NDLI: An implementation of Functional Neural Fuzzy Controller for the electrical 6-DOF Stewart Platform

Content Provider	IEEE Xplore Digital Library
Author	Chia-Hu Hsu Sheng-Fu Liang Cheng-Jian Lin Siao-Yin Wu
Copyright Year	2011
Description	Author affiliation: Department of Computer Science and Information Engineering, National Chin-Yi University of Technology, Taichung, Taiwan (Cheng-Jian Lin; Siao-Yin Wu) \|\| Department of Computer Science and Information Engineering, National Cheng Kung University, Tainan, Taiwan (Chia-Hu Hsu; Sheng-Fu Liang)
Abstract	The main research aim of this thesis is to design the system architecture of the Stewart Platform in order to make the related operational processes being more efficient and convenient. As the result, we developed a graphical user interface for the goal of effective adjustment of corresponding control parameters, which is implemented by I/O signal cards to transmit the data files between the control console and the platform. In other words, within the limited working space, we can control the motion cueing of the platform arbitrarily and immediately. The Functional Neural Fuzzy Controller (FNFC) was developed by our Lab, while the corresponding algorithms consist of the structure and parameter learning processes. The process of structure learning is based on the entropy measurement to decide whether there should be added one more fuzzy rule, and the backpropagation method is used in the parameter learning to adjust all free parameters of the neural network. Comparing to the existing PID controllers for evaluation of motion platforms, our approach could provide better performance, reduce the corresponding complexity, and minimize the error between actual length and commanded length of the platform's actuators. In order to maximize the working space within the realistic limited range and to simulate the large scale motions of the relative acceleration and angular velocity and to make experienced pilots feeling more realistically under their operations, we applied the algorithm of the washout filter to immediately and smoothly perform each commanded motion cues on our platform. Lastly, we compared our proposed approach with other methods to prove the effectiveness of our neural architecture and the corresponding algorithms.
Starting Page	292
Ending Page	297
File Size	348439
Page Count	6
File Format	PDF
ISBN	9781612843513
e-ISBN	9781612844718
e-ISBN	9781612844725
DOI	10.1109/ICSSE.2011.5961916
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-06-08
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Stewart Platform Actuators PID Controller Low pass filters Computer architecture Artificial neural networks Aerospace electronics Entropy Acceleration Washout Filter Functional Neural Fuzzy Controller
Content Type	Text
Resource Type	Article

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