E-Book, Englisch, Band 411, 419 Seiten, eBook
Chadli / Bououden / Zelinka Recent Advances in Electrical Engineering and Control Applications
1. Auflage 2017
ISBN: 978-3-319-48929-2
Verlag: Springer International Publishing
Format: PDF
Kopierschutz: 1 - PDF Watermark
E-Book, Englisch, Band 411, 419 Seiten, eBook
Reihe: Lecture Notes in Electrical Engineering
ISBN: 978-3-319-48929-2
Verlag: Springer International Publishing
Format: PDF
Kopierschutz: 1 - PDF Watermark
Zielgruppe
Research
Autoren/Hrsg.
Weitere Infos & Material
1;Foreword;6
2;Contents;8
3;Control and Systems Engineering (CSE);12
4;Power Quality Improvement Based on Five-Level NPC Series APF Using Fuzzy Control Scheme;13
4.1;Abstract;13
4.2;1 Introduction;13
4.3;2 Series APF Configuration System;14
4.4;3 Control Strategies;17
4.5;4 Fuzzy Logic Control;19
4.6;5 Simulation Results and Discussion;24
4.7;6 Conclusion;25
4.8;References;25
5;Adaptive Backstepping Control Using Combined Direct and Indirect \sigma –Modification Adaptation;27
5.1;Abstract;27
5.2;1 Introduction;27
5.3;2 Identification Based x-Swapping;28
5.4;3 Direct/Indirect Adaptive Backstepping Control with DSC;30
5.5;4 Stability Analysis;33
5.6;5 Numerical Example;35
5.7;6 Conclusion;39
5.8;References;39
6;Linear Stochastic Model Validation for Civil Engineering Structures Under Earthquakes;41
6.1;Abstract;41
6.2;1 Introduction;41
6.3;2 Dynamic Model of the Structure;42
6.4;3 Seismic Dynamic Model;44
6.5;4 ARMAX Model of the Structure;46
6.6;5 ARMA Model Identification;49
6.7;6 Simulation Results;51
6.8;7 Conclusions;53
6.9;References;54
7;Adaptive Fuzzy Control-Based Projective Synchronization Scheme of Uncertain Chaotic Systems with Input Nonlinearities;55
7.1;Abstract;55
7.2;1 Introduction;55
7.3;2 Problem Statements and Preliminaries;56
7.4;3 Design of Fuzzy Adaptive Controller;60
7.5;4 Simulation Results;65
7.6;5 Conclusion;67
7.7;References;68
8;A Novel State Representation of Electric Powered Wheelchair;70
8.1;Abstract;70
8.2;1 Introduction;70
8.3;2 Descripting and Modeling;71
8.4;3 Dynamic Modeling;72
8.5;4 New State Representation;75
8.6;5 Decoupling System;76
8.7;6 EPW Control System;77
8.8;7 Results and Discussion;77
8.9;8 Conclusion;79
8.10;References;79
9;Single and Multi Objective Predictive Control of Mobile Robots;80
9.1;Abstract;80
9.2;1 Introduction;80
9.3;2 Model Predictive Control;81
9.4;3 Solution of the Multi Objective Predictive Control Problem;82
9.5;4 Application;83
9.6;5 Conclusion;88
9.7;References;88
10;Comparison Between Predictive Sliding Mode Control and Sliding Mode Control with Predictive Sliding Function;90
10.1;Abstract;90
10.2;1 Introduction;90
10.3;2 System Description;92
10.4;3 Synthesis of Discrete Predictive Sliding Mode Controller;92
10.5;4 Synthesis of Discrete Sliding Mode Controller with Predictive Sliding Function;96
10.6;5 Comparison Between PSMC and SMC-PSF;101
10.7;6 Conclusion;105
10.8;Acknowledgment;105
10.9;References;105
11;Discrete Variable Structure Model Reference Adaptive Control for Non Strictly Positive Real Systems Using Only I/O Measurements;108
11.1;Abstract;108
11.2;1 Introduction;108
11.3;2 Basic Definitions;109
11.4;3 The Modified Discrete Model Reference Adaptive Control;110
11.5;4 The Discrete Variable Structure Model Reference Adaptive Control Using Only Input-Output Measurements;113
11.6;5 Simulation Example;114
11.6.1;5.1 Mrac;116
11.6.2;5.2 D-Vs-Mrac-Io;119
11.6.3;5.3 Comparison Between Discrete MRAC and D-VS-MRACIO;120
11.7;6 Conclusion;121
11.8;Acknowledgment;122
11.9;References;122
12;Stable Adaptive Fuzzy Sliding-Mode Controller for a Class of Underactuated Dynamic Systems;124
