Title :
A nonlinear observer design via differential neural networks for coupled tanks
Author :
Sharifi, Farid ; Menhaj, Mohammad Bagher
Author_Institution :
Electr. Eng. Dept., Amirkabir Univ. of Technol., Tehran
Abstract :
A nonlinear observer for a general class of dynamical nonlinear systems is proposed based on a Differential Neural Networks (DNN). A learning rule to adjust the parameters of the neuro-observer is designed. By a Lyapunov-like analysis, the upper bounds for the weights and the averaged estimation error are derived. To illustrate the applicability of the DNN observer, we consider a coupled tank as a case study. The results of simulation are very promising.
Keywords :
Lyapunov methods; control system synthesis; flow control; level control; neurocontrollers; nonlinear control systems; nonlinear dynamical systems; observers; stability; tanks (containers); Lyapunov method; coupled tank; differential neural network; dynamical nonlinear system; nonlinear observer design; stability; Artificial neural networks; Couplings; Estimation error; Lyapunov method; Neural networks; Nonlinear dynamical systems; Nonlinear systems; Observers; State estimation; Uncertainty; Coupled Tanks; Differential Neural Networks; Dynamic Neural Networks; Nonlinear observer; State Estimation;
Conference_Titel :
Electrical and Computer Engineering, 2008. CCECE 2008. Canadian Conference on
Conference_Location :
Niagara Falls, ON
Print_ISBN :
978-1-4244-1642-4
Electronic_ISBN :
0840-7789
DOI :
10.1109/CCECE.2008.4564783
