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.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
Copyright information
© 2019 Springer Nature Switzerland AG
About this chapter
Cite this chapter
Patan, K. (2019). Concluding Remarks and Further Research Directions. In: Robust and Fault-Tolerant Control. Studies in Systems, Decision and Control, vol 197. Springer, Cham. https://doi.org/10.1007/978-3-030-11869-3_7
Download citation
DOI: https://doi.org/10.1007/978-3-030-11869-3_7
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-11868-6
Online ISBN: 978-3-030-11869-3
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)