Comparative Performance Analysis of LQR and MPC for Active Suspension System

Abstract

This research presents the comparative analysis of two very famous controllers that are now being used to design an active suspension system (ASS). The Linear Quadratic Regulator (LQR) and Model Predictive Controller (MPC) are two controller are used here. Our main aim is to track the system’s actions with its controllers and determine which ones perform better in the same circumstances. For the designing of the ASS a quarter-car model (QCM) is used. The entire experiment is conducted on QUANSER ASS (QASS) connected to MATLAB software. The research is to minimize turbulences by applying various controls and to maximize the ride comfort of the QCM. For this purpose a LQR and MPC is used in the same framework. The outcomes are then compared to the controller that performs more effectively. The outcome reveal that the MPC performs better than the other controller. This fact is confirmed by using various performance indexes like integral absolute error (IAE), integral time absolute error (ITAE) and integral square error (ISE).