Title :
Backlash compensation in nonlinear systems using dynamic inversion by neural networks
Author :
Selmic, Rastko R. ; Lewis, Frank L.
Author_Institution :
Autom. & Robotics Res. Inst., Texas Univ., Arlington, TX, USA
Abstract :
A dynamic inversion compensation scheme is presented for backlash. The compensator uses the backstepping technique with neural networks (NN) for inverting the backlash nonlinearity in the feedforward path. The technique provides a general procedure for using NN to determine the dynamic pre-inverse of an invertible dynamical system. A tuning algorithm is presented for the NN backlash compensator which yields a stable closed-loop system
Keywords :
closed loop systems; compensation; control nonlinearities; inverse problems; neurocontrollers; nonlinear systems; stability; backlash compensation; backlash nonlinearity; backstepping; closed-loop system; dynamic inversion; neural networks; neurocontrol; nonlinear systems; stability; tuning algorithm; Actuators; Equations; Feedforward neural networks; Intelligent networks; Neural networks; Neurons; Nonlinear dynamical systems; Nonlinear systems; Robotics and automation; Stability;
Conference_Titel :
Control Applications, 1999. Proceedings of the 1999 IEEE International Conference on
Conference_Location :
Kohala Coast, HI
Print_ISBN :
0-7803-5446-X
DOI :
10.1109/CCA.1999.801137
