Recent Advances in Electrical Engineering and Control Applications
1st Edition
Published on 1. December 2016
X, 418 pages
978-3-319-48929-2 (ISBN)
Description
This book of proceedings includes papers presenting the state of art in electrical engineering and control theory as well as their applications. The topics focus on classical as well as modern methods for modeling, control, identification and simulation of complex systems with applications in science and engineering. The papers were selected from the hottest topic areas, such as control and systems engineering, renewable energy, faults diagnosis-faults tolerant control, large-scale systems, fractional order systems, unconventional algorithms in control engineering, signals and communications.
The control and design of complex systems dynamics, analysis and modeling of its behavior and structure is vitally important in engineering, economics and in science generally science today. Examples of such systems can be seen in the world around us and are a part of our everyday life. Application of modern methods for control, electronics, signal processing and more can be found in our mobile phones, car engines, home devices like washing machines is as well as in such advanced devices as space probes and systems for communicating with them. All these technologies are part of technological backbone of our civilization, making further research and hi-tech applications essential.
The rich variety of contributions appeals to a wide audience, including researchers, students and academics.
More details
Series
Language
English
Place of publication
Cham
Switzerland
Publishing group
Springer International Publishing
Target group
Professional and scholarly
Product notice
Reflowable
Illustrations
X, 418 p. 245 illus.
File size
43,88 MB
ISBN-13
978-3-319-48929-2 (9783319489292)
DOI
10.1007/978-3-319-48929-2
Schweitzer Classification
Other editions
Additional editions
Mohammed Chadli | Sofiane Bououden | Ivan Zelinka
Recent Advances in Electrical Engineering and Control Applications
Book
12/2016
Springer
€213.99
Shipment within 10-15 days
Content
1 - Foreword [Seite 6]
2 - Contents [Seite 8]
3 - Control and Systems Engineering (CSE) [Seite 12]
4 - Power Quality Improvement Based on Five-Level NPC Series APF Using Fuzzy Control Scheme [Seite 13]
4.1 - Abstract [Seite 13]
4.2 - 1 Introduction [Seite 13]
4.3 - 2 Series APF Configuration System [Seite 14]
4.4 - 3 Control Strategies [Seite 17]
4.5 - 4 Fuzzy Logic Control [Seite 19]
4.6 - 5 Simulation Results and Discussion [Seite 24]
4.7 - 6 Conclusion [Seite 25]
4.8 - References [Seite 25]
5 - Adaptive Backstepping Control Using Combined Direct and Indirect \sigma -Modification Adaptation [Seite 27]
5.1 - Abstract [Seite 27]
5.2 - 1 Introduction [Seite 27]
5.3 - 2 Identification Based x-Swapping [Seite 28]
5.4 - 3 Direct/Indirect Adaptive Backstepping Control with DSC [Seite 30]
5.5 - 4 Stability Analysis [Seite 33]
5.6 - 5 Numerical Example [Seite 35]
5.7 - 6 Conclusion [Seite 39]
5.8 - References [Seite 39]
6 - Linear Stochastic Model Validation for Civil Engineering Structures Under Earthquakes [Seite 41]
6.1 - Abstract [Seite 41]
6.2 - 1 Introduction [Seite 41]
6.3 - 2 Dynamic Model of the Structure [Seite 42]
6.4 - 3 Seismic Dynamic Model [Seite 44]
6.5 - 4 ARMAX Model of the Structure [Seite 46]
6.6 - 5 ARMA Model Identification [Seite 49]
6.7 - 6 Simulation Results [Seite 51]
6.8 - 7 Conclusions [Seite 53]
6.9 - References [Seite 54]
7 - Adaptive Fuzzy Control-Based Projective Synchronization Scheme of Uncertain Chaotic Systems with Input Nonlinearities [Seite 55]
7.1 - Abstract [Seite 55]
7.2 - 1 Introduction [Seite 55]
7.3 - 2 Problem Statements and Preliminaries [Seite 56]
7.4 - 3 Design of Fuzzy Adaptive Controller [Seite 60]
7.5 - 4 Simulation Results [Seite 65]
7.6 - 5 Conclusion [Seite 67]
7.7 - References [Seite 68]
8 - A Novel State Representation of Electric Powered Wheelchair [Seite 70]
8.1 - Abstract [Seite 70]
8.2 - 1 Introduction [Seite 70]
8.3 - 2 Descripting and Modeling [Seite 71]
8.4 - 3 Dynamic Modeling [Seite 72]
8.5 - 4 New State Representation [Seite 75]
8.6 - 5 Decoupling System [Seite 76]
8.7 - 6 EPW Control System [Seite 77]
8.8 - 7 Results and Discussion [Seite 77]
8.9 - 8 Conclusion [Seite 79]
8.10 - References [Seite 79]
9 - Single and Multi Objective Predictive Control of Mobile Robots [Seite 80]
9.1 - Abstract [Seite 80]
9.2 - 1 Introduction [Seite 80]
9.3 - 2 Model Predictive Control [Seite 81]
9.4 - 3 Solution of the Multi Objective Predictive Control Problem [Seite 82]
9.5 - 4 Application [Seite 83]
