Stability Analysis of Semi-active Suspension Systems Using a Data-driven Approach

The modern vehicles are getting equipped with more and sensors, which allows the engineers to collect information about states of vehicle its environment during operation. This can be used increase capacity performances control systems. In this paper, a novel data-driven approach is presented compute reachability sets vehicles, semi-active suspension system. dataset, in provided by high fidelity simulation software, CarSim. Firstly, dataset categorized using stability criterion. Then, machine-learning algorithm (C4.5 decision tree) trained, categorize given instance only onboard signals vehicle. Finally, possible application show use computed sets.