12.1;Abstract;124
12.2;1 Introduction;124
12.3;2 System Description and Problem Formulation;125
12.4;3 Control System Design and Stability Analysis;126
12.5;4 Simulation Study;130
12.6;5 Conclusion;133
12.7;References;133
13;Indirect Robust Adaptive Fuzzy Control of Uncertain Two Link Robot Manipulator;135
13.1;Abstract;135
13.2;1 Introduction;135
13.3;2 Problem Formulation;136
13.4;3 Description of Fuzzy Systems;138
13.5;4 Indirect Adaptive Fuzzy Control;138
13.6;5 Simulation Results;145
13.7;6 Conclusion;148
13.8;References;148
14;Constrained Fuzzy Predictive Control Design Based on the PDC Approach;150
14.1;Abstract;150
14.2;1 Introduction;150
14.3;2 Backgrounds;151
14.3.1;2.1 Model Predictive Control;151
14.3.2;2.2 Fuzzy Discrete Time T-S Model;151
14.3.3;2.3 PDC Fuzzy Control Law;152
14.4;3 Robust T-S Predictive Control Model Using PDC Controller;152
14.5;4 Simulation Results;157
14.5.1;4.1 Example 1;157
14.5.2;4.2 Example 2;158
14.6;5 Conclusion;163
14.7;References;164
15;Renewable Energy (RE);165
16;Control of Grid-Connected Photovoltaic System with Batteries Storage;166
16.1;Abstract;166
16.2;1 Introduction;166
16.3;2 Photovoltaic Model;167
16.4;3 Storage System;170
16.5;4 Topology of the System;171
16.6;5 Control Strategy;171
16.6.1;5.1 Boost Converter Control;172
16.6.2;5.2 Inverter Control;172
16.7;6 Simulation Results;174
16.8;7 Conclusion;178
16.9;References;178
17;The Development of Empirical Photovoltaic/Thermal Collector;180
17.1;Abstract;180
17.2;1 Introduction;180
17.3;2 Concept of Hybrid PVT Collector;181
17.3.1;2.1 Block Diagram of a PV/T System for the Production of Energy;181
17.3.2;2.2 Constitution of the Hybrid Collector;182
17.4;3 Thermal Analysis;182
17.4.1;3.1 Schematic of Heat Transfer;182
17.5;4 Results and Discussions;185
17.6;5 Experimental Study;186
17.7;6 Conclusion;188
17.8;References;188
18;A Mathematical Model to Determine the Shading Effects in the I-V Characteristic of a Photovoltaic Module;190
18.1;Abstract;190
18.2;1 Introduction;190
18.3;2 Model and Simulation Procedure;191
18.3.1;2.1 Model of Practical PV in First Quadrant;191
18.3.2;2.2 Modeling of Reverse Characteristics of PV Cell;193
18.4;3 Study of Partial Shadowing Effects in the Solar PV;195
18.5;4 Simulation Results;195
18.5.1;4.1 Influence of the Amount of Shading with Bypass Diode;196
18.6;5 Conclusion;197
18.7;References;198
19;Hybrid Systems Using Thermal/Biomass Sources;200
19.1;Abstract;200
19.2;1 Introduction;200
19.3;2 An Experimental Hybrid System;202
19.4;3 Energy Resources Estimation;202
19.4.1;3.1 Estimation of Annual Thermal Energy;202
19.4.2;3.2 Estimation of Annual Biogas Energy;203
19.5;4 Modeling the Hybrid System;204
19.5.1;4.1 Continuous Energy Case;204
19.5.2;4.2 Discrete Energy Case;204
19.6;5 Application;205
19.6.1;5.1 Continuous Energy Case;205
19.6.2;5.2 Discrete Energy Case;205
19.7;6 Results;205
19.8;7 Graphic;207
19.9;8 Conclusion;208
19.10;References;209
20;A Neural and Fuzzy Logic Based Control Scheme for a Shunt Active Power Filter;210
20.1;Abstract;210
20.2;1 Introduction;210
20.3;2 Proposed Control Strategy;212
20.4;3 Adaptive Linear Neural Networks Principle;212
20.5;4 ADALINE as Harmonic Estimator;213
20.6;5 Design of the DC-bus Fuzzy Logic Controller;214
20.7;6 Simulations and Analysis of the Results;216
20.8;7 Conclusion;219
20.9;References;219
21;Faults Diagnosis-Faults Tolerant Control (FTC);221
22;Robust Fault Detection Filter Design for Discrete-Time Fuzzy Models;222
22.1;Abstract;222
22.2;1 Introduction;222
22.3;2 Preliminaries on T-S Fuzzy Systems;223
