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Controlling wheeled mobile robot considering the effects of uncertainty with neuro-fuzzy cognitive map

机译:考虑与神经模糊认知地图的不确定性的影响控制轮式移动机器人

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摘要

In this paper, we present neuro-fuzzy cognitive map (NFCM) to control a non-holonomic wheeled mobile robot, for both the kinematic control and the dynamic control. For this purpose, the rules for updating the parameters of NFCM used in online training have been extracted. Also, the convergence of the presented approach has been confirmed by means of Lyapunov method. To evaluate the strength and robustness of the proposed model, it has been tested in tracking different circular and square paths. Experimental results indicate that despite the presence of disturbances, the changes of system parameters, and the existence of non-holonomic constraints, our robot has been able to follow challenging paths (e.g. square-shape trajectories) successfully. (C) 2020 ISA. Published by Elsevier Ltd. All rights reserved.
机译:在本文中,我们提出了神经模糊认知地图(NFCM)来控制非实体轮式移动机器人,适用于运动控制和动态控制。 为此目的,已提取用于更新在线培训中使用的NFCM参数的规则。 而且,通过Lyapunov方法证实了所提出的方法的收敛。 为了评估所提出的模型的强度和稳健性,已经在跟踪不同的圆形和方形路径时进行了测试。 实验结果表明,尽管存在干扰,系统参数的变化以及非完全限制的存在,我们的机器人能够成功地遵循具有挑战性的路径(例如方形轨迹)。 (c)2020 ISA。 elsevier有限公司出版。保留所有权利。

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