在资源效率高的网络控制系统中,对全体机器人Mecanum轮式机器人进行远程路径控制
Rafael Carbonell1, Ángel Cuenca1, Julián Salt1
1Instituto Universitario de Automática e Informática Industrial, Universitat Politècnica de València, 46022 Valencia, Spain.
ISA transactions
|June 4, 2024
概括
本研究介绍了自动驾驶汽车的资源高效控制系统,显著减少了资源使用,同时确保了准确的路径跟踪. 这种新的方法提高了无线网络控制系统 (WNCS) 的性能.
科学领域:
- 机器人和控制系统 机器人和控制系统
- 无线网络控制系统 (WNCS) 是指无线网络控制系统.
- 自动驾驶车辆导航自动驾驶车辆导航
背景情况:
- 无线网络控制系统 (WNCS) 面临着诸如资源限制,时间变化的延迟和数据包丢失等挑战.
- 有效的控制策略对于自动驾驶汽车在WNCS约束下保持路径跟踪精度至关重要.
研究的目的:
- 开发一种资源高效的控制结构,用于自动驾驶汽车的远程路径控制.
- 解决WNCS中的挑战,包括延迟,数据包丢失和混乱.
- 在尽量减少资源消耗的同时保持令人满意的路径效果.
主要方法:
- 一个新的控制结构,结合了卡尔曼过,非统一的双速抽样,周期性事件触发通信和基于预测的控制.
- 实施非统一的双速扩展卡尔曼波器 (NUDREKF) 具有 h 步前进的预测阶段.
- 对算法实施的周期性事件触发条件,确保指数平均平方边界预测错误.
主要成果:
- 与模拟中的时间触发控制解决方案相比,实现了显著的资源使用减少 (高达93%).
- 对于一个全方位的 Mecanum 轮式机器人来说,它表现出了强大的路径遵循行为.
- 通过Simscape多体模拟和实验测试验证了拟议的控制结构的有效性.
结论:
- 建议的资源效率控制结构有效地平衡了自动驾驶汽车在WNCS中的资源管理和路径跟踪性能.
- 具有预测能力的NUDREKF成功地处理了WNCS的缺点,例如延迟和数据包丢失.
- 该方法提供了一种实用且经过验证的解决方案,用于在无线环境中增强自动驾驶汽车的控制.
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