@incollection{eprints443,
       publisher = {Springer-Verlag},
          series = {Lecture Notes in Control and Information Sciences},
           pages = {183--194},
          editor = {Luigi Del Re and Frank Allg{\"o}wer and Luigi Glielmo and Carlos Guardiola and Ilya Kolmanovsky},
           title = {Model predictive powertrain control: an application to idle speed regulation},
         journal = {Automotive Model Predictive Control: Models, Methods and Applications},
            year = {2010},
          author = {Stefano Di Cairano and Diana Yanakiev and Alberto Bemporad and Ilya Kolmanovsky and Davor Hrovat},
          volume = {402},
       booktitle = {Automotive Model Predictive Control: Models, Methods and Applications},
        abstract = {Model Predictive Control (MPC) can enable powertrain systems to satisfy more stringent vehicle requirements. To illustrate this, we consider an application of MPC to idle speed regulation in spark ignition engines. Improved idle speed regulation can translate into improved fuel economy, while improper control can lead to engine stalls. From a control point of view, idle speed regulation is challenging, since the plant is subject to time delay and constraints. In this chapter, we first obtain a control-oriented model where ancillary states are added to account for delay and performance specifications. Then the MPC optimization problem is defined. The MPC feedback law is synthesized as a piecewise affine function, suitable for implementation in automotive microcontrollers. The obtained design has been extensively tested in a vehicle under different operating conditions. Finally, we show how competing requirements can be met by a switched MPC controller. },
             url = {http://eprints.imtlucca.it/443/}
}