22.4;3 Problem Statement;225
22.5;4 Robustness Conditions;226
22.6;5 Fault Sensitivity Conditions;229
22.7;6 Mixed {{{{\bf H}}_{ - } } \mathord{\left/ {\vphantom {{{{\bf H}}_{ - } } {{{\bf H}}_{\infty } }}} \right. \kern-0pt} {{{\bf H}}_{\infty } }} Fault Detection Observer Design;232
22.8;7 Simulation Example;232
22.9;8 Conclusion;237
22.10;Appendix A;238
22.11;References;239
23;Feature Selection for Enhancement of Bearing Fault Detection and Diagnosis Based on Self-Organizing Map;240
23.1;Abstract;240
23.2;1 Introduction;240
23.3;2 Theoretical Background;242
23.3.1;2.1 Feature Selection;242
23.3.2;2.2 ReliefF Feature Selection;242
23.3.3;2.3 Minimum Redundancy and Maximum Relevancy (MRMR);243
23.3.4;2.4 Self-Organizing Map (SOM);243
23.4;3 Proposed Fault Diagnosis System;245
23.4.1;3.1 Feature Extraction;245
23.5;4 Experimental Implementation;248
23.5.1;4.1 Experimental Data;248
23.5.2;4.2 Results and Discussion;249
23.6;5 Conclusion;251
23.7;References;251
24;Small Signal Fractional Order Modeling of PN Junction Diode;254
24.1;Abstract;254
24.2;1 Introduction;254
24.3;2 Diode AC Small Signal Impedance-Experimental Setup;255
24.3.1;2.1 Diode Elements;255
24.3.2;2.2 Integer Order Models;257
24.4;3 Fractional Order Models;258
24.5;4 Experimental Results;259
24.5.1;4.1 Analytical and Classical Models;259
24.5.2;4.2 Fractional Model with One Zero and One Pole;260
24.5.3;4.3 Fractional Model with One Zero and Two Poles;261
24.6;5 Conclusion;261
24.7;References;262
25;Fractional Order Systems (Sofa);263
26;Rational Function Approximation of a Fundamental Fractional Order Transfer Function;264
26.1;Abstract;264
26.2;1 Introduction;264
26.3;2 Rational Function Approximation;266
26.3.1;2.1 Case 1: 0 lessthan ? lessthan 0.5;266
26.3.2;2.2 Case 2: ? = 0.5;269
26.4;3 Time Responses;270
26.4.1;3.1 Case 1: 0 lessthan ? lessthan 0.5;270
26.4.2;3.2 Case 2: ? = 0.5;271
26.5;4 Illustrative Example;272
26.6;5 Conclusion;279
26.7;References;279
27;Robust Adaptive Fuzzy Control for a Class of Uncertain Nonlinear Fractional Systems;281
27.1;Abstract;281
27.2;1 Introduction;281
27.3;2 Basic Definitions and Preliminaries for Fractional Order Systems;282
27.4;3 Description of the T–S Fuzzy Systems;285
27.5;4 Adaptive H^{\infty } Control of Uncertain Fractional Order Systems;286
27.6;5 Simulation Results;292
27.7;6 Conclusion;297
27.8;References;297
28;Signal and Communications (SC);300
29;A Leaky Wave Antenna Based on SIW Technology for Ka Band Applications;301
29.1;Abstract;301
29.2;1 Introduction;301
29.3;2 Parameters of Substrate Integrated Waveguide;302
29.3.1;2.1 Feed Design;303
29.3.2;2.2 Microstrip Transition Lines in Substrate Integrated Waveguide;304
29.4;3 SIW Leaky-Wave Antenna Design;306
29.5;4 Conclusion;308
29.6;References;309
30;Selective Filters Design Based Two-Dimensional Photonic Crystals: Modeling Using the 2D-FDTD Method;310
30.1;Abstract;310
30.2;1 Introduction;310
30.3;2 Filtering in Two-Dimensional Photonic Crystals;311
30.4;3 Two Dimensional FDTD 2D;312
30.5;4 Selective Filter Design;315
30.5.1;4.1 First Filter Topology Based on Three Cascaded Waveguide in Triangular Lattices;315
30.5.2;4.2 Second Filter Topology Based on Three Cascaded Wave Guides in Square and Triangular Lattices;316
30.6;5 Conclusions;319
30.7;References;319
31;Writer’s Gender Classification Using HOG and LBP Features;321
31.1;Abstract;321
31.2;1 Introduction;321
31.3;2 Gender Classification System;322
31.3.1;2.1 Local Binary Patterns;322
31.3.2;2.2 Histogram of Oriented Gradients;324
31.3.3;2.3 Support Vector Machines;325
31.4;3 Experimental Results;325
