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http://dx.doi.org/10.5207/JIEIE.2011.25.9.050

Application of Neural Network Adaptive Control for Real-time Attitude Control of Multi-Articulated Robot  

Lee, Seong-Su (한국폴리텍VI대학 포항캠퍼스 전기제어과)
Park, Wal-Seo (원광대학교 공과대학 전기전자공학부)
Publication Information
Journal of the Korean Institute of Illuminating and Electrical Installation Engineers / v.25, no.9, 2011 , pp. 50-55 More about this Journal
Abstract
This research is to apply the adaptive control of neuron networks for the real-time attitude control of Multi-articulated robot. Multi-articulated robot is expressed with a complicated mathematical model on account of the mechanic, electric non-linearity which each articulation of mechanism has, and includes an unstable factor in time of attitude control. If such a complex expression is included in control operation, it leads to the disadvantage that operation time is lengthened. Thus, if the rapid change of the load or the disturbance is given, it is difficult to fulfill the control of desired performance. In this research we used the response property curve of the robot instead of the activation function of neural network algorithms, so the adaptive control system of neural networks constructed without the information of modeling can perform a real-time control. The proposed adaptive control algorithm generated control signs corresponding to the non-linearity of Multi-articulated robot, which could generate desired motion in real time.
Keywords
Multi-articulated robot; Attitude Control; Neural Network; Real-Time;
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