Active suspension control of light motored vehicles using PID and neural controllers

This article presents two different feedback control approaches namely Proportional-integral-derivative (PID) and Artificial neural network for active suspension control of quarter car model. The study analysis car and wheel body displacement and velocity for achieving desired control. Mathematical model of the system was developed and simulated in Matlab/Simulink platform. Initially, PID controller was designed and its results were used as data base for training of neural controller. Several iterations were performed till an optimal value of mean square error (MSE) and regression (R) results were obtained for neural controller. The performance of controllers has been monitored in terms of attributes like settle time, overshoot range and steady state response. Results indicate superior performance of neural controller in terms of settling time and overshoot ranges compared to PID controller. Lastly, both the controllers showed excellent steady state response thus enhancing robustness of the system against external disturbances.