An unmanned surface vessel (USV) experiences many uncertainties generated by variations in the water surface condition, wind, and other external factors. Because those uncertainties degrade the controller performance of the USV, the controller should be carefully designed. A nonlinear control method can compensate for those uncertainties appropriately. However, the design procedure of a nonlinear controller is not only highly complex but also very time-consuming. This study proposes a linear-quadratic-regulator (LQR) control method to address these problems simultaneously by integrating a linear system and integral error variables. Because the proposed method is developed with the LQR control method, the complexity and effort of the controller design can be reduced significantly. Moreover, the integral error terms composed of longitudinal velocity/yawrate commands and responses are incorporated into the existing linear systems. By handling the augmented linear system, the obtained LQR controller results in zero values for both state and integral error variables simultaneously. A simulator is developed using MATLAB Simulink, Gazebo, and robot operating system (ROS) to validate the performance of the proposed method. Then, several waypoints following simulations are conducted, and the performance is analyzed with a result based on a nonlinear control method.