors
  • Vehicle dynamics
  • Vehicles

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    Mahyuddin, M. N., Na, J., Herrmann, G., Ren, X., & Barber, P. (2012). An adaptive observer-based parameter estimation algorithm with application to road gradient and vehicle's mass estimation. In 2012 UKACC International Conference on Control (CONTROL) (pp. 102-107). Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/CONTROL.2012.6334614