改进了基于前补偿的高速列车自动驾驶的主动干扰排斥速度控制,基于前补偿
Lili Yue1, Yidong Wang1, Baodi Xiao1,2
1School of Automation and Electrical Engineering, Lanzhou Jiaotong University, Lanzhou, China.
Science progress
|October 25, 2023
概括
一种新的前补偿修改主动干扰排斥控制 (FC-MADRC) 算法通过减少模型依赖来增强火车速度控制. 这种先进的控制方法在复杂的操作环境中表现出卓越的抗干扰能力和高跟踪精度.
科学领域:
- 控制系统工程 控制系统工程
- 铁路运输系统 铁路运输系统
- 应用数学 应用数学 应用数学
背景情况:
- 由于复杂,动态的操作环境和时间变化的参数,精确的列车建模具有挑战性.
- 外部干扰对火车速度控制有重大影响,需要强有力的控制策略.
- 现有的控制方法往往严重依赖于精确的列车模型,限制了它们的适用性.
研究的目的:
- 为列车速度控制提出一个修改的主动干扰排斥控制 (FC-MADRC) 算法,以尽量减少模型依赖.
- 为了提高火车速度控制系统的反干扰能力和跟踪精度.
- 在复杂和不可预测的火车运行场景中解决传统控制方法的局限性.
主要方法:
- 开发了一个前补偿修改了主动干扰排斥控制 (FC-MADRC) 算法.
- 使用终端吸引器和Sigmoid函数设计了一个改进的跟踪差分器 (ITD).
- 构建了一个改进的fal (nsfal) 函数,具有整数错误项的改善性非线性状态错误反 (ANLSEF),以及一个修改的扩展状态观察器 (IESO).
- 集成的前和干扰补偿,以实时动态补偿干扰.
主要成果:
- 与传统的ADRC和2DOF-PID控制器相比,FC-MADRC表现出优越的反干扰能力和更高的跟踪精度.
- 使用CRH380A列车数据的模拟验证了算法的有效性.
- 拟议的方法在外部干扰和不同的道路条件下实现了准确的速度跟踪.
结论:
- 在火车速度控制方面,FC-MADRC在稳固性,快速响应和高跟踪精度方面具有显著的优势.
- 该算法有效地减轻了外部干扰的影响,而不依赖于精确的火车模型.
- 这种方法为在具有挑战性的操作环境中精确调节火车速度提供了可行的解决方案.
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