概括
这项研究引入了使用自适应神经模糊推理系统 (ANFIS) 的智能控制系统,以提高车辆的稳定性. 通过ANFIS控制的活性稳定棒显著降低了翻转风险,并改善了方向盘操作期间的车轮路面相互作用.
科学领域:
- 汽车工程 汽车工程
- 控制系统 控制系统
- 人工智能的人工智能
背景情况:
- 车辆翻转在方向盘操纵过程中是一个关键的安全问题.
- 传统的反滚系统在积极管理车辆动态方面存在局限性.
- 智能控制为先进的稳定性增强提供了潜力.
研究的目的:
- 开发和评估一种适应性神经模糊推理系统 (ANFIS),用于控制活性稳定棒.
- 证明ANFIS在防止车辆翻转方面优于PID和被动系统.
- 在动态转向条件下改善车辆稳定性和车轮路面相互作用.
主要方法:
- 实施ANFIS算法来控制主动反滚系统.
- 训练ANFIS使用从以前的研究精心挑选的数据.
- 与比例积分导数 (PID) 和被动 (机械) 系统进行比较模拟分析.
主要成果:
- ANFIS显著减少了滚动角度从8.15°降至6.87°,超过了PID (7.08°) 和被动 (7.80°) 系统的性能.
- 安菲斯控制器将车轮的垂直力从671.06N增加到3030.40N,提高了稳定性.
- 在高速 (80-90公里/小时) 时,使用ANFIS可以防止翻转,与没有活跃杆的系统不同.
结论:
- 安菲斯为主动反滚系统提供了高效的智能控制解决方案.
- 拟议的ANFIS控制器在各种驾驶条件下确保了强大的车辆滚动稳定性.
- 由ANFIS管理的活性稳定棒在防止翻转和保持轮胎接触方面提供了卓越的性能.
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