Optimization-based adaptive sliding mode control with application to vehicle dynamics control

This paper presents the design of a new adaptive optimization-based second-order sliding mode control algorithm for uncertain nonlinear systems. It is designed on the basis of a second-order sliding mode control with optimal reaching, with the aim of reducing the control effort while maintaining all the positive aspects in terms of finite-time convergence and robustness in front of matched uncertainties. These features are beneficial to guarantee good performance in case of vehicle dynamics control, a crucial topic in the light of the increasing demand of semiautonomous and autonomous driving capabilities in commercial vehicles. The new proposal is theoretically analyzed, as well as verified relying on an extensive comparative study, carried out on a realistic simulator of a 4-wheeled vehicle, in the case of a lateral stability control system.