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• W2998263492 abstract "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." @default.
• W2998263492 created "2020-01-10" @default.
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• W2998263492 date "2020-05-01" @default.
• W2998263492 modified "2023-10-02" @default.
• W2998263492 title "Controlling wheeled mobile robot considering the effects of uncertainty with neuro-fuzzy cognitive map" @default.
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• W2998263492 doi "https://doi.org/10.1016/j.isatra.2019.12.011" @default.
• W2998263492 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/31916988" @default.
• W2998263492 hasPublicationYear "2020" @default.
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