## Fuzzy Logic and Intelligent SystemsHua Li, Madan M. Gupta One of the attractions of fuzzy logic is its utility in solving many real engineering problems. As many have realised, the major obstacles in building a real intelligent machine involve dealing with random disturbances, processing large amounts of imprecise data, interacting with a dynamically changing environment, and coping with uncertainty. Neural-fuzzy techniques help one to solve many of these problems. Fuzzy Logic and Intelligent Systems reflects the most recent developments in neural networks and fuzzy logic, and their application in intelligent systems. In addition, the balance between theoretical work and applications makes the book suitable for both researchers and engineers, as well as for graduate students. |

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### Contents

CAMCORDER OPERATION JUDGEMENT | 14 |

BASIS FUNCTIONS FOR FUNCTIONAL | 17 |

V | 52 |

REFERENCES | 56 |

MODEL REDUCTION AND CONTROL | 58 |

REFERENCES | 85 |

REFERENCES | 115 |

5 | 125 |

157 | 269 |

USING FPGA TECHNIQUE FOR DESIGN | 271 |

90 | 285 |

REFERENCES | 287 |

A SIMPLE DIRECT ADAPTIVE FUZZY CONTROL | 293 |

AN ADAPTIVE FUZZY | 300 |

245 | 308 |

125 | 358 |

6 | 157 |

INDEX | 168 |

DESIGN OF FUZZY CONTROLLERS BASED | 187 |

REFERENCES | 202 |

FUZZY INFERENCE INTEGRATING | 213 |

17 | 215 |

27 | 232 |

9 | 245 |

50 | 263 |

158 | 363 |

271 | 366 |

126 | 372 |

187 | 400 |

291 | 401 |

138 | 403 |

198 | 435 |

200 | 442 |

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### Common terms and phrases

adaptive control algorithm angle applications backpropagation calibration camera change in error classical controller computation continuous functions control action control rules control system deﬁned deﬁnition defuzziﬁcation Design Procedure DRNN dynamic equation feedback controller feedforward ﬁgure ﬁnal ﬁne ﬁrst FPGA fuzzy control fuzzy control system fuzzy inference fuzzy logic controller fuzzy partition fuzzy phase-lead compensator fuzzy PID fuzzy sets fuzzy system Gaussian GESA given hand-eye hardware identiﬁcation IEEE implemented inference rules learning LED displacement sensor linear controller linguistic matrix measurement system membership functions method NB NB NB neural networks NM NL nonlinear system object operation optimal control parameters PB PB PB PDFLC performance PFLC PID controller PL PM position problem Proc recurrent neural network robot satisﬁed shown in Figure sigmoidal function simulation solution step Stone-Weierstrass theorem subspace technique theorem universal approximator universe of discourse unknown plant vector vision system zero