@incollection{eprints1471,
          author = {Matteo Rubagotti and Tomaso Poggi and Alberto Bemporad and Marco Storace},
            note = {51st IEEE Conference on Decision and Control December 10-13, 2012. Maui, Hawaii, USA},
       publisher = {IEEE},
       booktitle = {Proceedings of the IEEE 51st Annual Conference on Decision and Control (CDC), 2012},
           pages = {656 --661},
           month = {December},
            year = {2012},
           title = {Piecewise affine direct virtual sensors with Reduced Complexity},
             url = {http://eprints.imtlucca.it/1471/},
        abstract = {In this paper, a piecewise-affine direct virtual sensor is proposed for the estimation of unmeasured outputs of nonlinear systems whose dynamical model is unknown. In order to overcome the lack of a model, the virtual sensor is designed directly from measured inputs and outputs. The proposed approach generalizes a previous contribution, allowing one to design lower-complexity estimators. Indeed, the reduced-complexity approach strongly reduces the effect of the so-called "curse of dimensionality", and can be applied to relatively high-order systems, while enjoying all the convergence and optimality properties of the original approach.},
        keywords = {Complexity theory; Estimation; Observability; Sensor systems; Vectors; Voltage control.}
}