Adaptive Input and Parameter Estimation with Application to Engine Torque Estimation

Jing Na, Guido Herrmann, Richard Burke, Chris Brace

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

15 Citations (Scopus)
224 Downloads (Pure)

Abstract

This paper presents two estimation methods for systems with unknown time-varying input dynamics. By defining auxiliary filtered variables, an invariant manifold is derived and used to drive the input estimator with only one tuning parameter. Exponential error convergence to a small compact set around the
origin can be proved. Robustness against noise is studied and compared with two well-known schemes. Moreover, when the input dynamics to be estimated are parameterized in a quasilinear form with unknown parameters, the proposed idea is further investigated to estimate the associated unknown
time-varying parameters. The algorithms are tested by considering the torque estimation of internal combustion engines (ICEs). Comparative simulation results based on a benchmark engine simulation model show satisfactory transient and
robustness performance.
Original languageEnglish
Title of host publication2015 54th IEEE Conference on Decision and Control (CDC)
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages3687-3692
Number of pages6
ISBN (Print)9781479978847
DOIs
Publication statusPublished - 15 Dec 2015

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