Title :
Nonlinear system adaptive trajectory tracking by dynamic neural control
Author :
Sanchez, Edgar N. ; Bernal, Miguel A.
Author_Institution :
CINVESTAV, Guadalajara, Mexico
Abstract :
In this article, new nonlinear control techniques based on dynamic neural networks are presented. The authors discuss the implementation of a modified identification algorithm using dynamic neural networks as well as a control law, based on the neural identifier, which eliminates modeling error effects via sliding mode techniques. Simulation and real time results are presented for systems like an inverted pendulum and a full actuated robot manipulator
Keywords :
adaptive control; identification; neurocontrollers; nonlinear control systems; pendulums; robot dynamics; tracking; variable structure systems; adaptive control; dynamic neural networks; identification; inverted pendulum; neurocontrol; nonlinear control; robot manipulator; sliding mode method; trajectory tracking; Adaptive systems; Error correction; Heuristic algorithms; Neural networks; Nonlinear dynamical systems; Nonlinear systems; Real time systems; Robots; Sliding mode control; Trajectory;
Conference_Titel :
Neural Networks, 1999. IJCNN '99. International Joint Conference on
Conference_Location :
Washington, DC
Print_ISBN :
0-7803-5529-6
DOI :
10.1109/IJCNN.1999.832713
