## Evolutionary Learning Algorithms for Neural Adaptive ControlAfter an introduction to neural networks and genetic algorithms, this volume describes in detail how neural networks and evolutionary techniques (specifically genetic algorithms and genetic programming) can be applied to the adaptive control of complex dynamic systems (including chaotic ones). A number of examples are presented and useful tips are given for the application of the techniques described. The fundamentals of dynamic systems theory and classical adaptive control are also given. This volume will be of particular interest to undergraduate and postgraduate students taking courses in neural networks, genetic algorithms or control systems, researchers in neural networks and genetic algorithms who need to extend their field of application to dynamic systems and control, and control theorists/professionals who would like to use these advanced learning techniques for solving high-nonlinear control theory problems. |

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### Contents

Introduction | 1 |

Artificial Neural Networks | 47 |

Current Neurocontrol Techniques | 97 |

Copyright | |

3 other sections not shown

### Other editions - View all

Evolutionary Learning Algorithms for Neural Adaptive Control Dimitris C. Dracopoulos Limited preview - 2013 |

Evolutionary Learning Algorithms for Neural Adaptive Control Dimitris Dracopoulos No preview available - 2014 |

### Common terms and phrases

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