Fuzzy logic control in energy systems : with design applications in MATLAB /Simulink

This book is about fuzzy logic control and its applications in managing, controlling and operating electrical energy systems. It provides a comprehensive overview of fuzzy logic concepts and techniques required for designing fuzzy logic controllers, and then discusses several applications to control...

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Bibliographic Details
Main Author: Altas, Ísmail H., (Author)
Format: eBook
Language: English
Published: London : The Institution of Engineering and Technology, 2017.
Series: IET energy engineering series ; 91.
Subjects:
MATLAB.
MATLAB
Electric power systems > Control.
Fuzzy logic.
Numerical analysis > Computer programs.
Fuzzy logic > Congresses.
elektronické knihy
electronic books
ISBN: 9781785611087
1785611089
9781523112876
1523112875
9781785611070
1785611070
Physical Description: 1 online resource : illustrations

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Table of contents

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040 |a EBLCP  |b eng  |e rda  |e pn  |c EBLCP  |d ITD  |d UIU  |d IDEBK  |d OCLCO  |d MERUC  |d OCLCF  |d STF  |d VLB  |d YDX  |d N$T  |d UAB  |d KNOVL  |d CSA  |d EZ9  |d COO  |d OCLCQ  |d OTZ  |d OCLCQ  |d WYU  |d BNG  |d G3B  |d IGB  |d ERL  |d AUW  |d BTN  |d INTCL  |d MHW  |d SNK  |d CUV  |d UKAHL  |d OCLCQ  |d OCL  |d OCLCQ  |d MM9  |d OCLCQ  |d OCLCO  |d OCLCQ  |d OCLCO  |d OCLCL  |d BRX 
020 |a 9781785611087  |q (electronic bk.) 
020 |a 1785611089  |q (electronic bk.) 
020 |a 9781523112876  |q (electronic bk.) 
020 |a 1523112875  |q (electronic bk.) 
020 |z 9781785611070  |q (hardcover) 
020 |z 1785611070  |q (hardcover) 
035 |a (OCoLC)1011250817  |z (OCoLC)1008984718  |z (OCoLC)1012866067  |z (OCoLC)1016970616  |z (OCoLC)1018070097  |z (OCoLC)1021067831  |z (OCoLC)1057434298  |z (OCoLC)1076527900  |z (OCoLC)1171436428  |z (OCoLC)1229062944 
100 1 |a Altas, Ísmail H.,  |e author. 
245 1 0 |a Fuzzy logic control in energy systems :  |b with design applications in MATLAB /Simulink /  |c İsmail H. Altaş. 
264 1 |a London :  |b The Institution of Engineering and Technology,  |c 2017. 
300 |a 1 online resource :  |b illustrations 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
490 1 |a IET energy engineering ;  |v 91 
504 |a Includes bibliographical references and index. 
505 0 |a Machine generated contents note: 1. Introduction -- 1.1. Introduction -- 1.2. Fuzziness -- 1.3. Fuzzy membership functions -- 1.4. Fuzzy sets -- References -- 2. Fuzzy sets -- 2.1. Introduction -- 2.2. Fuzzy sets and fuzzy membership functions -- 2.2.1. Triangular membership function -- 2.2.2. Trapezoid membership function -- 2.2.3. Gaussian membership function -- 2.2.4. Bell membership function -- 2.2.5. Cauchy membership function -- 2.2.6. Sinusoid membership function -- 2.2.7. Sigmoid membership function -- 2.3. Properties of fuzzy membership functions -- 2.4. Fuzzy set operations -- 2.4.1. Intersection: t-norm -- 2.4.2. Union: t-conorm -- 2.4.3.Complement -- 2.4.4. De Morgan laws -- 2.5. Adjustment of fuzziness -- 2.6. Problems -- References -- 3. Fuzzy partitioning -- 3.1. Introduction -- 3.2. Theoretical approaches -- 3.3. Fuzzy partition examples in energy systems -- 3.4. Problems -- References -- 4. Fuzzy relation -- 4.1. Introduction -- 4.2. Fuzzy relation -- 4.3. Operation with fuzzy relations 
505 0 |a Note continued: 4.3.1. Intersection of two fuzzy relations -- 4.3.2. Union of two fuzzy relations -- 4.3.3. Negation of a fuzzy relation -- 4.3.4. Inverse of a fuzzy relation -- 4.3.5.Composition of fuzzy relations -- 4.3.6.Compositional rule of inference -- 4.3.7. The relational joint -- 4.4. Binary relations -- 4.5. The extension principle -- 4.5.1. The cylindrical extension -- 4.6. Fuzzy mapping -- 4.7. Problems -- References -- 5. Fuzzy reasoning and fuzzy decision-making -- 5.1. Introduction -- 5.2. Fuzzy implications -- 5.3. Approximate reasoning -- 5.4. Inference rules of approximate reasoning -- 5.4.1. Entailment rule of inference -- 5.4.2. Conjunction rule of inference -- 5.4.3. Disjunction rule of inference -- 5.4.4. Negation rule of inference -- 5.4.5. Projection rule of inference -- 5.4.6. Generalized modus ponens rule of inference -- 5.4.7.Compositional rule of inference -- 5.5. Fuzzy reasoning -- 5.5.1. Inference engine with single input single rule 
