Adaptive Fuzzy Tracking Control of Flexible-Joint Robots With Full-State Constraints

Adaptive Fuzzy Tracking Control of Flexible-Joint Robots With Full-State Constraints
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全状态约束柔性关节机器人自适应模糊跟踪控制

DOI:
10.1109/tsmc.2018.2870642
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发表时间:
2019-11
期刊:
IEEE Transactions on Systems, Man, and Cybernetics: Systems
影响因子:
--
通讯作者:
Van-Truong Nguyen
Van-Truong Nguyen
中科院分区:
其他
文献类型:
--
作者:
Wei Sun;Shun-Feng Su;Jianwei Xia;Van-Truong Nguyen

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研究了具有全状态约束的柔性关节机器人的自适应模糊跟踪控制。在控制设计中,采用模糊系统对完全未知的非线性函数进行辨识,避免了繁琐的计算。采用tan-型障碍Lyapunov函数来处理状态约束,使控制器在没有状态约束的情况下仍然有效。通过将反推设计方法和自适应模糊控制方法相结合,成功地构造了一种新的SIMPLER控制器,以确保输出跟踪误差收敛到原点的足够小的邻域,同时在运行过程中不违反对系统状态的约束。最后,进行了仿真比较,验证了所提控制方案的有效性。
This paper reports our study on adaptive fuzzy tracking control for flexible-joint robots with full state constraints. In the control design, fuzzy systems are adopted to identify the totally unknown nonlinear functions and can properly avoid burdensome computations. The tan-type barrier Lyapunov functions are used to deal with state constraints so that even without state constraints, the controller is still valid. By combining the method of backstepping design with adaptive fuzzy control approaches, a novel simpler controller is successfully constructed to ensure that the output tracking errors converge to a sufficiently small neighborhood of the origin, while the constraints on the system states will not be violated during operation. Finally, comparison simulations are presented to demonstrate the effectiveness of the proposed control schemes.
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