Model based control of a diesel engine

H. Jammoussi, M. A. Franchek, K. Grigoriadis, M. Books

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Proposed in this paper is an automated framework for calibration of diesel engine governors. The process involves two basic parts, online engine model identification followed by governor gain design. A previously developed Instrumental Variable 3 Step Algorithm for closed loop system identification is used to estimate the engine model. The identified model is then used in two different governor calibration approaches. The first approach employs a typical governor structure involving acceleration feedback. It will be shown that this governor structure reduces to a classical two degree-of-freedom design. The second approach is based on a procedure in which a desired open-loop transfer function (target transfer function) is shaped such that the same performance specifications as for the first design are satisfied. The control design methods are applied for an off-highway diesel engine with a disengaged transmission. In-field data collected from the engine operating closed-loop is used to identify a model for the open-loop system and the controller gains are then determined. The loop shaping method is then applied to the identified model to design a feedback controller and a prefilter. The efficacy of both loops in terms of tracking performance and noise rejection has been demonstrated through a time domain simulation of both closed-loop step responses.

Original languageEnglish (US)
Title of host publicationASME 2010 Dynamic Systems and Control Conference, DSCC2010
Pages93-99
Number of pages7
Volume1
DOIs
StatePublished - Dec 1 2010
EventASME 2010 Dynamic Systems and Control Conference, DSCC2010 - Cambridge, MA, United States
Duration: Sep 12 2010Sep 15 2010

Other

OtherASME 2010 Dynamic Systems and Control Conference, DSCC2010
Country/TerritoryUnited States
CityCambridge, MA
Period9/12/109/15/10

ASJC Scopus subject areas

  • Control and Systems Engineering

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