An Effective Application of Soft Computing Methods for Hydraulic Process Control

Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 188)

Abstract

The article deals with the modeling and predictive control of real hydraulic system using artificial neural network (ANN). For the design of optimal neural network model structure we developed procedures for creation optimal-minimal structure which ensure desired model accuracy. This procedure was designed using genetic algorithms (GA) in Matlab-Simulink. The predictive control algorithm was implemented using CompactLogix programmable logic controller (PLC). The main aim of the proposed paper is design of methodology and effective real-time algorithm for possible applications in industry.

Keywords

Neural network genetic algorithm predictive control PLC realization optimization methods 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  1. 1.Institute of Control and Industrial Informatics, Faculty of Electrical Engineering and Information TechnologySlovak University of TechnologyBratislavaSlovak Republic

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