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Neuro Emission Controller for Minimizing Cyclic Dispersion in Spark Ignition Engines

Research output: Contribution to journalArticlepeer-review

Abstract

A novel neural network (NN) controller is developed to control spark ignition (SI) engines at extreme lean conditions. The purpose of neurocontroller is to reduce the cyclic dispersion at lean operation even when the engine dynamics are unknown. The stability analysis of the closed-loop control system is given and the boundedness of all signals is ensured. Results demonstrate that the cyclic dispersion is reduced significantly using the proposed controller. The neuro controller can also be extended to minimize engine emissions with high EGR levels, where similar complex cyclic dynamics are observed. Further, the proposed approach can be applied to control nonlinear systems that have similar structure as that of the engine dynamics.

Keywords

  • Air pollution
  • Closed Loop Systems
  • Combustion
  • Control System Synthesis
  • Internal combustion engines
  • Neurocontrollers
  • Nonlinear control theory
  • Spark ignition engines -- Ignition
  • Stability

Disciplines

  • Computer Sciences
  • Electrical and Computer Engineering
  • Operations Research, Systems Engineering and Industrial Engineering

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