Modeling and Control of Car Active Suspension System Using a Neural Network-based Controller and Linear Quadratic Regulator Controller

This paper aims to demonstrate the application of two different control techniques, namely the Linear Quadratic Regulator (LQR) and a neural network-based controller to evaluate and control the vibrations that occurred in the car's suspension system. When the car suspension is designed, a quarter car model with 1-DOF is used. A complete control system is needed to provide the desired suspension performance and characteristics such as passenger comfort, road handling, and suspension deflection, this control system performed by using the Matlab software and includes three parts: input signals (actuator force and road profile), Controller, and the suspension system model. The simulation results show a comparison between the uncontrolled suspension system and the suspension system with a neural network-based controller and the active suspension system of the car based on the linear-quadratic regulator, and it is explained thoroughly.