Title :
Reinforcing robustness using high order neural network controllers
Author :
Rovithakis, George A.
Author_Institution :
Dept. of Electron. & Comput. Eng., Tech. Univ. of Crete, Chania, Greece
Abstract :
A robustifying control methodology for affine in the control nonlinear dynamical systems, is developed. A correction control signal is added to a nominal controller, (designed to guarantee a desired performance for the corresponding nominal system), to render the actual system uniformly ultimately bounded. The control signal is smooth and doesn´t require the a priori knowledge of an upper bound on the modeling error and/or optimal weight values
Keywords :
neurocontrollers; nonlinear dynamical systems; robust control; affine nonlinear dynamical systems; correction control signal; high order neural network controllers; nominal controller; robustifying control methodology; Computer networks; Control nonlinearities; Control systems; Neural networks; Nonlinear control systems; Optimal control; Robust control; Robust stability; Signal design; Upper bound;
Conference_Titel :
Decision and Control, 1998. Proceedings of the 37th IEEE Conference on
Conference_Location :
Tampa, FL
Print_ISBN :
0-7803-4394-8
DOI :
10.1109/CDC.1998.760836
