Autonomous Vehicle Front Steering Control Computation Saving

In the trajectory tracking of an autonomous vehicle, a lane-keeping control loop is fundamental. This involves a correct orientation of the yaw angle, which is achieved by actuating the steering. When addressing this type of control, one possible approach is to consider the design of a robust controller with various performance requirements defined by weighting functions. This procedure usually leads to a high-order controller, which entails a computational cost that burdens the processor dedicated to other high-demand control loops, such as computer vision algorithms. In this work, an interlacing procedure for the implementation of the robust controller will be introduced, which will allow a substantial reduction in computational load. The technique is applied to the state-space controller, allowing its extrapolation to MIMO controllers. Several options will be discussed, and the effectiveness and validity of the method will be evaluated through results based on real path tracking.