Title :
Control of continuous-time nonlinear systems using neural networks
Author :
He, Shouling ; Reif, Konrad ; Unbehauen, Rolf
Author_Institution :
Lehrstuhl fur Allgemeine und Theor. Elektrotech., Erlangen-Nurnberg Univ., Germany
Abstract :
The main objective of this paper is to discuss training neural networks for control of continuous-time nonlinear systems. Here multilayer neural networks are employed, which are trained by dynamic and static backpropagations. The control with feedback linearization is applied to solving control of a nonlinear dynamical system. A simulation is given to complete the discussion
Keywords :
backpropagation; continuous time systems; feedback; multilayer perceptrons; neurocontrollers; nonlinear control systems; nonlinear dynamical systems; continuous-time nonlinear systems; dynamic backpropagations; feedback linearization; multilayer neural networks; static backpropagations; Backpropagation; Control systems; Linear feedback control systems; Multi-layer neural network; Neural networks; Neurofeedback; Nonlinear control systems; Nonlinear dynamical systems; Nonlinear systems; Vectors;
Conference_Titel :
Neural Networks for Identification, Control, Robotics, and Signal/Image Processing, 1996. Proceedings., International Workshop on
Conference_Location :
Venice
Print_ISBN :
0-8186-7456-3
DOI :
10.1109/NICRSP.1996.542784
