遗传算法在智能车控制器参数寻优中的应用  

Genetic Algorithm in Intelligent Car Controller Parameters Optimization of Application

作　　者：赵文龙[1] 阮艳凤[1] 谢敏[1] 彭洁[1] 

机构地区：[1]南昌航空大学信息工程学院,江西南昌330063

出　　处：《计算机仿真》2012年第10期259-262,共4页Computer Simulation

摘　　要：研究智能车控制器优化设计问题,由于控制器参数不准确,引起控制误差。为解决上述问题,根据智能车的运动学模型,设计出智能车轨迹跟踪控制律。采用遗传算法对控制律参数寻优,利用逆推(Backstepping)方法,在搜索空间里获得全局最优解。最后利用提出的遗传算法对控制律参数优化方法,通过智能车对圆周轨迹的跟踪仿真,证明了智能车在遗传算法对该控制律参数寻优下,能够实现对给定轨迹的全局渐近跟踪,获得了较好的控制效果。验证了遗传算法对智能车控制器参数寻优的可行性和有效性。According to the intelligence of the kinematics model car,using inverse push（Backstepping） method,the intelligent vehicle trajectory tracking control law were designed.A genetic algorithm was adopted in parameters optimization that makes the search space tend to global optima.Finally,the control law parameters optimization method was optimized by using genetic algorithm.Through the smart cars on the circular trajectory tracking simulation experiment,it was proved that the intelligent vehicle in the genetic algorithm to the control parameter optimization can realize the track of a given global asymptotic tracking and obtain better control effects.It is verified that the genetic algorithm to the intelligent controller parameters optimization of the car is feasible and effective.

关 键 词：智能车 遗传算法 参数优化 

分 类 号：TP202.7[自动化与计算机技术—检测技术与自动化装置]