This paper deals with control design of Motion Cueing Algorithms for driving simulation. The development of driving-assistance systems and the gradual move towards autonomous driving led automobile manufacturers to focus on high performance driving simulation in order to validate novel functionalities and driving confort before production. Driving simulators are currently constrained environments because of the workspace size and the actuators resistance. As part of the software operating the platform, a control block has to manage the position of a cabin by guaranteeing realistic acceleration feelings to a driver. In this purpose, the controller is usually design within Model Predictive Control (MPC) framework. However large prediction horizons and constrained tracking problems implies heavy computational burden. In this paper, a novel MPC-based motion cueing algorithm is proposed considering periodic invariant sets as a key concept to decrease the complexity of the real-time optimization.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.