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ADALINE based robust control in robotics: a Riemann-Liouville fractional differintegration based learning scheme

机译:基于ADALINE的机器人鲁棒控制:基于Riemann-Liouville分数微积分的学习方案

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摘要

This paper presents an approach to improve the performance of intelligent sliding model control achieved by the use of a fundamental constituent of soft computing, named Adaptive Linear Element (ADALINE). The proposed scheme is based on the fractional calculus. A previously considered tuning scheme is revised according to the rules of fractional order differintegration. After a comparison with the integer order counterpart, it is seen that the control system with the proposed adaptation scheme provides (1) better tracking performance, (2) suppression of undesired drifts in parameter evolution and (3) a very high degree of robustness and insensitivity to disturbances. The claims are justified through some simulations utilizing the dynamic model of a two degrees of freedom (DOF) direct drive robot arm and overall, the contribution of the paper is to introduce the fractional order calculus into a robust and nonlinear control problem with some outperforming features that are absent when the integer order differintegration operators are adopted.
机译:本文提出了一种通过使用称为自适应线性元素(ADALINE)的软计算的基本组成部分来提高智能滑模控制性能的方法。提出的方案基于分数演算。根据分数阶微分积分的规则修改了先前考虑的调整方案。与整数阶对应项进行比较后,可以看出采用所提出的自适应方案的控制系统具有(1)更好的跟踪性能,(2)抑制了参数演变中不希望的漂移,以及(3)很高的鲁棒性和对干扰不敏感。通过使用两自由度(DOF)直接驱动机器人手臂和整体的动力学模型进行的一些模拟,可以证明这些要求是正确的。本文的贡献是将分数阶微积分引入具有某些性能优于特征的鲁棒非线性控制问题采用整数阶微分积分算子时不存在。

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