Valavanis Applications of Intelligent Control to Engineering Systems

In Honour of Dr. G. J. Vachtsevanos
1. Auflage 2009
ISBN: 978-90-481-3018-4
Verlag: Springer Netherlands
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, Band 39, 426 Seiten

Reihe: Intelligent Systems, Control and Automation: Science and Engineering

This book reflects the work of top scientists in the field of intelligent control and its applications, prognostics, diagnostics, condition based maintenance and unmanned systems. It includes results, and presents how theory is applied to solve real problems.

Autoren/Hrsg.

Valavanis, Kimon P.

Inhaltsverzeichnis

1;Table of Contents;7
2;Preface;9
3;List of Contributors;11
4;PART I DIAGNOSTICS, PROGNOSTICS, CONDITION-BASED MAINTENANCE;19
4.1;1 Selected Prognostic Methods with Application to an Integrated Health Management System;20
4.1.1;1.1 Introduction;20
4.1.2;1.2 Prognostic Algorithm Approaches;21
4.1.3;1.3 Statistical Reliability and Usage-Based Approaches;22
4.1.4;1.4 Signal Integrity and Anomaly Detection;24
4.1.5;1.5 Trend-Based Evolutionary Approaches;26
4.1.6;1.6 Data-Driven Model-Based Approaches;27
4.1.7;1.7 State-Estimator-Based Prognostics;28
4.1.8;1.8 Physics-Based Modeling Approaches;30
4.1.9;1.9 Prognosis Remaining Useful Life Probability Density Function;32
4.1.10;1.10 Adaptive Prognosis;34
4.1.11;1.11 Distributed Prognosis System Architecture;35
4.1.12;1.12 Conclusions;36
4.1.13;References;37
4.2;2 Advances in Uncertainty Representation and Management for Particle Filtering Applied to Prognostics*;39
4.2.1;2.1 Introduction;40
4.2.2;2.2 Uncertainty Representation and Management in Long-Term Prediction: A Particle Filtering-Based Approach;41
4.2.3;2.3 Uncertainty Management in Long-Term Predictions;44
4.2.4;2.4 An Illustrative Example;46
4.2.5;2.5 Conclusion;50
4.2.6;Acknowledgment;51
4.2.7;References;51
4.3;3 A Novel Blind Deconvolution De-Noising Scheme in Failure Prognosis;52
4.3.1;List of Symbols;52
4.3.2;3.1 Introduction;53
4.3.3;3.2 The De-Noising Scheme Architecture;55
4.3.4;3.3 Vibration Data Analysis;56
4.3.5;3.4 Blind Deconvolution De-Noising Scheme;64
4.3.6;3.5 Experimental Studies;66
4.3.7;3.6 Conclusion;76
4.3.8;Acknowledgement;77
4.3.9;References;77
4.4;4 Particle Filter Based Anomaly Detection for Aircraft Actuator Systems;79
4.4.1;Nomenclature;80
4.4.2;4.1 Introduction;81
4.4.3;4.2 System Background;82
4.4.4;4.3 Theory;85
4.4.5;4.4 Experimental Evaluation;95
4.4.6;4.5 Conclusion;101
4.4.7;Acknowledgements;101
4.4.8;References;101
5;PART II UNMANNED AERIAL SYSTEMS;103
5.1;5 Design of a Hardware and Software Architecture for Unmanned Vehicles: A Modular Approach;104
5.1.1;5.1 Introduction;105
5.1.2;5.2 Hardware Design;106
5.1.3;5.3 Software Design;108
5.1.4;5.4 Hardware Architecture;110
5.1.5;5.5 Software Architecture;119
5.1.6;5.6 Field Experiments;125
5.1.7;5.7 Conclusions;127
5.1.8;References;127
5.2;6 Designing a Real-time Vision System for Small Unmanned Rotorcraft: A Minimal and Cost- Effective Approach;129
5.2.1;6.1 Introduction;129
5.2.2;6.2 Literature Review;133
5.2.3;6.3 Restating and Addressing the Problem;136
5.2.4;6.4 System Implementation and Performance Evaluation;149
5.2.5;6.5 Conclusion;168
5.2.6;6.6 Future Research;173
5.2.7;Acknowledgment;176
5.2.8;References;177
5.3;7 Coordination of Helicopter UAVs for Aerial Forest- Fire Surveillance;180
