## Intelligent Control Systems Using Computational Intelligence TechniquesIntelligent Control techniques are becoming important tools in both academia and industry. Methodologies developed in the field of soft-computing, such as neural networks, fuzzy systems and evolutionary computation, can lead to accommodation of more complex processes, improved performance and considerable time savings and cost reductions. |

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### Contents

An overview of nonlinear identification and control with | 1 |

Notes | 33 |

References | 79 |

Multiobjective evolutionary computing solutions for control | 89 |

Adaptive local linear modelling and control of nonlinear | 119 |

Nonlinear system identification with local linear | 153 |

Gaussian process approaches to nonlinear modelling | 177 |

Neurofuzzy model construction design and estimation | 219 |

A neural network approach for nearly optimal control | 253 |

Reinforcement learning for online control and optimisation | 293 |

Reinforcement learning and multiagent control within | 327 |

Combined computational intelligence and analytical methods | 349 |

Application of intelligent control to autonomous search | 393 |

Applications of intelligent control in medicine | 415 |

447 | |

### Other editions - View all

Intelligent Control Systems Using Computational Intelligence Techniques A.E. Ruano Limited preview - 2005 |