Fractional Fuzzy Adaptive Sliding-Mode Control of a 2-DOF Direct-Drive Robot Arm
Fractional Fuzzy Adaptive Sliding-Mode Control of a 2-DOF Direct-Drive Robot Arm
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DOI：
10.1109/tsmcb.2008.928227
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发表时间：
2008-12-01
影响因子：
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通讯作者：
Efe, Mehmet Oender
中科院分区：
文献类型：
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作者：
Efe, Mehmet Oender
本文提出了一种新的参数调整方案，以提高模糊滑模控制的鲁棒性实现了使用自适应神经模糊推理系统（ANFIS）的结构。该方案在参数整定阶段采用分数阶积分。调整控制器的参数，使得在控制下的系统被驱动向传统意义上的滑动政权。与经典的整数阶对应的比较后，可以看出，所提出的自适应方案的控制系统显示出更好的跟踪性能，并观察到非常高的鲁棒性和对干扰的不敏感性。索赔是合理的，通过一些模拟利用2自由度直接驱动机器人手臂的动态模型。总体而言，本文的贡献是证明控制下的系统的响应是显着更好的分数阶集成利用在参数自适应阶段比经典的整数阶集成。
This paper presents a novel parameter adjustment scheme to improve the robustness of fuzzy sliding-mode control achieved by the use of an adaptive neuro-fuzzy inference system (ANFIS) architecture. The proposed scheme utilizes fractional-order integration in the parameter tuning stage. The controller parameters are tuned such that the system under control is driven toward the sliding regime in the traditional sense. After a comparison with the classical integer-order counterpart, it is seen that the control system with the proposed adaptation scheme displays better tracking performance, and a very high degree of robustness and insensitivity to disturbances are observed. The claims are justified through some simulations utilizing the dynamic model of a 2-DOF direct-drive robot arm. Overall, the contribution of this paper is to demonstrate that the response of the system under control is significantly better for the fractional-order integration exploited in the parameter adaptation stage than that for the classical integer-order integration.