9.6 - 5 Conclusion [Seite 88]
9.7 - References [Seite 88]
10 - Comparison Between Predictive Sliding Mode Control and Sliding Mode Control with Predictive Sliding Function [Seite 90]
10.1 - Abstract [Seite 90]
10.2 - 1 Introduction [Seite 90]
10.3 - 2 System Description [Seite 92]
10.4 - 3 Synthesis of Discrete Predictive Sliding Mode Controller [Seite 92]
10.5 - 4 Synthesis of Discrete Sliding Mode Controller with Predictive Sliding Function [Seite 96]
10.6 - 5 Comparison Between PSMC and SMC-PSF [Seite 101]
10.7 - 6 Conclusion [Seite 105]
10.8 - Acknowledgment [Seite 105]
10.9 - References [Seite 105]
11 - Discrete Variable Structure Model Reference Adaptive Control for Non Strictly Positive Real Systems Using Only I/O Measurements [Seite 108]
11.1 - Abstract [Seite 108]
11.2 - 1 Introduction [Seite 108]
11.3 - 2 Basic Definitions [Seite 109]
11.4 - 3 The Modified Discrete Model Reference Adaptive Control [Seite 110]
11.5 - 4 The Discrete Variable Structure Model Reference Adaptive Control Using Only Input-Output Measurements [Seite 113]
11.6 - 5 Simulation Example [Seite 114]
11.6.1 - 5.1 Mrac [Seite 116]
11.6.2 - 5.2 D-Vs-Mrac-Io [Seite 119]
11.6.3 - 5.3 Comparison Between Discrete MRAC and D-VS-MRACIO [Seite 120]
11.7 - 6 Conclusion [Seite 121]
11.8 - Acknowledgment [Seite 122]
11.9 - References [Seite 122]
12 - Stable Adaptive Fuzzy Sliding-Mode Controller for a Class of Underactuated Dynamic Systems [Seite 124]
12.1 - Abstract [Seite 124]
12.2 - 1 Introduction [Seite 124]
12.3 - 2 System Description and Problem Formulation [Seite 125]
12.4 - 3 Control System Design and Stability Analysis [Seite 126]
12.5 - 4 Simulation Study [Seite 130]
12.6 - 5 Conclusion [Seite 133]
12.7 - References [Seite 133]
13 - Indirect Robust Adaptive Fuzzy Control of Uncertain Two Link Robot Manipulator [Seite 135]
13.1 - Abstract [Seite 135]
13.2 - 1 Introduction [Seite 135]
13.3 - 2 Problem Formulation [Seite 136]
13.4 - 3 Description of Fuzzy Systems [Seite 138]
13.5 - 4 Indirect Adaptive Fuzzy Control [Seite 138]
13.6 - 5 Simulation Results [Seite 145]
13.7 - 6 Conclusion [Seite 148]
13.8 - References [Seite 148]
14 - Constrained Fuzzy Predictive Control Design Based on the PDC Approach [Seite 150]
14.1 - Abstract [Seite 150]
14.2 - 1 Introduction [Seite 150]
14.3 - 2 Backgrounds [Seite 151]
14.3.1 - 2.1 Model Predictive Control [Seite 151]
14.3.2 - 2.2 Fuzzy Discrete Time T-S Model [Seite 151]
14.3.3 - 2.3 PDC Fuzzy Control Law [Seite 152]
14.4 - 3 Robust T-S Predictive Control Model Using PDC Controller [Seite 152]
14.5 - 4 Simulation Results [Seite 157]
14.5.1 - 4.1 Example 1 [Seite 157]
14.5.2 - 4.2 Example 2 [Seite 158]
14.6 - 5 Conclusion [Seite 163]
14.7 - References [Seite 164]
15 - Renewable Energy (RE) [Seite 165]
16 - Control of Grid-Connected Photovoltaic System with Batteries Storage [Seite 166]
16.1 - Abstract [Seite 166]
16.2 - 1 Introduction [Seite 166]
16.3 - 2 Photovoltaic Model [Seite 167]
16.4 - 3 Storage System [Seite 170]
16.5 - 4 Topology of the System [Seite 171]
16.6 - 5 Control Strategy [Seite 171]
16.6.1 - 5.1 Boost Converter Control [Seite 172]
16.6.2 - 5.2 Inverter Control [Seite 172]
16.7 - 6 Simulation Results [Seite 174]
16.8 - 7 Conclusion [Seite 178]
16.9 - References [Seite 178]
17 - The Development of Empirical Photovoltaic/Thermal Collector [Seite 180]
17.1 - Abstract [Seite 180]
17.2 - 1 Introduction [Seite 180]
17.3 - 2 Concept of Hybrid PVT Collector [Seite 181]
17.3.1 - 2.1 Block Diagram of a PV/T System for the Production of Energy [Seite 181]
17.3.2 - 2.2 Constitution of the Hybrid Collector [Seite 182]
17.4 - 3 Thermal Analysis [Seite 182]
17.4.1 - 3.1 Schematic of Heat Transfer [Seite 182]
17.5 - 4 Results and Discussions [Seite 185]
17.6 - 5 Experimental Study [Seite 186]
17.7 - 6 Conclusion [Seite 188]
17.8 - References [Seite 188]
18 - A Mathematical Model to Determine the Shading Effects in the I-V Characteristic of a Photovoltaic Module [Seite 190]
18.1 - Abstract [Seite 190]
18.2 - 1 Introduction [Seite 190]
18.3 - 2 Model and Simulation Procedure [Seite 191]
18.3.1 - 2.1 Model of Practical PV in First Quadrant [Seite 191]
18.3.2 - 2.2 Modeling of Reverse Characteristics of PV Cell [Seite 193]
18.4 - 3 Study of Partial Shadowing Effects in the Solar PV [Seite 195]
18.5 - 4 Simulation Results [Seite 195]
18.5.1 - 4.1 Influence of the Amount of Shading with Bypass Diode [Seite 196]
18.6 - 5 Conclusion [Seite 197]
18.7 - References [Seite 198]
19 - Hybrid Systems Using Thermal/Biomass Sources [Seite 200]
19.1 - Abstract [Seite 200]
19.2 - 1 Introduction [Seite 200]
