Linear dynamic parameter-varying sliding manifold for air-fuel ratio control in lean-burn engines

Reza Tafreshi, Behrouz Ebrahimi, Javad Mohammadpour, Matthew A. Franchek, Karolos Grigoriadis, Houshang Masudi

Research output: Contribution to journalArticlepeer-review

24 Scopus citations


Precise control of air-fuel ratio (AFR) is one of the most challenging tasks in lean-burn spark ignition engines control. The main problem arises because of the large time-varying delay in the engine operating envelope. In this study, a new sliding mode-based synthesis method is presented to control AFR in order to improve fuel economy and decrease the tailpipe emissions. The time-varying delay dynamics is first estimated by Padé approximation, which transfers the system into a system with parameter-varying non-minimum phase dynamics. Non-minimum phase characteristics restrict the application of conventional sliding mode control approach because of the unstable internal dynamics. The system dynamics is then rendered into the normal form to investigate the system unstable internal dynamics. A systematic approach is proposed to design a linear dynamic parameter-varying sliding manifold (LDPVSM) in order to stabilise the unstable internal dynamics according to the desired output tracking error dynamics. Additionally, the proposed LDPVSM provides the system with robustness against unmatched perturbation. The method that can be easily implemented in practical settings exhibits the desired dynamics independent of the matched and unmatched disturbances. The results of applying the proposed method to experimental data demonstrate the closed-loop system stability and a superior performance against time-varying delay, canister purge disturbances and measurement noise.

Original languageEnglish (US)
Pages (from-to)1319-1329
Number of pages11
JournalIET Control Theory and Applications
Issue number10
StatePublished - 2013

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Human-Computer Interaction
  • Computer Science Applications
  • Control and Optimization
  • Electrical and Electronic Engineering


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