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Self-Structured Organizing Single-Input CMAC Control for Robot Manipulator
Author(s) -
Thanh Quyen Ngo,
Yaonan Wang
Publication year - 2011
Publication title -
international journal of advanced robotic systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.394
H-Index - 46
eISSN - 1729-8814
pISSN - 1729-8806
DOI - 10.5772/45695
Subject(s) - cerebellar model articulation controller , computer science , control theory (sociology) , controller (irrigation) , robot , lyapunov function , position (finance) , scheme (mathematics) , stability (learning theory) , differentiable function , control engineering , control (management) , artificial intelligence , nonlinear system , mathematics , mathematical analysis , physics , finance , quantum mechanics , agronomy , economics , biology , engineering , machine learning
This paper represents a self-structured organizing single-input control system based on differentiable cerebellar model articulation controller (CMAC) for an n-link robot manipulator to achieve the high-precision position tracking. In the proposed scheme, the single-input CMAC controller is solely used to control the plant, so the input space dimension of CMAC can be simplified and no conventional controller is needed. The structure of single-input CMAC will also be self-organized; that is, the layers of single-input CMAC will grow or prune systematically and their receptive functions can be automatically adjusted. The online tuning laws of single-input CMAC parameters are derived in gradient-descent learning method and the discrete-type Lyapunov function is applied to determine the learning rates of proposed control system so that the stability of the system can be guaranteed. The simulation results of robot manipulator are provided to verify the effectiveness of the proposed control methodology

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