ROBUST NONLINEAR CONTROL AND ESTIMATION OF A PRRR ROBOT SYSTEM
Mohammad Al‐Shabi, Khaled S. Hatamleh, S. Andrew Gadsden, Bassel Soudan, A. Elnady
- 发表年份
- 2019
- 引用次数
- 23
摘要
In this paper, a newly proposed implementation of an unscented Kalman (UK)-based smooth variable structure filter (UK-SVSF) is introduced. The method is combined with a sliding mode controller (SMC) to compensate for modelling uncertainties. The robustness and tracking accuracy of the proposed controller and estimation strategy are demonstrated on a four-degree-of-freedom robotic system with one prismatic and three rotary joints. The effectiveness of the proposed combination is proven through comparisons with three different non-linear estimation algorithms: the standard unscented Kalman filter, SVSF, and a previously published UK-SVSF. The robot's trajectory following accuracy and efficiency are used as the performance parameters to study and compare the different strategies. Modelling uncertainties are added to the system to provide a more thorough evaluation of the robustness of the different non-linear control and estimation strategies.
关键词
相关论文
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
Artificial intelligence: a modern approach
1995
Fractional Differential Equations
Igor Podlubný
2025
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991