19.3 - 2 An Experimental Hybrid System [Seite 202]
19.4 - 3 Energy Resources Estimation [Seite 202]
19.4.1 - 3.1 Estimation of Annual Thermal Energy [Seite 202]
19.4.2 - 3.2 Estimation of Annual Biogas Energy [Seite 203]
19.5 - 4 Modeling the Hybrid System [Seite 204]
19.5.1 - 4.1 Continuous Energy Case [Seite 204]
19.5.2 - 4.2 Discrete Energy Case [Seite 204]
19.6 - 5 Application [Seite 205]
19.6.1 - 5.1 Continuous Energy Case [Seite 205]
19.6.2 - 5.2 Discrete Energy Case [Seite 205]
19.7 - 6 Results [Seite 205]
19.8 - 7 Graphic [Seite 207]
19.9 - 8 Conclusion [Seite 208]
19.10 - References [Seite 209]
20 - A Neural and Fuzzy Logic Based Control Scheme for a Shunt Active Power Filter [Seite 210]
20.1 - Abstract [Seite 210]
20.2 - 1 Introduction [Seite 210]
20.3 - 2 Proposed Control Strategy [Seite 212]
20.4 - 3 Adaptive Linear Neural Networks Principle [Seite 212]
20.5 - 4 ADALINE as Harmonic Estimator [Seite 213]
20.6 - 5 Design of the DC-bus Fuzzy Logic Controller [Seite 214]
20.7 - 6 Simulations and Analysis of the Results [Seite 216]
20.8 - 7 Conclusion [Seite 219]
20.9 - References [Seite 219]
21 - Faults Diagnosis-Faults Tolerant Control (FTC) [Seite 221]
22 - Robust Fault Detection Filter Design for Discrete-Time Fuzzy Models [Seite 222]
22.1 - Abstract [Seite 222]
22.2 - 1 Introduction [Seite 222]
22.3 - 2 Preliminaries on T-S Fuzzy Systems [Seite 223]
22.4 - 3 Problem Statement [Seite 225]
22.5 - 4 Robustness Conditions [Seite 226]
22.6 - 5 Fault Sensitivity Conditions [Seite 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 [Seite 232]
22.8 - 7 Simulation Example [Seite 232]
22.9 - 8 Conclusion [Seite 237]
22.10 - Appendix A [Seite 238]
22.11 - References [Seite 239]
23 - Feature Selection for Enhancement of Bearing Fault Detection and Diagnosis Based on Self-Organizing Map [Seite 240]
23.1 - Abstract [Seite 240]
23.2 - 1 Introduction [Seite 240]
23.3 - 2 Theoretical Background [Seite 242]
23.3.1 - 2.1 Feature Selection [Seite 242]
23.3.2 - 2.2 ReliefF Feature Selection [Seite 242]
23.3.3 - 2.3 Minimum Redundancy and Maximum Relevancy (MRMR) [Seite 243]
23.3.4 - 2.4 Self-Organizing Map (SOM) [Seite 243]
23.4 - 3 Proposed Fault Diagnosis System [Seite 245]
23.4.1 - 3.1 Feature Extraction [Seite 245]
23.5 - 4 Experimental Implementation [Seite 248]
23.5.1 - 4.1 Experimental Data [Seite 248]
23.5.2 - 4.2 Results and Discussion [Seite 249]
23.6 - 5 Conclusion [Seite 251]
23.7 - References [Seite 251]
24 - Small Signal Fractional Order Modeling of PN Junction Diode [Seite 254]
24.1 - Abstract [Seite 254]
24.2 - 1 Introduction [Seite 254]
24.3 - 2 Diode AC Small Signal Impedance-Experimental Setup [Seite 255]
24.3.1 - 2.1 Diode Elements [Seite 255]
24.3.2 - 2.2 Integer Order Models [Seite 257]
24.4 - 3 Fractional Order Models [Seite 258]
24.5 - 4 Experimental Results [Seite 259]
24.5.1 - 4.1 Analytical and Classical Models [Seite 259]
24.5.2 - 4.2 Fractional Model with One Zero and One Pole [Seite 260]
24.5.3 - 4.3 Fractional Model with One Zero and Two Poles [Seite 261]
24.6 - 5 Conclusion [Seite 261]
24.7 - References [Seite 262]
25 - Fractional Order Systems (Sofa) [Seite 263]
26 - Rational Function Approximation of a Fundamental Fractional Order Transfer Function [Seite 264]
26.1 - Abstract [Seite 264]
26.2 - 1 Introduction [Seite 264]
26.3 - 2 Rational Function Approximation [Seite 266]
26.3.1 - 2.1 Case 1: 0 lessthan ? lessthan 0.5 [Seite 266]
26.3.2 - 2.2 Case 2: ? = 0.5 [Seite 269]
26.4 - 3 Time Responses [Seite 270]
26.4.1 - 3.1 Case 1: 0 lessthan ? lessthan 0.5 [Seite 270]
26.4.2 - 3.2 Case 2: ? = 0.5 [Seite 271]
26.5 - 4 Illustrative Example [Seite 272]
26.6 - 5 Conclusion [Seite 279]
26.7 - References [Seite 279]
27 - Robust Adaptive Fuzzy Control for a Class of Uncertain Nonlinear Fractional Systems [Seite 281]
27.1 - Abstract [Seite 281]
27.2 - 1 Introduction [Seite 281]
27.3 - 2 Basic Definitions and Preliminaries for Fractional Order Systems [Seite 282]
27.4 - 3 Description of the T-S Fuzzy Systems [Seite 285]
27.5 - 4 Adaptive H^{\infty } Control of Uncertain Fractional Order Systems [Seite 286]
27.6 - 5 Simulation Results [Seite 292]
27.7 - 6 Conclusion [Seite 297]
27.8 - References [Seite 297]
28 - Signal and Communications (SC) [Seite 300]
29 - A Leaky Wave Antenna Based on SIW Technology for Ka Band Applications [Seite 301]
29.1 - Abstract [Seite 301]
29.2 - 1 Introduction [Seite 301]
29.3 - 2 Parameters of Substrate Integrated Waveguide [Seite 302]
29.3.1 - 2.1 Feed Design [Seite 303]
29.3.2 - 2.2 Microstrip Transition Lines in Substrate Integrated Waveguide [Seite 304]
