Neural Networks and Adaptive Control

  • Andrew G. Barto
  • Vijaykumar Gullapalli
Part of the Research Notes in Neural Computing book series (NEURALCOMPUTING, volume 4)


This chapter provides an overview of some adaptive control methods and how artificial neural networks are being used as components of adaptive control systems. It suggests, however, that the adaptive control methods developed by control engineers can be misleading guides to thinking about control in biological systems. Furthermore, it suggests that neural networks, whether artificial or real, might be most effective when used as components of architectures that are not conservative extensions of conventional adaptive control architectures. After a brief discussion of control, several approaches to adaptive control as developed by control engineers are described, followed by presentation of a view of artificial neural networks and their potential roles in control systems. Two examples are described in which artificial neural networks have been applied successfully to difficult control problems, and a model of the cerebellum is discussed in light of conceptual schemes based on engineering control practice.


Artificial Neural Network Adaptive Control Cerebellar Cortex Control Rule Adaptive Control System 
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 1993

Authors and Affiliations

  • Andrew G. Barto
    • 1
  • Vijaykumar Gullapalli
    • 1
  1. 1.Department of Computer ScienceUniversity of MassachusettsAmherstUSA

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