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Concluding Remarks and Further Research Directions

  • Krzysztof PatanEmail author
Chapter
Part of the Studies in Systems, Decision and Control book series (SSDC, volume 197)

Abstract

Owing to their powerful properties, artificial neural networks have become a popular choice in terms of problems occurring in control theory. Furthermore, the following two trends in modern control: robust control and fault-tolerant control can be effectively realized using appropriate neural-network architecture. This monograph is devoted to the selected designs of the robust and fault-tolerant control systems for nonlinear processes. The reported approaches mainly use the capability of a neural network to learn from historical data and to approximate nonlinear functions with an assumed accuracy. These two properties are extremely useful when dealing with nonlinear industrial plants for which a mathematical model is unknown or is very expensive to determine.

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Institute of Control and Computation EngineeringUniversity of Zielona GóraZielona GóraPoland

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