Identification of Static Boundary Model Based on Gaussian Process Classification
Abstract Due to the needs for CO2 emission reduction, the control region for automotive engine system is pushed toward the boundary between normal and abnormal engine operations such as knocking and misfiring. When an engine is operated outside of admissible region, the engine or the catalyst is seriously damaged or passengers feel very uncomfortable. Therefore the identification of the boundary is highly demanded. In this paper we propose a design of experiment (DoE) strategy based on the Gaussian process classifier (GPC) with the expectation propagation (EP) algorithm. In the experimental result, the proposed algorithm can identify the boundaries of an engine benchmark problem, provided by the joint research committee of the Society of Automotive Engineers (JSAE) and Society of Instrument and Control Engineers (SICE)