29.4 - 3 SIW Leaky-Wave Antenna Design [Seite 306]
29.5 - 4 Conclusion [Seite 308]
29.6 - References [Seite 309]
30 - Selective Filters Design Based Two-Dimensional Photonic Crystals: Modeling Using the 2D-FDTD Method [Seite 310]
30.1 - Abstract [Seite 310]
30.2 - 1 Introduction [Seite 310]
30.3 - 2 Filtering in Two-Dimensional Photonic Crystals [Seite 311]
30.4 - 3 Two Dimensional FDTD 2D [Seite 312]
30.5 - 4 Selective Filter Design [Seite 315]
30.5.1 - 4.1 First Filter Topology Based on Three Cascaded Waveguide in Triangular Lattices [Seite 315]
30.5.2 - 4.2 Second Filter Topology Based on Three Cascaded Wave Guides in Square and Triangular Lattices [Seite 316]
30.6 - 5 Conclusions [Seite 319]
30.7 - References [Seite 319]
31 - Writer's Gender Classification Using HOG and LBP Features [Seite 321]
31.1 - Abstract [Seite 321]
31.2 - 1 Introduction [Seite 321]
31.3 - 2 Gender Classification System [Seite 322]
31.3.1 - 2.1 Local Binary Patterns [Seite 322]
31.3.2 - 2.2 Histogram of Oriented Gradients [Seite 324]
31.3.3 - 2.3 Support Vector Machines [Seite 325]
31.4 - 3 Experimental Results [Seite 325]
31.4.1 - 3.1 Results Obtained for the First Training Set [Seite 326]
31.4.2 - 3.2 Results Obtained for the Second Training Set [Seite 327]
31.5 - 4 Conclusion and Future Work [Seite 328]
31.6 - References [Seite 328]
32 - Speech Recognition System Based on OLLO French Corpus by Using MFCCs [Seite 330]
32.1 - Abstract [Seite 330]
32.2 - 1 Introduction [Seite 330]
32.3 - 2 The Mel-Frequency Cepstrum Coefficient (MFCC) [Seite 331]
32.4 - 3 Coprus [Seite 331]
32.5 - 4 Experimental Results and Analyse [Seite 333]
32.6 - 5 Conclusion [Seite 335]
32.7 - References [Seite 335]
33 - Wavelets Based Image De-Noising: Application to EFTEM Imaging [Seite 336]
33.1 - Abstract [Seite 336]
33.2 - 1 Introduction [Seite 336]
33.3 - 2 Noise in EM Images [Seite 337]
33.4 - 3 Concrete Steps of Wavelets De-Noising Algorithm in EM [Seite 338]
33.4.1 - 3.1 Basic Assumption [Seite 338]
33.4.2 - 3.2 Concrete Steps of De-noising EM Images [Seite 340]
33.5 - 4 Results [Seite 340]
33.5.1 - 4.1 Experimental Test Data [Seite 340]
33.5.2 - 4.2 Performance Evaluation [Seite 340]
33.5.3 - 4.3 Results of the De-Noising Algorithm [Seite 343]
33.6 - 5 Concluding Remarques [Seite 344]
33.7 - References [Seite 346]
34 - New Front End Based on Multitaper and Gammatone Filters for Robust Speaker Verification [Seite 348]
34.1 - Abstract [Seite 348]
34.2 - 1 Introduction [Seite 348]
34.3 - 2 The Proposed Multitaper Gammatone Cepstral Coefficient MGCC [Seite 349]
34.4 - 3 Gammatone Filter [Seite 350]
34.5 - 4 Multitaper Spectrum Estimation [Seite 351]
34.6 - 5 Experiment [Seite 352]
34.6.1 - 5.1 Experimental Setup [Seite 352]
34.6.2 - 5.2 Experimental Results Using GMM-UBM [Seite 353]
34.6.3 - 5.3 Experimental Results Using I-Vector [Seite 356]
34.7 - 6 Conclusion [Seite 357]
34.8 - References [Seite 357]
35 - Comparative Study of Time Frequency Analysis Application on Abnormal EEG Signals [Seite 359]
35.1 - Abstract [Seite 359]
35.2 - 1 Introduction [Seite 359]
35.3 - 2 Methods [Seite 360]
35.3.1 - 2.1 Time-Frequency Analysis [Seite 360]
35.3.2 - 2.2 Rényi Entropy [Seite 361]
35.4 - 3 Materials and EEG Data [Seite 362]
35.5 - 4 Experimental Results [Seite 363]
35.5.1 - 4.1 Time-Frequency Analysis Using Rényi Entropy [Seite 363]
35.5.2 - 4.2 Peak Seizure Characterisation [Seite 364]
35.6 - 5 Conclusion [Seite 370]
35.7 - References [Seite 370]
36 - Performance Evaluation of Segmentation Algorithms Based on Level Set Method: Application to Medical Images [Seite 373]
36.1 - Abstract [Seite 373]
36.2 - 1 Introduction [Seite 373]
36.3 - 2 Level Set Method in Image Segmentation [Seite 374]
36.3.1 - 2.1 Level Sets [Seite 374]
36.3.2 - 2.2 Performance Evaluation [Seite 378]
36.4 - 3 Experimental Results [Seite 380]
36.5 - 4 Concluding Remarques [Seite 383]
36.6 - References [Seite 383]
37 - Design of Antipodal Linearly Tapered Slot Antennas (ALTSA) Arrays in SIW Technology for UWB Imaging [Seite 385]
37.1 - Abstract [Seite 385]
37.2 - 1 Introduction [Seite 385]
37.3 - 2 Single Antenna Element [Seite 386]
37.4 - 3 SIW Bends Design [Seite 388]
37.5 - 4 Design of SIW Power 2-Way Divider with ALTSA [Seite 388]
37.6 - 5 Resultants and Simulation [Seite 390]
37.7 - 6 Present Electromagnetic Fields in SIW Bends [Seite 391]
37.8 - 7 Conclusion [Seite 392]
37.9 - References [Seite 392]
38 - Large Scale Systems (SI03) [Seite 394]
39 - Optimized Sliding Mode Control of DC-DC Boost Converter for Photovoltaic System [Seite 395]
39.1 - Abstract [Seite 395]
39.2 - 1 Introduction [Seite 395]
