Approval of Artificial Intelligence and Machine Learning Models to Solve Problems in Nonlinear Active Suspension Systems

Abstract

In this chapter, the authors used a comparative study between passive and active suspension of quarter car models with deference intelligent controllers. This study aims to obtain an active suspension that adapts to all types of roads, especially rough and slippery ones, and absorbs shocks resulting from road vibrations, which gives more comfort to passengers and the driver. The results have proven that FOPID gave better results than PID in all types of road testing. The concerns related to the proposed chapter are that the car makers have a fear of the Fractional-Order controller FOPID to the difficulty of achieving it in the industrial field because of the difficulty of its mathematical equations and its high cost.