505 0 |a Note continued: 5.5.2. Inference engine with multiple input single rule -- 5.5.3. Inference engine with multiple input multiple rule -- 5.6. Problems -- References -- 6. Fuzzy processor -- 6.1. Introduction -- 6.2. Mamdani fuzzy reasoning -- 6.2.1. Fuzzification -- 6.2.2. Fuzzy rule base -- 6.2.3. Fuzzy conclusion -- 6.2.4. Defuzzification -- 6.3. Takagi-Sugeno fuzzy reasoning -- 6.4. Tsukamoto fuzzy reasoning -- 6.5. Problems -- References -- 7. Fuzzy logic controller -- 7.1. Introduction -- 7.2. Physical system behaviors and control -- 7.3. Fuzzy processor for control -- 7.3.1. Fuzzy rules: the modeling of thoughts -- 7.3.2. The input -- output interaction -- 7.4. Modeling the FLC in MATLAB -- 7.5. Modeling the FLC in Simulink -- 7.6. Problems -- References -- 8. System modeling and control -- 8.1. Introduction -- 8.2. System modeling -- 8.3. Modeling electrical systems -- 8.4. Modeling mechanical systems -- 8.4.1. Mechanical systems with linear motion 
505 0 |a Note continued: 8.4.2. Mechanical systems with rotational motion -- 8.5. Modeling electromechanical systems -- 8.5.1. Field subsystem -- 8.5.2. Armature subsystem -- 8.5.3. Mechanical subsystem -- 8.5.4. Electromechanic interaction subsystem -- 8.5.5. Modeling DC motors -- 8.5.6. Modeling AC motors -- 8.6. Problems -- References -- 9. FLC in power systems -- 9.1. Introduction -- 9.2. Excitation control -- 9.2.1. Excitation system modeling -- 9.2.2. State-space model of excitation systems -- 9.2.3. FLC of excitation systems -- 9.3. LF control -- 9.3.1. Small signal modeling of power systems -- 9.3.2. FLC design for LFC -- 9.4. FLC in power compensation -- 9.4.1. Power factor improvement -- 9.4.2. Bus voltage control -- 9.5. Problems -- References -- 10. FLC in wind energy systems -- 10.1. Introduction -- 10.2. Wind turbine -- 10.3. Electrical generator -- 10.3.1. Dynamic modeling of induction generator -- 10.3.2. Self-excited induction generator -- 10.4. FLC examples in WEC systems 
505 0 |a Note continued: 10.5. Problems -- References -- 11. FLC in PV solar energy systems -- 11.1. Introduction -- 11.2. PV cell modelings -- 11.2.1. Reference I -- V characteristics of a PV panel -- 11.2.2. Effects of changes in solar irradiation and temperature -- 11.2.3. PV panel modeling in Simulink -- 11.2.4.A PV array emulator -- 11.3. MPP search in PV arrays -- 11.3.1. MPP by lookup tables -- 11.3.2. MPP search algorithm based on measurements of SX and TX -- 11.3.3. MPP search algorithm based on voltage and current measurements -- 11.3.4. MPP search algorithm based on online repetitive method -- 11.4. MPPT of PV arrays -- 11.4.1. Constant maximum power angle approach -- 11.4.2. Online load matching approach -- 11.5. Problems -- References -- 12. Energy management and fuzzy decision-making -- 12.1. Introduction -- 12.2. Distributed generation and control -- 12.3. Energy management in a renewable integration system -- 12.3.1. Centralized control of distributed renewable energy systems 
505 0 |a Note continued: 12.3.2. Distributed control of renewable energy systems -- 12.4. Problems -- References. 
506 |a Plný text je dostupný pouze z IP adres počítačů Univerzity Tomáše Bati ve Zlíně nebo vzdáleným přístupem pro zaměstnance a studenty 
520 |a This book is about fuzzy logic control and its applications in managing, controlling and operating electrical energy systems. It provides a comprehensive overview of fuzzy logic concepts and techniques required for designing fuzzy logic controllers, and then discusses several applications to control and management in energy systems. 
590 |a Knovel  |b Knovel (All titles) 
630 0 0 |a MATLAB. 
630 0 7 |a MATLAB  |2 fast 
650 0 |a Electric power systems  |x Control. 
650 0 |a Fuzzy logic. 
650 0 |a Numerical analysis  |x Computer programs. 
650 0 |a Fuzzy logic  |v Congresses. 
655 7 |a elektronické knihy  |7 fd186907  |2 czenas 
655 9 |a electronic books  |2 eczenas 
776 0 8 |i Print version:  |a Altaş, İsmail H.  |t Fuzzy logic control in energy systems.  |d London : The Institution of Engineering and Technology, 2017  |z 9781785611070  |w (OCoLC)1014434727 
830 0 |a IET energy engineering series ;  |v 91. 
856 4 0 |u https://proxy.k.utb.cz/login?url=https://app.knovel.com/hotlink/toc/id:kpFLCESWM1/fuzzy-logic-control?kpromoter=marc  |y Full text 

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