39.3 - 2 System Configuration and Sliding Mode Control Strategy [Seite 396]
39.3.1 - 2.1 Validity of the Control Methodology [Seite 398]
39.4 - 3 Optimization of the Sliding Mode Control Strategy [Seite 402]
39.4.1 - 3.1 Simplex Method to Delimitate Sliding Mode Controller Gains [Seite 402]
39.4.2 - 3.2 PSO-Based Optimization of Sliding Mode Controller Gains [Seite 404]
39.5 - 4 Simulation Results [Seite 405]
39.6 - 5 Conclusion [Seite 407]
39.7 - References [Seite 408]
40 - Modeling of MOSFET Transistor by MLP Neural Networks [Seite 409]
40.1 - Abstract [Seite 409]
40.2 - 1 Introduction [Seite 409]
40.3 - 2 The Metal Oxide Semiconductor (MOS) Transistor [Seite 410]
40.4 - 3 Artificial Neuron Networks ANN [Seite 411]
40.4.1 - 3.1 Structure of ANN [Seite 411]
40.4.2 - 3.2 Training of an ANN [Seite 412]
40.5 - 4 Genetic Algorithms GA [Seite 412]
40.6 - 5 Applying of Genetic Algorithms for Neural Network Training [Seite 413]
40.7 - 6 Simulation Results [Seite 414]
40.8 - 7 Conclusion [Seite 416]
40.9 - References [Seite 416]
41 - Author Index [Seite 418]
2 - Contents [Seite 8]
3 - Control and Systems Engineering (CSE) [Seite 12]
4 - Power Quality Improvement Based on Five-Level NPC Series APF Using Fuzzy Control Scheme [Seite 13]
4.1 - Abstract [Seite 13]
4.2 - 1 Introduction [Seite 13]
4.3 - 2 Series APF Configuration System [Seite 14]
4.4 - 3 Control Strategies [Seite 17]
4.5 - 4 Fuzzy Logic Control [Seite 19]
4.6 - 5 Simulation Results and Discussion [Seite 24]
4.7 - 6 Conclusion [Seite 25]
4.8 - References [Seite 25]
5 - Adaptive Backstepping Control Using Combined Direct and Indirect \sigma -Modification Adaptation [Seite 27]
5.1 - Abstract [Seite 27]
5.2 - 1 Introduction [Seite 27]
5.3 - 2 Identification Based x-Swapping [Seite 28]
5.4 - 3 Direct/Indirect Adaptive Backstepping Control with DSC [Seite 30]
5.5 - 4 Stability Analysis [Seite 33]
5.6 - 5 Numerical Example [Seite 35]
5.7 - 6 Conclusion [Seite 39]
5.8 - References [Seite 39]
6 - Linear Stochastic Model Validation for Civil Engineering Structures Under Earthquakes [Seite 41]
6.1 - Abstract [Seite 41]
6.2 - 1 Introduction [Seite 41]
6.3 - 2 Dynamic Model of the Structure [Seite 42]
6.4 - 3 Seismic Dynamic Model [Seite 44]
6.5 - 4 ARMAX Model of the Structure [Seite 46]
6.6 - 5 ARMA Model Identification [Seite 49]
6.7 - 6 Simulation Results [Seite 51]
6.8 - 7 Conclusions [Seite 53]
6.9 - References [Seite 54]
7 - Adaptive Fuzzy Control-Based Projective Synchronization Scheme of Uncertain Chaotic Systems with Input Nonlinearities [Seite 55]
7.1 - Abstract [Seite 55]
7.2 - 1 Introduction [Seite 55]
7.3 - 2 Problem Statements and Preliminaries [Seite 56]
7.4 - 3 Design of Fuzzy Adaptive Controller [Seite 60]
7.5 - 4 Simulation Results [Seite 65]
7.6 - 5 Conclusion [Seite 67]
7.7 - References [Seite 68]
8 - A Novel State Representation of Electric Powered Wheelchair [Seite 70]
8.1 - Abstract [Seite 70]
8.2 - 1 Introduction [Seite 70]
8.3 - 2 Descripting and Modeling [Seite 71]
8.4 - 3 Dynamic Modeling [Seite 72]
8.5 - 4 New State Representation [Seite 75]
8.6 - 5 Decoupling System [Seite 76]
8.7 - 6 EPW Control System [Seite 77]
8.8 - 7 Results and Discussion [Seite 77]
8.9 - 8 Conclusion [Seite 79]
8.10 - References [Seite 79]
9 - Single and Multi Objective Predictive Control of Mobile Robots [Seite 80]
9.1 - Abstract [Seite 80]
9.2 - 1 Introduction [Seite 80]
9.3 - 2 Model Predictive Control [Seite 81]
9.4 - 3 Solution of the Multi Objective Predictive Control Problem [Seite 82]
9.5 - 4 Application [Seite 83]
9.6 - 5 Conclusion [Seite 88]
9.7 - References [Seite 88]
10 - Comparison Between Predictive Sliding Mode Control and Sliding Mode Control with Predictive Sliding Function [Seite 90]
10.1 - Abstract [Seite 90]
10.2 - 1 Introduction [Seite 90]
10.3 - 2 System Description [Seite 92]
10.4 - 3 Synthesis of Discrete Predictive Sliding Mode Controller [Seite 92]
10.5 - 4 Synthesis of Discrete Sliding Mode Controller with Predictive Sliding Function [Seite 96]
10.6 - 5 Comparison Between PSMC and SMC-PSF [Seite 101]
10.7 - 6 Conclusion [Seite 105]
10.8 - Acknowledgment [Seite 105]
10.9 - References [Seite 105]
11 - Discrete Variable Structure Model Reference Adaptive Control for Non Strictly Positive Real Systems Using Only I/O Measurements [Seite 108]
11.1 - Abstract [Seite 108]
11.2 - 1 Introduction [Seite 108]
11.3 - 2 Basic Definitions [Seite 109]
11.4 - 3 The Modified Discrete Model Reference Adaptive Control [Seite 110]
11.5 - 4 The Discrete Variable Structure Model Reference Adaptive Control Using Only Input-Output Measurements [Seite 113]
