Design and Comparative Evaluation of Path-Tracking Controllers Using Reduced-Order State-Space Models

This study presents a comparative evaluation of path-tracking controllers designed from reduced-order state-space vehicle models. A four-state state-space model is formulated from the bicycle-model dynamics and target-path geometry, where the state variables are the previewed lateral error, heading error, side-slip angle, and yaw rate. To reduce the dependence on variables that are difficult to obtain in practice, a three-state model is derived by eliminating the explicit side-slip dynamics, and a two-state model is further obtained by replacing the yaw-rate dynamics with a kinematic approximation. Based on these three models, linear-quadratic regulator (LQR) controllers are designed. In addition, two linear quadratic static output-feedback (LQ SOF) controllers are constructed from the original four-state model by using reduced output sets. The five controllers are evaluated by vehicle simulations carried out in CarSim under front-wheel-steering and four-wheel-steering configurations. The results clarify the influence of controller structure and model order on path-tracking performance and identify the controller–actuator combination that provides the most favorable performance under the conditions considered.