Parameter Estimation of Spark-Ignited Internal Combustion Engines

Adaptive control of a power prime-mover requires effective modeling and identification techniques that have good disturbance rejection properties. Existing methods tend to avoid explicit modeling of input dead-time due to resulting computational complexity. TWO different approaches of modeling the diesel power prime-mover are presented in this paper. Both approaches are used for plant identification, to set up predictors that model dead-time explicitly. It is shown by extensive simulation studies that the predictors obtained are fast converging, and operate with very small prediction error under severe load disturbances and large speed reference changes. A comparative discussion of the two methods is presented.The prediction algorithms may be used in practice with one of the well known adaptive control methods.

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Parameter Estimation of Spark-Ignited Internal Combustion Engines

Cited by 5 publications

References 10 publications

Using an Angle-Based, Sampled-Data Approach to Modeling a Diesel Engine

Using an Angle-Based, Sampled-Data Approach to Modeling a Diesel Engine

Modelling of automobile dynamics for digital control of vehicle platoons

Predictors for application to real-time adaptive control of a diesel prime-mover

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