ࡱ> #` R6Cbjbj9`l/ox~nnnnnnn$phs\nE"nn])])])"~n])~n])])]^J c @O*f _4ln0/o_(ks$8ksh c cksj])nn'>/oD  0!j|c6R 0SYef['Y~ e z Ty: Fuzzy Control zS0201612 ;`f[e32 vQ-Ntf[e32 Sf[e28 ;`f[R2 HQO zꁨRc6Rt`! (uNNꁨRS _USMO5uP[Oo`Nc6R] zf[b ꁨRSYex[ gb{NY[m [!hN _ec N0 zYef[Q[ Chapter 1 Introduction 1.1 Two Examples example 1: human and age; example 2: parking. 1.2 Fuzzy Control Theory incompatibility theory; development of fuzzy control theory. 1.3 Characteristics of Fuzzy Control advantages of fuzzy control; tasks of fuzzy control. Chapter 2 Fuzzy Mathematics 2.1 Classical Set basic definitions; cartesian product of sets; mapping and relation; operation characters of sets; expression of classical sets. 2.2 Fuzzy Set basic definitions; different ways to describe fuzzy sets; operation of fuzzy sets; operation characters of fuzzy sets. 2.3 Disintegrating Theorem and Expanding Theorem disintegrating theorem; expanding theorem. 2.4 Membership Function methods of finding membership function; some kinds of membership function. 2.5 Fuzzy Matrix basic definitions of fuzzy matrix; support of fuzzy matrix; composition of fuzzy matrix; transpose of fuzzy matrix. 2.6 Fuzzy Relation definition of fuzzy relation; operation of fuzzy relation; composition of fuzzy relation. 2.7 Fuzzy Vector definition of fuzzy vector; cartesian product of fuzzy vector; dot product of fuzzy vector. 2.8 Fuzzy Logic and Fuzzy Reasoning fuzzy logic; fuzzy linguistic operator; fuzzy linguistic variable; fuzzy reasoning. Chapter 3 Fuzzy Control 3.1 Fuzzy Control Theory composition of fuzzy control system; principle of fuzzy control system; an example. 3.2 Design of Fuzzy Logic Controller input and output variables; fuzzification method of the crisp data; defuzzification methods; choose the universe of discourse and parameters of the fuzzy controller; fuzzy control rules; fuzzy rogatory table. 3.3 Example of Fuzzy Control an example of fuzzy control. ,{Vz 9eU!j|c6R|~'`vel c6RĉRStev!j|c6RhV S㉐gcvc6RĉR&^ gUS*NbY*NteVP[vc6RĉR0 !j|PID YTc6R PIDc6RhV!j|PID YTc6RhV0 !j|~b_ YTc6R !j|c6RhVN~Wc6RhVv~T0 ,{V !j|c6R^(u>NO !j|c6R5uQ{!j|c6Rmc:g0 N0`N0XQ[ 1[,{NzvQ[[c`NN!k cc!j|w5 !j|ƖT !j|Tϑ !j|sQ|I{vЏ{0 2[,{ NzvQ[[c`NN!k cc!j|c6RhVvelS^(u0 3[ O~c6RelT!j|c6RelvTO:p[c0 Yef['Y~ffN N0 zv'`(NNR ,g z/fꁨRSNNvNNN O z0 O~vc6Rel OY~xQc6RtTsNc6RtGW/f^z(W|~v|nxpef[!jWKN Nv !j|c6RelR^\Nzfc6Rtu [SNEQR)R(uNv~ĉR eg㉳QNel^zw|nxpef[!jWv|~vc6R0_,g zvvv(WNSN_bf[uvwƋb fRhQbvN㉧c6R{| z0 N0 zNvQN zvT|NR] ,g z/f~ꁨRc6RtTsNc6Rt zKNTvSN蕧c6Rt z0,g z^\Nzfc6RelvNy /fc6RelvbU\ [SN O~vPIDc6RelNS^y~Q~I{zfc6Relv~Teg[uNǏ zۏLc6R0 N0TzQ[vW,gBlS͑p0p Chapter 1 Introduction Basic Requirements: incompatibility theory; development of fuzzy control theory; advantages of fuzzy control; tasks of fuzzy control. Key Points: incompatibility theory; development of fuzzy control theory. 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Key Points: fuzzy set; disintegrating theorem and expanding theorem; membership function; fuzzy matrixfuzzy relation; fuzzy vector; fuzzy logic and fuzzy reasoning. Difficulty: fuzzy relation; fuzzy logic and fuzzy reasoning. Chapter 3: Fuzzy Control Basic Requirements: fuzzy control theory; design of fuzzy logic controller; an example of fuzzy control. Key Points: design of fuzzy logic controller. Difficulty: design of fuzzy logic controller. ,{Vz 9eU!j|c6R|~'`vel W,gBlN㉧c6RĉRStev!j|c6RhVT!j|~'` YTc6Rcc!j|PID YTc6Rel0 V0`N0XBl 1.[,{NzvQ[[c`NN!k Ǐ~`Nvb__egcc!j|w5 !j|ƖT !j|Tϑ !j|sQ|I{vЏ{0 2[,{ NzvQ[[c`NN!k Ǐ[E] zyv^(uegcc!j|c6RhVvelS^(u0 3. Џ(u z^Nw[kveleg[ O~c6RelT!j|c6RelvTO:pۏL0 N0f[eRM^ f[e\ Sf[e,{Nz333,{Nz162 162 162 ,{ Nz92 92 92 ,{Vz220 Y`N :gR220T323228mQ0cPYePgT;NSYePg cPYePg 1!j|c6RSYef[IN Y[m 2006t^0 SYePg 1Fuzzy Control, Kevin M. Passino, Stephen Yurkovich, nNS'Yf[QHr>y0 2Fuzzy Set Theory and Its Application, H. J. 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