自平衡车辆的基于优化的自适应轨迹跟踪控制器设计,具有非对称的规定的性能
Chuan Hu1, Minhao Liu2, Lei Wang2
1School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai 200240 China.
ISA transactions
|March 7, 2024
概括
一个新的自适应控制器通过使用规定的性能和神经网络来解决非线性干扰和未建模的动态来增强自平衡车辆 (SBV) 轨迹跟踪. 这保证了运动稳定性和强度的提高.
科学领域:
- 机器人和控制系统 机器人和控制系统
- 在工程领域的人工智能.
背景情况:
- 自动平衡车辆 (SBV) 面临着非线性外部干扰和非建模动态的挑战,影响轨迹跟踪的准确性和稳定性.
- 在这种复杂的条件下,现有的控制方法可能难以保证瞬态和稳定状态的性能.
研究的目的:
- 为SBVs提出一种新的自适应轨迹跟踪控制器,以确保异常规定的性能.
- 为了增强运动稳定性和强度,对抗非线性干扰和非建模动力学.
主要方法:
- 开发了一种基于动态的速度规划器,以稳定SBV的速度信号.
- 一个规定的性能函数 (PPF) 被设计为定义所需的过渡状态和稳定状态性能 (TSP).
- 基于优化的预测控制 (OPC) 策略与修改的辐射基函数神经网络 (RBFNN) 近似器集成,以弥补不确定性.
主要成果:
- 拟议的控制器证明了SBV的准确轨迹跟踪.
- 修改后的RBFNN有效地弥补了未建模的动态和非线性外部干扰.
- 利亚普诺夫定理被用来证明整个系统的稳定性.
结论:
- 基于异常规定的性能的新型自适应控制器显著改善了SBV轨迹跟踪.
- 该方法提供了对外部干扰和未建模的动态的增强稳定性,通过模拟验证.
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