Gain-scheduled Control with Data-driven Control and Model-matching Method for Vehicle

Abstract

For realizing desired control performances, data-driven tunings such as virtual reference feedback tuning (VRFT) and fictious reference iterative tuning (FRIT) were proposed. However, these methods cannot realize desired control performances of autonomous vehicles because vehicle dynamics is time variant systems. To solve this problem, we propose gain-scheduled PI controls based on data-driven controls and model-based controls were proposed. The validity of proposed method is verified through vehicle simulators.