A Self-Tuning Type Neural Net Controller For Robotic Manipulators

摘要

ABSTRACTThis article presents a self-tuning type neural net controller for robotic manipulators. A parallel recursive adaptation algorithm is described for on-line implementation of the neural net controller. The proposed control scheme does not require any information about the system dynamics. The control system was implemented for a cylindrical robot by computer simulation. The simulation result shows the effectiveness of the neural net controller and its adaptation and learning capability for nonlinear time-varying robot systems.