Stability control represents one of the most challenging tasks in autonomous vehicle dynamics. Within this context, model uncertainty may play a crucial role in determining the quality of the overall control system. In this work, we deal with nonlinear vehicle stability control design by using the D2-IBC (Data Driven - Inversion Based Control) method, wherein the dynamics of the system are modeled from data not to optimize the open-loop model matching but to maximize the closed-loop performance. Specifically, a multivariable extension of the method is derived and discussed in detail as far as the stability control application is concerned. This method will prove its effectiveness on a multi-body simulator of a 4-wheel steering autonomous vehicle.
Nonlinear stability control of autonomous vehicles: a MIMO D2-IBC solution
Galluppi, O.;Formentin, S.;Savaresi, S. M.
2017-01-01
Abstract
Stability control represents one of the most challenging tasks in autonomous vehicle dynamics. Within this context, model uncertainty may play a crucial role in determining the quality of the overall control system. In this work, we deal with nonlinear vehicle stability control design by using the D2-IBC (Data Driven - Inversion Based Control) method, wherein the dynamics of the system are modeled from data not to optimize the open-loop model matching but to maximize the closed-loop performance. Specifically, a multivariable extension of the method is derived and discussed in detail as far as the stability control application is concerned. This method will prove its effectiveness on a multi-body simulator of a 4-wheel steering autonomous vehicle.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
