There is a growing interest in applying model predictive control techniques to automotive systems, often for different reasons: the simple handling of constraints, the easy use of preview information or the flexibility of the method. Some long-standing problems with this approach, like the high computational burden, have been solved or at least substantially mitigated. Even so, many issues remain to be elucidated, and, at the same time, papers and results in the increasingly rich literature are not always comparable. Against this background, the proceedings of the Automotive Model Predictive Control: Models, Methods and Applications workshop investigates whether constrained predictive control is reasonable in automotive control and what is necessary for its application. The workshop, held at the University of Linz on 9th a 10th February 2009 brought together workers from academia and industry from three key automotive branches: modeling, control and the application. The workshop included three keynote presentations, each of them contributing to the solution of an essential question. ac Which problems in automotive applications need constrained optimal control? ac Models of emissions for modern engines for model based control? ac Industrial methods and requirements for control schemes? The results of testing control strategies on a dynamical engine test bench give a feeling for the necessary computing power, the model plant mismatch, etc. and thus for the real application of control laws in production cars.Still there is no consensus on whether model predictive control with its high requi- ments on model quality and on computational power is a sensible choice for automotive control.
|Title||:||Automotive Model Predictive Control|
|Author||:||Luigi Del Re|
|Publisher||:||Springer Science & Business Media - 2010-03-11|