A First Course in FUZZY and NEURAL CONTROL

252 CHAPTER 8. APPLICATIONS optimum heat extraction can be achieved. For this purpose, a fuzzy logic-based scheme is proposed. F ...

8.2. COOLING SCHEME FOR LASER MATERIALS 253 fuzzy logic-based system. This feature is the most significant benefit derived from ...

254 CHAPTER 8. APPLICATIONS empirical relationship governing the heat pumped at the cold surface given by a commercially availab ...

8.2. COOLING SCHEME FOR LASER MATERIALS 255 Figure 8.4. Simulation results with prototype membership functions Figure 8.5. Effec ...

256 CHAPTER 8. APPLICATIONS Figure 8.2. Figure 8.6. Critically damped response 8.3 Color quality processing Color matching is an ...

8.3. COLOR QUALITY PROCESSING 257 factors, metamerism, and texture and composition of the material (substrate), has made visual ...

258 CHAPTER 8. APPLICATIONS solution to the changes required in the colorant concentrations. Final analysis is based upon a visu ...

8.3. COLOR QUALITY PROCESSING 259 Figure 8.7 Triangular membership functions defining the inputs and the output The fuzzy contro ...

260 CHAPTER 8. APPLICATIONS absorption characteristics of the sample, sample thickness, and sample texture are implicitly accoun ...

8.3. COLOR QUALITY PROCESSING 261 These equations, given in [7], are: X−X 0 =(X−X 1 )∆C 1 +(X−X 2 )∆C 2 +(X−X 3 )∆C 3 (8.1) Y−Y ...

262 CHAPTER 8. APPLICATIONS be pointed out that in dye-mixing processes, the desired color match is obtained by systematically a ...

8.4. IDENTIFICATION OF TRASH IN COTTON 263 dynamic allocation of cleaning equipment to produce high-quality cotton. In this exam ...

264 CHAPTER 8. APPLICATIONS in Figure 8.12 (b), where nodes of the same layer have similar functions. In the discussion, the ter ...

8.4. IDENTIFICATION OF TRASH IN COTTON 265 Layer 5: The single node in this layer is afixed node labeled P ,which computes the o ...

266 CHAPTER 8. APPLICATIONS consequent membership function and afiring strength. For the Mamdani fuzzy inference system with max ...

8.4. IDENTIFICATION OF TRASH IN COTTON 267 In many instances, the row vectors of matrixA(and the corresponding elements ind) are ...

268 CHAPTER 8. APPLICATIONS Table 8.5. Linguistic variables and linguistic values for fuzzy ìIf... then... î rules Linguistic Va ...

8.4. IDENTIFICATION OF TRASH IN COTTON 269 the sigmoidal membership functions are smooth and nonlinear functions and are increas ...

270 CHAPTER 8. APPLICATIONS R^9 :Ifareais large andsolidityis medium andEdifis small, then trash type is bark. R^10 :Ifareais la ...

8.4. IDENTIFICATION OF TRASH IN COTTON 271 Figure 8.14. ANFIS structure for identification of trash types There are a total of 6 ...