Combining Optimal Controller and Luenberger Observer for an Active Roll Control System on Trucks to Avoid Rollover Phenomenon at High Speeds

Abstract

The propensity for roll instability in automobiles, particularly trucks, often arises during high-speed maneuvers and emergency scenarios. The active roll control (ARC) system presents a promising solution for enhancing truck roll stability. This study delves into designing a controller for the ARC system adapted to high-speed truck operations. It entails formulating a cost function for the linear quadratic regulator (LQR) optimal controller, incorporating variables directly pertinent to truck roll stability: vehicle body’s roll angle, unsprung masses’ roll angle, and normalized load transfer at the two axles. To streamline sensor usage and prioritize cost-effectiveness, the Luenberger observer is integrated with the full-state feedback LQR controller. The investigation involves executing double lane change maneuvers, simulating overtaking and obstacle avoidance, at speeds of 70, 100, 130, and 160 km/h. The maximum absolute value of the normalized load transfer coefficient at the axles is assessed up to speeds of 200 km/h. Research findings underscore the efficacy of the ARC system in enhancing truck safety by reducing the normalized load transfer of all axles over 30% compared to the passive system, particularly during high-speed operations.