【摘要】 针对车辆自适应巡航控制(ACC)系统的非线性和动态切换特点,提出一种使用混合模型预测控制(HMPC)的车辆自适应巡航控制方法。利用HMPC为ACC系统建立混合模型,利用混合系统描述语言(HYSDEL)自动将该模型转换成混合整数线性规划(MILP)问题;为了加速HMPC的过程,提出一种改进的粒子群优化(MPSO)算法,并在HMPC的滚动优化过程中利用MPSO算法在线求解MILP问题;利用优化得到的控制序列作用于巡航车辆,自适应改变车辆的速度。仿真结果表明,自适应巡航控制方法能够使巡航车跟踪前面车辆,速度保持一致,并且引入MPSO求解MILP问题可以加速HMPC的实现。更多还原

【Abstract】 According to its nonlinear and dynamical features of a vehicular adaptive cruise control(ACC)system,a ACC method based on hybrid model predictive control(HMPC)is proposed.Firstly,HMPC is adopted to design a hybrid model for the ACC system and the hybrid systems description language(HYSDEL)is used to transform the hybrid model into a problem of mixed integer linear programming(MILP).Then,in order to reduce HMPC’s calculation time,a modified particle swarm optimization(MPSO)algorithm is proposed,and the algorithm is applied to solve the MILP problem online.At last,the optimized results are used to control the cruising vehicle and change its speed adaptively.Simulation results indicate that the proposed method can make the cruising vehicle follow the leading vehicle very well.Moreover,the MPSO algorithm efficiently accelerates the process of HMPC.更多还原