自动驾驶汽车的GA增强控制:在随机扰乱的采样周期下协调FlexRay协议
IEEE transactions on cybernetics
|February 6, 2026
概括
本研究介绍了一种用于自动驾驶汽车横向动态的新型模糊控制器,解决了随机抽样和FlexRay通信问题. 控制器在复杂的通信环境中确保稳定性和性能.
科学领域:
- 控制系统工程 控制系统工程
- 汽车工程 汽车工程
- 机器人技术 机器人技术 机器人技术
背景情况:
- 自动驾驶汽车的控制受到随机抽样周期和复杂的通信协议 (如Flex.Ray) 的挑战.
- 车辆的非线性和变速需要复杂的建模方法.
研究的目的:
- 为自动驾驶汽车制定一个强大的横向动力学控制战略.
- 为应对随机扰乱采样 (RPS) 和FlexRay通信协议 (FRP) 所带来的挑战.
主要方法:
- 构建了一个TS模糊模型,以捕捉变速下车辆的非线性.
- 一个马科维的过程模拟了随机采样行为,一个统一的补偿策略处理了FlexRay的混合调度.
- 一个依赖采样模式的模糊控制器是使用异步约束技术设计的.
主要成果:
- 拟议的控制器保证了闭环系统的随机稳定性和H无限性性能.
- 一个遗传算法被用来解决控制器设计的全面优化问题.
- 模拟结果验证了控制策略的有效性和优越性.
结论:
- 开发的控制策略有效地管理在具有挑战性的通信条件下自动驾驶汽车的横向动态.
- 该方法提供了一个强大的解决方案,用于将高级控制与现实世界通信限制相结合.
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