基于模型预测控制的智能车辆避障跟踪仿真

针对智能车辆的避障跟踪控制问题,设计一种模型预测控制器。该控制器采用分层结构,上层基于非线性车辆点质量模型在避障时进行局部路径规划,下层基于单轨车辆动力学模型实现路径跟踪。通过Carsim和Matlab联合仿真,利用粒子群算法在线优化控制器参数,以不同的速度测试控制器性能,仿真结果表明：控制器具有良好的鲁棒性和实时性,跟踪误差较小,在单个和多个障碍物情况下,通过分层控制均实现了平稳避障并重新跟踪上原路径,表明控制器准确性高。

Simulation on Obstacle Avoidance Tracking of Intelligent Vehicle Based on Model Predictive Control

Aiming at the obstacle avoidance and path tracking control of intelligent vehicle, a model predictive controller (MPC) is designed. A layered structure is used in the controller. The high-level layer carries out the local path planning based on non-linear vehicle point mass model and the low-level layer realizes the path tracking based on monorail vehicle dynamics model. Through the joint simulation of Carsim and Matlab software, the controller parameters are optimized on-line by using Particle Swarm Optimization, and the performance of the controller is tested at different speeds. Simulation results show that the controller has good robustness, real-time performance and small tracking error. In the case of single and multiple obstacles, the hierarchical controller could avoid obstacles smoothly and re-track the original path in high accuracy.