11.6 - 5 Simulation Example [Seite 114]
11.6.1 - 5.1 Mrac [Seite 116]
11.6.2 - 5.2 D-Vs-Mrac-Io [Seite 119]
11.6.3 - 5.3 Comparison Between Discrete MRAC and D-VS-MRACIO [Seite 120]
11.7 - 6 Conclusion [Seite 121]
11.8 - Acknowledgment [Seite 122]
11.9 - References [Seite 122]
12 - Stable Adaptive Fuzzy Sliding-Mode Controller for a Class of Underactuated Dynamic Systems [Seite 124]
12.1 - Abstract [Seite 124]
12.2 - 1 Introduction [Seite 124]
12.3 - 2 System Description and Problem Formulation [Seite 125]
12.4 - 3 Control System Design and Stability Analysis [Seite 126]
12.5 - 4 Simulation Study [Seite 130]
12.6 - 5 Conclusion [Seite 133]
12.7 - References [Seite 133]
13 - Indirect Robust Adaptive Fuzzy Control of Uncertain Two Link Robot Manipulator [Seite 135]
13.1 - Abstract [Seite 135]
13.2 - 1 Introduction [Seite 135]
13.3 - 2 Problem Formulation [Seite 136]
13.4 - 3 Description of Fuzzy Systems [Seite 138]
13.5 - 4 Indirect Adaptive Fuzzy Control [Seite 138]
13.6 - 5 Simulation Results [Seite 145]
13.7 - 6 Conclusion [Seite 148]
13.8 - References [Seite 148]
14 - Constrained Fuzzy Predictive Control Design Based on the PDC Approach [Seite 150]
14.1 - Abstract [Seite 150]
14.2 - 1 Introduction [Seite 150]
14.3 - 2 Backgrounds [Seite 151]
14.3.1 - 2.1 Model Predictive Control [Seite 151]
14.3.2 - 2.2 Fuzzy Discrete Time T-S Model [Seite 151]
14.3.3 - 2.3 PDC Fuzzy Control Law [Seite 152]
14.4 - 3 Robust T-S Predictive Control Model Using PDC Controller [Seite 152]
14.5 - 4 Simulation Results [Seite 157]
14.5.1 - 4.1 Example 1 [Seite 157]
14.5.2 - 4.2 Example 2 [Seite 158]
14.6 - 5 Conclusion [Seite 163]
14.7 - References [Seite 164]
15 - Renewable Energy (RE) [Seite 165]
16 - Control of Grid-Connected Photovoltaic System with Batteries Storage [Seite 166]
16.1 - Abstract [Seite 166]
16.2 - 1 Introduction [Seite 166]
16.3 - 2 Photovoltaic Model [Seite 167]
16.4 - 3 Storage System [Seite 170]
16.5 - 4 Topology of the System [Seite 171]
16.6 - 5 Control Strategy [Seite 171]
16.6.1 - 5.1 Boost Converter Control [Seite 172]
16.6.2 - 5.2 Inverter Control [Seite 172]
16.7 - 6 Simulation Results [Seite 174]
16.8 - 7 Conclusion [Seite 178]
16.9 - References [Seite 178]
17 - The Development of Empirical Photovoltaic/Thermal Collector [Seite 180]
17.1 - Abstract [Seite 180]
17.2 - 1 Introduction [Seite 180]
17.3 - 2 Concept of Hybrid PVT Collector [Seite 181]
17.3.1 - 2.1 Block Diagram of a PV/T System for the Production of Energy [Seite 181]
17.3.2 - 2.2 Constitution of the Hybrid Collector [Seite 182]
17.4 - 3 Thermal Analysis [Seite 182]
17.4.1 - 3.1 Schematic of Heat Transfer [Seite 182]
17.5 - 4 Results and Discussions [Seite 185]
17.6 - 5 Experimental Study [Seite 186]
17.7 - 6 Conclusion [Seite 188]
17.8 - References [Seite 188]
18 - A Mathematical Model to Determine the Shading Effects in the I-V Characteristic of a Photovoltaic Module [Seite 190]
18.1 - Abstract [Seite 190]
18.2 - 1 Introduction [Seite 190]
18.3 - 2 Model and Simulation Procedure [Seite 191]
18.3.1 - 2.1 Model of Practical PV in First Quadrant [Seite 191]
18.3.2 - 2.2 Modeling of Reverse Characteristics of PV Cell [Seite 193]
18.4 - 3 Study of Partial Shadowing Effects in the Solar PV [Seite 195]
18.5 - 4 Simulation Results [Seite 195]
18.5.1 - 4.1 Influence of the Amount of Shading with Bypass Diode [Seite 196]
18.6 - 5 Conclusion [Seite 197]
18.7 - References [Seite 198]
19 - Hybrid Systems Using Thermal/Biomass Sources [Seite 200]
19.1 - Abstract [Seite 200]
19.2 - 1 Introduction [Seite 200]
19.3 - 2 An Experimental Hybrid System [Seite 202]
19.4 - 3 Energy Resources Estimation [Seite 202]
19.4.1 - 3.1 Estimation of Annual Thermal Energy [Seite 202]
19.4.2 - 3.2 Estimation of Annual Biogas Energy [Seite 203]
19.5 - 4 Modeling the Hybrid System [Seite 204]
19.5.1 - 4.1 Continuous Energy Case [Seite 204]
19.5.2 - 4.2 Discrete Energy Case [Seite 204]
19.6 - 5 Application [Seite 205]
19.6.1 - 5.1 Continuous Energy Case [Seite 205]
19.6.2 - 5.2 Discrete Energy Case [Seite 205]
19.7 - 6 Results [Seite 205]
19.8 - 7 Graphic [Seite 207]
19.9 - 8 Conclusion [Seite 208]
19.10 - References [Seite 209]
20 - A Neural and Fuzzy Logic Based Control Scheme for a Shunt Active Power Filter [Seite 210]
20.1 - Abstract [Seite 210]
20.2 - 1 Introduction [Seite 210]
20.3 - 2 Proposed Control Strategy [Seite 212]
20.4 - 3 Adaptive Linear Neural Networks Principle [Seite 212]
20.5 - 4 ADALINE as Harmonic Estimator [Seite 213]
20.6 - 5 Design of the DC-bus Fuzzy Logic Controller [Seite 214]
20.7 - 6 Simulations and Analysis of the Results [Seite 216]
