Linear Quadratic Regulator (LQR) Control for the Active Suspension System of a Four-Wheeled Agricultural Robot

As the adoption of robotics within the agricultural industry increases, the issue of maintaining stability and precise task execution on irregular terrain has emerged as a critical challenge. To address this, this study introduces a control strategy for enhancing the suspension system of an agricultural mobile robot. A dynamic model, characterized in the state-space representation, was formulated to encapsulate the robot’s suspension dynamics. This model was then interfaced with a Linear Quadratic Regulator (LQR) for optimized control. Performance evaluations were conducted using MATLAB/Simulink, and two contrasting road profiles were employed to simulate agricultural terrains. When compared to the passive counterpart, the active LQR-controlled suspension presented substantial improvements. Specifically, for the initial road profile, the roll angle, pitch angle, and vertical acceleration showed improvements of 40.68%, 39.47%, and 37.73%, respectively. On the second road profile characterized by depressions, these metrics improved by 52.02%, 66.97%, and 71.03%. Consequently, the proposed LQR control strategy enhances the robot’s stability and precision on challenging agricultural terrains by reducing oscillations and minimizing stabilization time.