31.4.1;3.1 Results Obtained for the First Training Set;326
31.4.2;3.2 Results Obtained for the Second Training Set;327
31.5;4 Conclusion and Future Work;328
31.6;References;328
32;Speech Recognition System Based on OLLO French Corpus by Using MFCCs;330
32.1;Abstract;330
32.2;1 Introduction;330
32.3;2 The Mel-Frequency Cepstrum Coefficient (MFCC);331
32.4;3 Coprus;331
32.5;4 Experimental Results and Analyse;333
32.6;5 Conclusion;335
32.7;References;335
33;Wavelets Based Image De-Noising: Application to EFTEM Imaging;336
33.1;Abstract;336
33.2;1 Introduction;336
33.3;2 Noise in EM Images;337
33.4;3 Concrete Steps of Wavelets De-Noising Algorithm in EM;338
33.4.1;3.1 Basic Assumption;338
33.4.2;3.2 Concrete Steps of De-noising EM Images;340
33.5;4 Results;340
33.5.1;4.1 Experimental Test Data;340
33.5.2;4.2 Performance Evaluation;340
33.5.3;4.3 Results of the De-Noising Algorithm;343
33.6;5 Concluding Remarques;344
33.7;References;346
34;New Front End Based on Multitaper and Gammatone Filters for Robust Speaker Verification;348
34.1;Abstract;348
34.2;1 Introduction;348
34.3;2 The Proposed Multitaper Gammatone Cepstral Coefficient MGCC;349
34.4;3 Gammatone Filter;350
34.5;4 Multitaper Spectrum Estimation;351
34.6;5 Experiment;352
34.6.1;5.1 Experimental Setup;352
34.6.2;5.2 Experimental Results Using GMM-UBM;353
34.6.3;5.3 Experimental Results Using I-Vector;356
34.7;6 Conclusion;357
34.8;References;357
35;Comparative Study of Time Frequency Analysis Application on Abnormal EEG Signals;359
35.1;Abstract;359
35.2;1 Introduction;359
35.3;2 Methods;360
35.3.1;2.1 Time-Frequency Analysis;360
35.3.2;2.2 Rényi Entropy;361
35.4;3 Materials and EEG Data;362
35.5;4 Experimental Results;363
35.5.1;4.1 Time-Frequency Analysis Using Rényi Entropy;363
35.5.2;4.2 Peak Seizure Characterisation;364
35.6;5 Conclusion;370
35.7;References;370
36;Performance Evaluation of Segmentation Algorithms Based on Level Set Method: Application to Medical Images;373
36.1;Abstract;373
36.2;1 Introduction;373
36.3;2 Level Set Method in Image Segmentation;374
36.3.1;2.1 Level Sets;374
36.3.2;2.2 Performance Evaluation;378
36.4;3 Experimental Results;380
36.5;4 Concluding Remarques;383
36.6;References;383
37;Design of Antipodal Linearly Tapered Slot Antennas (ALTSA) Arrays in SIW Technology for UWB Imaging;385
37.1;Abstract;385
37.2;1 Introduction;385
37.3;2 Single Antenna Element;386
37.4;3 SIW Bends Design;388
37.5;4 Design of SIW Power 2-Way Divider with ALTSA;388
37.6;5 Resultants and Simulation;390
37.7;6 Present Electromagnetic Fields in SIW Bends;391
37.8;7 Conclusion;392
37.9;References;392
38;Large Scale Systems (SI03);394
39;Optimized Sliding Mode Control of DC-DC Boost Converter for Photovoltaic System;395
39.1;Abstract;395
39.2;1 Introduction;395
39.3;2 System Configuration and Sliding Mode Control Strategy;396
39.3.1;2.1 Validity of the Control Methodology;398
39.4;3 Optimization of the Sliding Mode Control Strategy;402
39.4.1;3.1 Simplex Method to Delimitate Sliding Mode Controller Gains;402
39.4.2;3.2 PSO-Based Optimization of Sliding Mode Controller Gains;404
39.5;4 Simulation Results;405
39.6;5 Conclusion;407
39.7;References;408
40;Modeling of MOSFET Transistor by MLP Neural Networks;409
40.1;Abstract;409
40.2;1 Introduction;409
40.3;2 The Metal Oxide Semiconductor (MOS) Transistor;410
40.4;3 Artificial Neuron Networks ANN;411
40.4.1;3.1 Structure of ANN;411
40.4.2;3.2 Training of an ANN;412
40.5;4 Genetic Algorithms GA;412
40.6;5 Applying of Genetic Algorithms for Neural Network Training;413
40.7;6 Simulation Results;414
40.8;7 Conclusion;416
40.9;References;416
41;Author Index;418