Verification of Multilayer Neural-Net Controller in Manipulator Tracking Control
In this paper a multilayer neural-net (NN) controller is applied for tracking control of robotic manipulator, which is a nonlinear object having unknown and changeable parameters. Dynamics equations of a rigid manipulator are presented. The NN controller is used for compensating manipulator nonlinearities. The controller is realized in a form of a multilayer NN, which is nonlinear in the weights. The standard delta rule using backpropagation tuning is inadequate, so a term correcting the delta rule as well as a robustifying term is added. The presented control law and tuning algorithm are derived from the Lyapunov’s direct method. Results of the experiment are presented in this paper.
Andrejus H. Marcinkevičius and Algirdas V.Valiulis
W. Żylski and P. Gierlak, "Verification of Multilayer Neural-Net Controller in Manipulator Tracking Control", Solid State Phenomena, Vol. 164, pp. 99-104, 2010