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Articulated vehicle is one of the utmost members of intelligent mining equipment and working under terrible conditions, which has the special steering structure and driving characteristics. In order to improve the tracking accuracy and response speed of the articulated vehicle, a linear quadratic regulator (LQR) strategy based on predictive information was proposed and a genetic algorithm (GA) was used to optimize the state quantity matrix, and the optimal LQR state feedback controller was obtained to realize the precise path tracking control of the articulated vehicle. The control result was reflected by the displacement deviation, the heading deviation and the curvature deviation. In the co-simulation (ADAMS-Matlab/Simulink) results, the displacement deviation was 0.03m, the deviation error was 1.3%, the heading deviation error was 0.19%, and the curvature deviation converged to be 0.003m-1. The co-simulation and experiment results showed that the proposed control method can effectively improve the control precision. The control strategy proposed can achieve the precise and stable path tracking of articulated vehicles, which was an alternative control method.