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Transient engine models for optimization and implementation of model predictive control

Šika Z., Valášek M., Florián M., Macek J., Polášek M., Dolecek V., Bozek J.

Silniki Spalinowe

2007

R. 46, nr SC1

234-241

The paper deals with the investigation of model based predictive control of combustion engines. Three levels of dynamic models have been used. Firstly the reference1-D model with 3-D extensions calibrated by the experimental data to interpolate/extrapolate the data for identification of simplified fast models. Secondly the nearly real-time physical simulation model which allows for very fast simulation of engine transients and control algorithm design. Finaly the neuro-fuzzy predictive models implemented directly in controller. The predictive models are based on LOLIMOT approach. It is a description of generally nonlinear dynamic system by a sequence of linear dynamic systems valid in particular in one subregion of the whole state space. The decomposition of the state space into subregions is provided using the validity of linear dynamic models. The predictive models are used for the prediction of future engine states in dependence on actual measured states and possible control inputs. The future control inputs are optimized on-line based on locally linearized models. The problem of attainable prediction horizons in context of different speed of engine response to different control inputs is discussed.