一个通用的汉密尔顿强大的轨迹跟踪控制方案,用于智能汽车的轨迹跟踪
Yu Zhang1, Wenhui Pei1, Qi Zhang2
1School of Information Science and Electrical Engineering, Shandong Jiaotong University, Jinan 250357, China.
Sensors (Basel, Switzerland)
|August 12, 2023
概括
使用通用汉密尔顿理论的新型强大的轨迹跟踪控制策略可以改进智能汽车控制. 这种方法提高了准确性和稳定性,显著优于SMC和LQR控制器等现有方法.
科学领域:
- 控制系统工程 控制系统工程
- 机器人技术 机器人技术 机器人技术
- 汽车工程 汽车工程
背景情况:
- 智能车辆轨迹跟踪需要高精度和稳定性.
- 现有的控制策略在性能和稳定性方面存在局限性.
研究的目的:
- 为智能汽车提出基于广义汉密尔顿理论的强有力的轨迹跟踪控制策略.
- 为了提高车辆轨迹跟踪的准确性和稳定性.
主要方法:
- 使用直角分解和控制切换方法设计动态汉密尔顿散热控制器 (DHDC) 和轨迹跟踪汉密尔顿散热控制器 (TTHDC).
- 发展反分散的汉密尔顿实现,以实现系统的融合.
- 基于TTHDC消散式汉密尔顿系统的通用汉密尔顿强控制器 (GHRC) 的设计.
- 使用Carsim和MATLAB/Simulink进行同步模拟进行验证.
主要成果:
- DHDC和TTHDC展示了自我稳定控制和轨迹跟踪能力.
- 与DHDC和TTHDC相比,GHRC显著提高了跟踪精度和稳定性.
- 与SMC和LQR控制器相比,GHRC减少了84.44%的横向误差和83.92%的RMSE.
结论:
- 拟议的通用汉密尔顿稳定控制器 (GHRC) 在精度和稳定性方面提供了卓越的性能,用于智能汽车轨迹跟踪.
- 一般化的汉密尔顿理论为开发先进的车辆控制系统提供了有效的框架.
- 该研究通过全面的模拟来验证拟议的控制器的有效性.
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