Identification and control of a non-minimum phase flexible dynamical system using neural networks

2002 ◽  
Author(s):  
M. Sasaki ◽  
A. Ogasawara ◽  
M. Kawafuku
Keyword(s):  
Dynamical System ◽  
Neural Networks ◽  
Minimum Phase ◽  
And Control

MODELING A NONLINEAR LIQUID LEVEL SYSTEM BY CELLULAR NEURAL NETWORKS

2010 ◽  
Vol 21 (04) ◽  
pp. 489-501
Author(s):  
NORBERTO HERNANDEZ-ROMERO ◽  
JUAN CARLOS SECK-TUOH-MORA ◽  
MANUEL GONZALEZ-HERNANDEZ ◽  
JOSELITO MEDINA-MARIN ◽  
JUAN JOSE FLORES-ROMERO
Keyword(s):  
Dynamical System ◽  
Neural Networks ◽  
Block Diagram ◽  
Nonlinear Dynamical System ◽  
Cellular Neural Networks ◽  
Liquid Level ◽  
Level System ◽  
Exact Linearization ◽  
Modeling And Control ◽  
And Control

This paper presents the analogue simulation of a nonlinear liquid level system composed by two tanks; the system is controlled using the methodology of exact linearization via state feedback by cellular neural networks (CNNs). The relevance of this manuscript is to show how a block diagram representing the analogue modeling and control of a nonlinear dynamical system, can be implemented and regulated by CNNs, whose cells may contain numerical values or arithmetic and control operations. In this way the dynamical system is modeled by a set of local-interacting elements without need of a central supervisor.

Artificial Neural Networks vs. Fuzzy Logic: Simple Tools to Predict and Control Complex Processes—Application to Plasma Spray Processes

2008 ◽  
Vol 17 (3) ◽  
pp. 365-376 ◽  
Author(s):  
Abdoul-Fatah Kanta ◽  
Ghislain Montavon ◽  
Michel Vardelle ◽  
Marie-Pierre Planche ◽  
Christopher C. Berndt ◽  
...  
Keyword(s):  
Neural Networks ◽  
Fuzzy Logic ◽  
Artificial Neural Networks ◽  
Plasma Spray ◽  
Complex Processes ◽  
Artificial Neural ◽  
And Control ◽  
Control Complex

Einsatz von künstlichen neuronalen Netzwerken an Scannersystemen*/Application of artificial neural networks on scanner systems

2017 ◽  
Vol 107 (07-08) ◽  
pp. 536-540
Author(s):  
S. J. Pieczona ◽  
F. Muratore ◽  
M. F. Prof. Zäh
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Artificial Neural ◽  
And Control ◽  
Dynamic Enhancement

Zur Dynamiksteigerung von Scannersystemen werden verschiedene Arten von Modellierungs- und Regelungsmethoden in der Forschung genutzt. Jedoch sind Nichtlinearitäten, welche das Systemverhalten nachweisbar beeinflussen, in aller Regel nicht Teil der Untersuchung. Mit der Anwendung künstlicher neuronaler Netzwerke (KNN) wird das gesamte dynamische Systemverhalten sowohl für ein geregeltes als auch für ein ungeregeltes Scannersystem abgebildet. So wird geklärt, ob sich diese Art der Modellbildung für eine zukünftige Dynamiksteigerung eignet.   To enhance the dynamics of a scanner system, different methods of modelling and control are utilized. Nonlinearities, which have a certain impact on the system’s behavior, are generally ignored, though. By applying artificial neural networks, the overall dynamics of a controlled and an uncontrolled scanner could be represented. Thus, it will be clarified whether this kind of modelling is appropriate for a future dynamic enhancement.

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