20.8 - 7 Conclusion [Seite 219]
20.9 - References [Seite 219]
21 - Faults Diagnosis-Faults Tolerant Control (FTC) [Seite 221]
22 - Robust Fault Detection Filter Design for Discrete-Time Fuzzy Models [Seite 222]
22.1 - Abstract [Seite 222]
22.2 - 1 Introduction [Seite 222]
22.3 - 2 Preliminaries on T-S Fuzzy Systems [Seite 223]
22.4 - 3 Problem Statement [Seite 225]
22.5 - 4 Robustness Conditions [Seite 226]
22.6 - 5 Fault Sensitivity Conditions [Seite 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 [Seite 232]
22.8 - 7 Simulation Example [Seite 232]
22.9 - 8 Conclusion [Seite 237]
22.10 - Appendix A [Seite 238]
22.11 - References [Seite 239]
23 - Feature Selection for Enhancement of Bearing Fault Detection and Diagnosis Based on Self-Organizing Map [Seite 240]
23.1 - Abstract [Seite 240]
23.2 - 1 Introduction [Seite 240]
23.3 - 2 Theoretical Background [Seite 242]
23.3.1 - 2.1 Feature Selection [Seite 242]
23.3.2 - 2.2 ReliefF Feature Selection [Seite 242]
23.3.3 - 2.3 Minimum Redundancy and Maximum Relevancy (MRMR) [Seite 243]
23.3.4 - 2.4 Self-Organizing Map (SOM) [Seite 243]
23.4 - 3 Proposed Fault Diagnosis System [Seite 245]
23.4.1 - 3.1 Feature Extraction [Seite 245]
23.5 - 4 Experimental Implementation [Seite 248]
23.5.1 - 4.1 Experimental Data [Seite 248]
23.5.2 - 4.2 Results and Discussion [Seite 249]
23.6 - 5 Conclusion [Seite 251]
23.7 - References [Seite 251]
24 - Small Signal Fractional Order Modeling of PN Junction Diode [Seite 254]
24.1 - Abstract [Seite 254]
24.2 - 1 Introduction [Seite 254]
24.3 - 2 Diode AC Small Signal Impedance-Experimental Setup [Seite 255]
24.3.1 - 2.1 Diode Elements [Seite 255]
24.3.2 - 2.2 Integer Order Models [Seite 257]
24.4 - 3 Fractional Order Models [Seite 258]
24.5 - 4 Experimental Results [Seite 259]
24.5.1 - 4.1 Analytical and Classical Models [Seite 259]
24.5.2 - 4.2 Fractional Model with One Zero and One Pole [Seite 260]
24.5.3 - 4.3 Fractional Model with One Zero and Two Poles [Seite 261]
24.6 - 5 Conclusion [Seite 261]
24.7 - References [Seite 262]
25 - Fractional Order Systems (Sofa) [Seite 263]
26 - Rational Function Approximation of a Fundamental Fractional Order Transfer Function [Seite 264]
26.1 - Abstract [Seite 264]
26.2 - 1 Introduction [Seite 264]
26.3 - 2 Rational Function Approximation [Seite 266]
26.3.1 - 2.1 Case 1: 0 lessthan ? lessthan 0.5 [Seite 266]
26.3.2 - 2.2 Case 2: ? = 0.5 [Seite 269]
26.4 - 3 Time Responses [Seite 270]
26.4.1 - 3.1 Case 1: 0 lessthan ? lessthan 0.5 [Seite 270]
26.4.2 - 3.2 Case 2: ? = 0.5 [Seite 271]
26.5 - 4 Illustrative Example [Seite 272]
26.6 - 5 Conclusion [Seite 279]
26.7 - References [Seite 279]
27 - Robust Adaptive Fuzzy Control for a Class of Uncertain Nonlinear Fractional Systems [Seite 281]
27.1 - Abstract [Seite 281]
27.2 - 1 Introduction [Seite 281]
27.3 - 2 Basic Definitions and Preliminaries for Fractional Order Systems [Seite 282]
27.4 - 3 Description of the T-S Fuzzy Systems [Seite 285]
27.5 - 4 Adaptive H^{\infty } Control of Uncertain Fractional Order Systems [Seite 286]
27.6 - 5 Simulation Results [Seite 292]
27.7 - 6 Conclusion [Seite 297]
27.8 - References [Seite 297]
28 - Signal and Communications (SC) [Seite 300]
29 - A Leaky Wave Antenna Based on SIW Technology for Ka Band Applications [Seite 301]
29.1 - Abstract [Seite 301]
29.2 - 1 Introduction [Seite 301]
29.3 - 2 Parameters of Substrate Integrated Waveguide [Seite 302]
29.3.1 - 2.1 Feed Design [Seite 303]
29.3.2 - 2.2 Microstrip Transition Lines in Substrate Integrated Waveguide [Seite 304]
29.4 - 3 SIW Leaky-Wave Antenna Design [Seite 306]
29.5 - 4 Conclusion [Seite 308]
29.6 - References [Seite 309]
30 - Selective Filters Design Based Two-Dimensional Photonic Crystals: Modeling Using the 2D-FDTD Method [Seite 310]
30.1 - Abstract [Seite 310]
30.2 - 1 Introduction [Seite 310]
30.3 - 2 Filtering in Two-Dimensional Photonic Crystals [Seite 311]
30.4 - 3 Two Dimensional FDTD 2D [Seite 312]
30.5 - 4 Selective Filter Design [Seite 315]
30.5.1 - 4.1 First Filter Topology Based on Three Cascaded Waveguide in Triangular Lattices [Seite 315]
30.5.2 - 4.2 Second Filter Topology Based on Three Cascaded Wave Guides in Square and Triangular Lattices [Seite 316]
30.6 - 5 Conclusions [Seite 319]
30.7 - References [Seite 319]
31 - Writer's Gender Classification Using HOG and LBP Features [Seite 321]
31.1 - Abstract [Seite 321]
31.2 - 1 Introduction [Seite 321]
31.3 - 2 Gender Classification System [Seite 322]
31.3.1 - 2.1 Local Binary Patterns [Seite 322]
31.3.2 - 2.2 Histogram of Oriented Gradients [Seite 324]
31.3.3 - 2.3 Support Vector Machines [Seite 325]
