Title :
Artificial neural networks for real-time process control
Author :
Gulati, Aashish ; Jacobs, Derya A.
Author_Institution :
Dept. of Eng. Manage., Old Dominion Univ., Norfolk, VA, USA
Abstract :
The purpose of this study was to develop a neural network based on real-time control system for fluid level in a given tank. The tank has an “I” shape with a circular cross sectional area varying across the “I” shaped profile height. The simulated “I” shaped tank has a height of 12 meters and divided into three sections. Each of the sections has a height of four meters. The tank is demarcated into water level marks from O m to 12 m at intervals of 1 each. An ANN is designed and developed for real-time control of water level in the tank. The goal was to enable a smooth change in target level at a constant rate of change inspite of the two nonlinearity points introduced by the “I” shaped structure of the tank, after a certain amount of uncontrolled output flow has occurred
Keywords :
control system synthesis; digital control; flow control; learning (artificial intelligence); level control; neurocontrollers; real-time systems; I-shape tank; circular cross sectional area; control design; fluid level; neural network; nonlinearity points; real-time process control; target level; uncontrolled output flow; water level; Alarm systems; Artificial neural networks; Backpropagation; Capacitors; Control systems; Jacobian matrices; Process control; Real time systems; Research and development management; Training data;
Conference_Titel :
Engineering Management Conference, 1994. 'Management in Transition: Engineering a Changing World', Proceedings of the 1994 IEEE International
Conference_Location :
Dayton North, OH
Print_ISBN :
0-7803-1955-9
DOI :
10.1109/IEMC.1994.379923
