滑动模式基于观察者的模型预测跟踪控制用于Mecanum轮式移动机器人.
Dongliang Wang1, Yong Gao2, Wu Wei2
1School of Department of Electronic and Information Engineering, Shantou University, 515063, Guangdong, China; Key Lab of Digital Signal and Image Processing of Guangdong Province, Shantou University, 515063, Guangdong, China.
ISA transactions
|June 30, 2024
概括
一个新的自适应变量功率滑动模式以观察者为基础的模型预测控制 (AVPSMO-MPC) 增强了 Mecanum 轮式移动机器人 (MWMR) 轨迹跟踪. 这种强大的方法确保了精确的控制,尽管存在外部干扰和模型不确定性.
科学领域:
- 机器人和控制系统 机器人和控制系统
- 机械电子学是什么意思 机械电子学
- 应用数学 应用数学 应用数学
背景情况:
- 机械轮式移动机器人 (MWMR) 在轨迹跟踪方面面临挑战,原因是外部干扰和模型不确定性.
- 现有的控制方法在动态操作条件下可能难以保持精度并遵守物理约束.
研究的目的:
- 开发一种新的控制策略,用于精确跟踪MWMR的轨迹.
- 为了增强机器人对外部干扰和内部模型不确定性的强度.
- 确保在运行过程中遵守MWMR的物理限制.
主要方法:
- 基于名义MWMR动态的模型预测控制器 (MPC) 的设计,将轨迹跟踪转化为受约束的二次编程 (QP) 问题.
- 集成自适应变量功率滑动模式观察器 (AVPSMO) 作为前补偿器,以减轻干扰和不确定性.
- 使用利亚普诺夫理论证明AVPSMO稳定的数学证明.
主要成果:
- 拟议的AVPSMO-MPC方法实现了对MWMRs的精确轨迹跟踪.
- 控制策略有效地抑制了外部干扰和模型不确定性的影响.
- 模拟证明了该方法的有效性和稳定性,证实了约束满足.
结论:
- AVPSMO-MPC方法为MWMR轨迹跟踪提供了强大的和有效的解决方案.
- 这种方法在存在动态不确定性的情况下提高了控制精度和可靠性.
- 该研究通过比较模拟验证了拟议方法的性能.
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