Literature DB >> 29994372

Fuzzy Neural Network Control of a Flexible Robotic Manipulator Using Assumed Mode Method.

Changyin Sun, Hejia Gao, Wei He, Yao Yu.   

Abstract

In this paper, in order to analyze the single-link flexible structure, the assumed mode method is employed to develop the dynamic model. Based on the discrete dynamic model, fuzzy neural network (NN) control is investigated to track the desired trajectory accurately and to suppress the flexible vibration maximally. To ensure the stability rigorously as the goal, the system is proved to be uniform ultimate boundedness by Lyapunov's stability method. Eventually, simulations verify that the proposed control strategy is effective, and the control performance is compared with the proportion derivative control. The experiments are implemented on the Quanser platform to further demonstrate the feasibility of the proposed fuzzy NN control.

Year:  2018        PMID: 29994372     DOI: 10.1109/TNNLS.2017.2743103

Source DB:  PubMed          Journal:  IEEE Trans Neural Netw Learn Syst        ISSN: 2162-237X            Impact factor:   10.451


  3 in total

1.  A Model-Based Recurrent Neural Network With Randomness for Efficient Control With Applications.

Authors:  Yangming Li; Shuai Li; Blake Hannaford
Journal:  IEEE Trans Industr Inform       Date:  2018-09-10       Impact factor: 10.215

2.  Research on Robot Fuzzy Neural Network Motion System Based on Artificial Intelligence.

Authors:  Jie Hu
Journal:  Comput Intell Neurosci       Date:  2022-02-09

3.  A Trajectory Tracking Control Based on a Terminal Sliding Mode for a Compliant Robot with Nonlinear Stiffness Joints.

Authors:  Zhibin Song; Tianyu Ma; Keke Qi; Emmanouil Spyrakos-Papastavridis; Songyuan Zhang; Rongjie Kang
Journal:  Micromachines (Basel)       Date:  2022-03-04       Impact factor: 2.891

  3 in total

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