基于塔卡吉-苏杰诺模糊模型的智能农业机器斯塔克尔伯格对纵向和横向游戏控制的研究
Guangfei Xu1, Dexi Wu2, Haizhu Xu3
1School of Mechanical and Automotive Engineering Liaocheng University Liaocheng China.
Food science & nutrition
|September 12, 2025
概括
本研究介绍了Takagi-Sugeno (T-S) 模糊模型Stackelberg游戏控制算法,以解决智能农业机械控制中的合干扰. 新的算法通过管理动态模型参数变化来提高控制性能.
科学领域:
- 农业工程 农业工程
- 控制系统 控制系统
- 人工智能的人工智能
背景情况:
- 智能农业机械在纵向和横向控制中面临着合干扰的挑战.
- 动态模型中的实时参数变化会降低控制器的性能.
研究的目的:
- 提出一个新的Takagi-Sugeno (T-S) 模糊模型Stackelberg游戏控制算法.
- 克服智能农业机械现有控制方法的局限性.
主要方法:
- 根据系统特征确定模型参数.
- 设计了一个TS模糊模型,具有定义的会员功能.
- 开发了一个TS Stackelberg游戏控制器.
主要成果:
- 提议的TS Stackelberg游戏控制算法有效地解决了合干扰.
- 尽管动态参数发生了变化,但控制器表现出更好的性能.
- 硬件在循环中的实验验验证了算法的可靠性.
结论:
- 斯塔克尔伯格游戏控制算法提供了一个强大的解决方案,用于智能农业机械.
- 这种方法在复杂的操作环境中提高了控制精度和稳定性.
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