5.3.1;7.1 Introduction;180
5.3.2;7.2 Low-Cost Unmanned Aerial Vehicles;183
5.3.3;7.3 Cooperation Strategies and Consensus for UAVs in Forest Fire Surveillance Operations;184
5.3.4;7.4 Unmanned Quadrotor Helicopter Dynamics;187
5.3.5;7.5 UqH Control Design and rendez-vous Task Formulation for Forest Fire Surveillance;194
5.3.6;7.6 Simulation Studies;198
5.3.7;7.7 Conclusions;202
5.3.8;References;203
5.4;8 Genetic Fuzzy Rule-Based Classifiers for Land Cover Classification from Multispectral Images;205
5.4.1;8.1 Introduction;205
5.4.2;8.2 Basic Concepts;207
5.4.3;8.3 Boosted Genetic Fuzzy Classifier;212
5.4.4;8.4 Experimental Results;221
5.4.5;8.5 Conclusions;229
5.4.6;References;230
5.5;9 Epileptic Seizures May Begin Hours in Advance of Clinical Onset: A Report of Five Patients*;233
5.5.1;9.1 Introduction;234
5.5.2;9.2 Clinical Background;235
5.5.3;9.3 Results;238
5.5.4;9.4 Clinical Research: Experimental Issues;245
5.5.5;9.5 An Implantable Diagnostic-Therapeutic Device;246
5.5.6;9.6 Analogy to Cardiology;247
5.5.7;9.7 Conclusion;248
5.5.8;9.8 Experimental Methods;248
5.5.9;Acknowledgements;250
5.5.10;References;251
5.6;10 Intelligent Control Strategies for Neurostimulation;254
5.6.1;10.1 Introduction;254
5.6.2;10.2 Implantable Neurostimulation Devices;255
5.6.3;10.3 Experimental Evidence for Feedback Devices;257
5.6.4;10.4 Computer Simulation of Pathologic Oscillations and Feedback Therapy;258
5.6.5;10.5 Extension to Continuous Feedback Control;260
5.6.6;10.6 Conclusion;267
5.6.7;References;269
5.7;11 Software Technology for Implementing Reusable, Distributed Control Systems*;272
5.7.1;11.1 Component-Based Architectures;273
5.7.2;11.2 Distributed Computing Overview;279
5.7.3;11.3 Real-Time Computing;288
5.7.4;11.4 Commercial Products and Market Trends;292
5.7.5;11.5 Research Tools on the Horizon;293
5.7.6;11.6 Summary;294
5.7.7;Acknowledgments;295
5.7.8;References;295
5.8;12 UGV Localization Based on Fuzzy Logic and Extended Kalman Filtering;299
5.8.1;Nomenclature;300
5.8.2;12.1 Introduction;300
5.8.3;12.2 RelatedWork;302
5.8.4;12.3 Extended Kalman Filter;303
5.8.5;12.4 Fuzzy Logic Controllers;307
5.8.6;12.5 Case Study;311
5.8.7;12.6 Conclusions;330
5.8.8;References;331
5.9;13 Adaptive Estimation of Fuzzy Cognitive Networks and Applications;333
5.9.1;13.1 Introduction;334
5.9.2;13.2 Fuzzy Cognitive Maps;336
5.9.3;13.3 Existence and uniqueness of solutions in Fuzzy Cognitive Maps;338
5.9.4;13.4 Online Parameter Estimation of Fuzzy Cognitive Maps;350
5.9.5;13.5 Numerical Examples;355
5.9.6;13.6 The Fuzzy Cognitive Network Approach;357
5.9.7;13.7 Conclusions;364
5.9.8;References;365
5.10;14 An Improved Method in Receding Horizon Control with Updating of Terminal Cost Function;368
5.10.1;14.1 Introduction;369
5.10.2;14.2 Receding Horizon Control;370
5.10.3;14.3 Updated Terminal Cost Receding Horizon Control;377
5.10.4;14.4 Simulation Results;383
5.10.5;14.5 Conclusion;392
5.10.6;References;395
5.11;15 Identifier-Based Discovery in Large-Scale Networks;397
5.11.1;15.1 Introduction;398
5.11.2;15.2 Networks and Strategic Behavior;400
5.11.3;15.3 Identifier-Based Discovery;406
5.11.4;15.4 An Incentive Model for Route Distribution and Discovery in Path Vector Protocols;413
5.11.5;15.5 HRP: Convergence, and Equilibria;420
5.11.6;15.6 Conclusions and Ongoing Work;424
5.11.7;Appendix A: Proof of Lemma 1;425
5.11.8;References;426