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Emission requirements for diesel engines are becoming increasingly strict, leading to the increase of engine architecture complexity. This evolution requires a more systematic approach in the development of control systems than presently adopted, in order to achieve improved performances and reduction of times and costs in design, implementation and calibration. To this end, large efforts have been devoted in recent years to the application of advanced Model-Based MIMO control systems. In the present paper a new MIMO nonlinear feedback control is proposed, based on an innovative data-driven method, which allows to design the control directly from the experimental data acquired on the plant to be controlled. Thus, the proposed control design does not need the intermediate step of a reliable plant model identification, as required by Model-Based methods.

The vehicle sideslip angle is one of the most important variables for evaluating vehicle dynamics. The potential value of such a variable for obtaining significant improvements over current stability control systems is widely recognized. However, its direct measurement requires the use of complex and expensive devices which cannot be used in production cars. Large research efforts has been devoted to the problem of estimating the sideslip angle from other variables currently measured by standard Electronic Stability Control (ESC) sensors. However, at the best of author's knowledge, until now no application to production cars is known. In this paper, a new sideslip angle estimation technology is presented.