31.4 - 3 Experimental Results [Seite 325]
31.4.1 - 3.1 Results Obtained for the First Training Set [Seite 326]
31.4.2 - 3.2 Results Obtained for the Second Training Set [Seite 327]
31.5 - 4 Conclusion and Future Work [Seite 328]
31.6 - References [Seite 328]
32 - Speech Recognition System Based on OLLO French Corpus by Using MFCCs [Seite 330]
32.1 - Abstract [Seite 330]
32.2 - 1 Introduction [Seite 330]
32.3 - 2 The Mel-Frequency Cepstrum Coefficient (MFCC) [Seite 331]
32.4 - 3 Coprus [Seite 331]
32.5 - 4 Experimental Results and Analyse [Seite 333]
32.6 - 5 Conclusion [Seite 335]
32.7 - References [Seite 335]
33 - Wavelets Based Image De-Noising: Application to EFTEM Imaging [Seite 336]
33.1 - Abstract [Seite 336]
33.2 - 1 Introduction [Seite 336]
33.3 - 2 Noise in EM Images [Seite 337]
33.4 - 3 Concrete Steps of Wavelets De-Noising Algorithm in EM [Seite 338]
33.4.1 - 3.1 Basic Assumption [Seite 338]
33.4.2 - 3.2 Concrete Steps of De-noising EM Images [Seite 340]
33.5 - 4 Results [Seite 340]
33.5.1 - 4.1 Experimental Test Data [Seite 340]
33.5.2 - 4.2 Performance Evaluation [Seite 340]
33.5.3 - 4.3 Results of the De-Noising Algorithm [Seite 343]
33.6 - 5 Concluding Remarques [Seite 344]
33.7 - References [Seite 346]
34 - New Front End Based on Multitaper and Gammatone Filters for Robust Speaker Verification [Seite 348]
34.1 - Abstract [Seite 348]
34.2 - 1 Introduction [Seite 348]
34.3 - 2 The Proposed Multitaper Gammatone Cepstral Coefficient MGCC [Seite 349]
34.4 - 3 Gammatone Filter [Seite 350]
34.5 - 4 Multitaper Spectrum Estimation [Seite 351]
34.6 - 5 Experiment [Seite 352]
34.6.1 - 5.1 Experimental Setup [Seite 352]
34.6.2 - 5.2 Experimental Results Using GMM-UBM [Seite 353]
34.6.3 - 5.3 Experimental Results Using I-Vector [Seite 356]
34.7 - 6 Conclusion [Seite 357]
34.8 - References [Seite 357]
35 - Comparative Study of Time Frequency Analysis Application on Abnormal EEG Signals [Seite 359]
35.1 - Abstract [Seite 359]
35.2 - 1 Introduction [Seite 359]
35.3 - 2 Methods [Seite 360]
35.3.1 - 2.1 Time-Frequency Analysis [Seite 360]
35.3.2 - 2.2 Rényi Entropy [Seite 361]
35.4 - 3 Materials and EEG Data [Seite 362]
35.5 - 4 Experimental Results [Seite 363]
35.5.1 - 4.1 Time-Frequency Analysis Using Rényi Entropy [Seite 363]
35.5.2 - 4.2 Peak Seizure Characterisation [Seite 364]
35.6 - 5 Conclusion [Seite 370]
35.7 - References [Seite 370]
36 - Performance Evaluation of Segmentation Algorithms Based on Level Set Method: Application to Medical Images [Seite 373]
36.1 - Abstract [Seite 373]
36.2 - 1 Introduction [Seite 373]
36.3 - 2 Level Set Method in Image Segmentation [Seite 374]
36.3.1 - 2.1 Level Sets [Seite 374]
36.3.2 - 2.2 Performance Evaluation [Seite 378]
36.4 - 3 Experimental Results [Seite 380]
36.5 - 4 Concluding Remarques [Seite 383]
36.6 - References [Seite 383]
37 - Design of Antipodal Linearly Tapered Slot Antennas (ALTSA) Arrays in SIW Technology for UWB Imaging [Seite 385]
37.1 - Abstract [Seite 385]
37.2 - 1 Introduction [Seite 385]
37.3 - 2 Single Antenna Element [Seite 386]
37.4 - 3 SIW Bends Design [Seite 388]
37.5 - 4 Design of SIW Power 2-Way Divider with ALTSA [Seite 388]
37.6 - 5 Resultants and Simulation [Seite 390]
37.7 - 6 Present Electromagnetic Fields in SIW Bends [Seite 391]
37.8 - 7 Conclusion [Seite 392]
37.9 - References [Seite 392]
38 - Large Scale Systems (SI03) [Seite 394]
39 - Optimized Sliding Mode Control of DC-DC Boost Converter for Photovoltaic System [Seite 395]
39.1 - Abstract [Seite 395]
39.2 - 1 Introduction [Seite 395]
39.3 - 2 System Configuration and Sliding Mode Control Strategy [Seite 396]
39.3.1 - 2.1 Validity of the Control Methodology [Seite 398]
39.4 - 3 Optimization of the Sliding Mode Control Strategy [Seite 402]
39.4.1 - 3.1 Simplex Method to Delimitate Sliding Mode Controller Gains [Seite 402]
39.4.2 - 3.2 PSO-Based Optimization of Sliding Mode Controller Gains [Seite 404]
39.5 - 4 Simulation Results [Seite 405]
39.6 - 5 Conclusion [Seite 407]
39.7 - References [Seite 408]
40 - Modeling of MOSFET Transistor by MLP Neural Networks [Seite 409]
40.1 - Abstract [Seite 409]
40.2 - 1 Introduction [Seite 409]
40.3 - 2 The Metal Oxide Semiconductor (MOS) Transistor [Seite 410]
40.4 - 3 Artificial Neuron Networks ANN [Seite 411]
40.4.1 - 3.1 Structure of ANN [Seite 411]
40.4.2 - 3.2 Training of an ANN [Seite 412]
40.5 - 4 Genetic Algorithms GA [Seite 412]
40.6 - 5 Applying of Genetic Algorithms for Neural Network Training [Seite 413]
40.7 - 6 Simulation Results [Seite 414]
40.8 - 7 Conclusion [Seite 416]
40.9 - References [Seite 416]
41 - Author Index [Seite 418]
