Application of Artificial Neural Network Strategies in Process Control

  • Alojz Mészáros
  • Anton Andrášik
  • Anton Rusnák
Part of the Advances in Soft Computing book series (AINSC, volume 5)


Artificial Neural Networks (ANN) have been enjoying an increasing attention in various fields of theory and application, lately. This contribution addresses the new concepts of introduction of the ANN approach into system identification and control. Both, ANN model based predictive control strategy and adaptive PID control are introduced. To demonstrate the feasibility and the performance of the control schemes, a continuous biochemical reactor is chosen as a realistic non-linear case study. Simulation results demonstrate the usefulness and the robustness of the proposed control algorithms.


Model Predictive Control Feedforward Neural Network Prediction Horizon Artificial Neural Network Approach Stochastic Approximation Algorithm 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2000

Authors and Affiliations

  • Alojz Mészáros
    • 1
  • Anton Andrášik
    • 1
  • Anton Rusnák
    • 1
  1. 1.Department of Process Control, Faculty of Chemical TechnologySlovak University of Technology BratislavaRadlinského 9Bratislava

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