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二型模糊逻辑:非确定系统建模与控制 (英文版) Type-2 Fuzzy Logic:Uncertain Systems’ Modeling and Contr


作者:
Rómulo Antão (安塔奥)
定价:
79.00 元
版面字数:
130千字
开本:
16开
装帧形式:
精装
版次:
1
最新版次
印刷时间:
2017年
ISBN:
978-7-04-047809-9
物料号:
47809-00
出版时间:
2017-09-21
读者对象:
学术著作
一级分类:
自然科学
二级分类:
数学与统计
三级分类:
计算数学

暂无
  • 目录
    • 前辅文
      • 1 Introduction
        • 1.1 Book Outline
          • References
          • 2 Fuzzy Logic Systems
            • 2.1 Introduction
              • 2.2 Type-1 Fuzzy Sets
                • 2.3 Type-1 Fuzzy Logic Systems
                  • 2.3.1 Fuzzifier
                    • 2.3.2 Rule-Base
                      • 2.3.3 Inference Engine
                        • 2.3.4 Output Processor
                          • 2.3.5 Considerations About Type-1 Fuzzy Logic Systems
                          • 2.4 Type-2 Fuzzy Sets
                            • 2.5 Type-2 Fuzzy Logic Systems
                              • 2.5.1 Fuzzifier
                                • 2.5.2 Rule-Base
                                  • 2.5.3 Inference Engine
                                    • 2.5.4 Type-Reduction
                                      • 2.5.5 Defuzzifier
                                      • 2.6 Comparative Analysis
                                        • 2.7 Conclusions
                                          • References
                                          • 3 Takagi-Sugeno Fuzzy Logic Systems
                                            • 3.1 Introduction
                                              • 3.2 Type-1 Takagi-Sugeno Fuzzy Logic Systems
                                                • 3.3 Type-2 Takagi-Sugeno Fuzzy Logic Systems
                                                  • 3.3.1 A2-C1 Structure
                                                    • 3.3.2 A2-C0 Structure
                                                      • 3.3.3 A1-C1 Structure
                                                      • 3.4 ANFIS Based on Type-2 TS Fuzzy Logic Systems
                                                        • 3.5 Training Algorithms for TS Fuzzy Systems
                                                          • 3.5.1 Model Initialization
                                                            • 3.5.2 Training of the Antecedent Part of the Rule Base
                                                              • 3.5.3 Training of the Consequent Part of the Rule Base
                                                              • 3.6 Conclusions
                                                                • References
                                                                • 4 System Modeling Using Type-2 Takagi-Sugeno Fuzzy Systems
                                                                  • 4.1 Introduction
                                                                    • 4.2 Locally Linear Models Based on Type-2 TS Fuzzy Logic Systems
                                                                      • 4.2.1 Development of the Interpolated Interval Type-2 Fuzzy Model
                                                                        • 4.2.2 Development of the n-step Ahead Predictor
                                                                        • 4.3 Application Scenarios
                                                                          • 4.3.1 Fermentation Reactor Modeling
                                                                            • 4.3.2 Coupled Tanks Modeling
                                                                            • 4.4 Conclusions
                                                                              • References
                                                                              • 5 Model Predictive Control Using Type-2 Takagi-Sugeno Fuzzy Systems
                                                                                • 5.1 Introduction
                                                                                  • 5.2 Generalized Predictive Control
                                                                                    • 5.3 Derivation of a n-step Ahead Predictor
                                                                                      • 5.4 Extension of Generalized Predictive Control to Non-linear Models
                                                                                        • 5.4.1 Generalized Predictive Control Using Type-2 TS Fuzzy Models
                                                                                        • 5.5 Application Scenarios
                                                                                          • 5.5.1 Fermentation Reactor’s Temperature Control
                                                                                            • 5.5.2 Coupled Tanks Liquid Level Control
                                                                                            • 5.6 Conclusions
                                                                                              • References
                                                                                              • 6 Processor-In-the-Loop Simulation
                                                                                                • 6.1 Introduction
                                                                                                  • 6.2 PIL Architecture
                                                                                                    • 6.2.1 Development Board
                                                                                                      • 6.2.2 Embedded System’s Software Architecture
                                                                                                      • 6.3 System Evaluation
                                                                                                        • 6.4 Conclusions
                                                                                                          • References
                                                                                                          • 7 Conclusions
                                                                                                            • Appendix

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