Research On Model Predictive Control-based Trajectory Tracking Algorithm For Unmanned Vehicles

The efficient and stable trajectory tracking control system is necessary for theunmanned vehicle to be more intelligent and practical. This thesis is aimed at theresearch that how the high-speed unmanned vehicle follows the desired trajectory onthe ice and snow road through active front steering（AFS）. In this thesis, based on themodel predictive control (MPC) algorithm, the linear time-varying MPC (LTV MPC)controller is proposed to track the desired trajectory while ensuring the stability of thevehicle.Firstly, the nonlinear vehicle dynamic model with six degrees of freedom isderived. Magic formula tire model is applied to describe the tire characteristics.Designing the prediction model based on the nonlinear vehicle dynamic model andmagic formula tire model, it meets the real-time requirement. At the same time, iteliminates the influence of model mismatch.Secondly, the nonlinear system is converted to the linear time-varying systemconsidering the real-time requirement of the trajectory tracking control algorithm.Then the LTV MPC formula is derived. The LTV MPC optimal problem is convertedto the standard quadratic programming (QP) problem that is easy to calculate incomputer.Thirdly, the AFS LTV MPC-based trajectory tracking controller is proposed,which integrates the multi-constraints and the optimal cost function. The softconstraints of side-slip angle are applied to ensure the stability of the vehicle at highspeed, which prevents the vehicle from losing the trajectory tracking ability becauseof the front axle side sliding and from losing the stability because of the rear side spin.Finally, three different trajectory tracking controllers are proposed. Thesimulation experiments in the Simulink/Carsim simulation platform have beenconducted to verify the proposed methods. The simulation experiments show that theAFS LTV MPC-based trajectory tracking controller with soft constraints of side-slipangle has the best performance. This controller has good robustness and adaptabilityto the condition of road friction, the speed alteration and the reference trajectory.