Indirect adaptive control of a two-link robot arm using regularization neural networks

An artificial neural network was developed to control the flexibility of a two-link robot arm. The control scheme consists of two regularization networks plus proportional control. One artificial neural network acts as a system identifier using a recursive algorithm and provides time-related system...

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Bibliographic Details
Published inProceedings IECON '91: 1991 International Conference on Industrial Electronics, Control and Instrumentation pp. 952 - 956 vol.2
Main Authors Greene, M.E., Tan, H.
Format Conference Proceeding
LanguageEnglish
Published IEEE 1991
Subjects
Adaptive control
Artificial neural networks
Azimuth
Control systems
Neural networks
Open loop systems
Optical feedback
Optical sensors
Robots
Vectors
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Summary:An artificial neural network was developed to control the flexibility of a two-link robot arm. The control scheme consists of two regularization networks plus proportional control. One artificial neural network acts as a system identifier using a recursive algorithm and provides time-related system information to the vibration controller. The second network acts as a vibration controller whose parameters are varied through minimization of an integral-squared-error cost function. A fixed proportional gain feedback system was used to control the rigid body of the manipulator.< >
ISBN:9780879426880
0879426888
DOI:10.1109/IECON.1991.239162