Nonlinear Model Predictive Control for Longitudinal and Lateral Dynamic of Autonomous Car

Autonomous cars, when two essential variables influence tracks to determine their stability, namely position control and speed control. Speed is a control variable in longitudinal motion because it controls car movement along the X axis. Steering is a control variable in the lateral control system because it controls car movement along the Y axis. Some of the studies before, most of them only paid attention to one variable between speed and steering, and other variables are considered constant. Therefore, in this study, multivariable control was carried out using Nonlinear Model Predictive Control (NMPC) to determine the speed and steering of the car. Nonlinear Model Predictive Control (NMPC) predicts control inputs in the next few steps. The use of the predicted value results is to minimize the execution time required by the car control system. Because the system's complexity in autonomous cars is high, thus it is better to process data faster. The NMPC process produces a car's steering angle and speed value that must be achieved when tracking on a predetermined track. The results showed that the proposed control strategy could precisely set the vehicle to follow the target's trajectory.