PSO Based Linear Parameter Varying Model Predictive Control for Trajectory Tracking of Autonomous Vehicles

Abstract

Autonomous vehicles (AV) have gained significant attention and became prominent for research area in recent years due to their potential to revolutionize transportation systems. The AV system is characterized by instability, high nonlinearity and time-varying dynamics. Trajectory tracking control, plays a fundamental role in achieving the basic task of AVs to enable safe and efficient autonomous driving. In this research work, the design of a trajectory tracking control system for AVs using a specific variant of Model Predictive Control (MPC) called Linear Parameter Varying (LPV)-MPC which has emerged as an effective technique for trajectory tracking is designed. The time-varying LPV form of the state space representation is formulated from the mathematical model of the vehicle. This model is based on a nonlinear dynamic bicycle model, which considers constraints and is expressed in road-aligned coordinates. The LPV form allows for the incorporation of time varying dynamics, providing a more accurate representation of the vehicle's behavior. The designed LPV-MPC controller for AVs is specifically designed to handle constraints in trajectory tracking. To enhance its performance, Particle Swarm Optimization (PSO) is employed as an optimization technique. PSO is used to tune the weighting matrices of the control parameters, optimizing the system's response and improving trajectory tracking performance. To evaluate the effectiveness of the LPV-MPC system, extensive simulation and testing are conducted. The results are compared with the outcomes of a Linear MPC controller. The simulation and testing demonstrate that the LPV-MPC controller outperforms the Linear MPC controller in accurately tracking the desired trajectory, particularly when dealing with nonlinear reference roads. This highlights the capability of the LPV-MPC controller to effectively handle the challenges posed by nonlinear reference trajectories.