Computational Intelligence in Systems and Control Design and Applications / Edition 1

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The field of computational intelligence (CI) has expanded rapidly during recent years with a large and still increasing range of applications. This book contains a cohesive set of thirty contributions that cover a wide, well-selected range of topics. The book is organized in the following five parts:

• Part I: Neural network-based intelligent estimation and control
• Part II: Fuzzy logic-based intelligent estimation and control
• Part III: Genetic algorithm-based system analysis and design
• Part IV: Hybrid intelligent techniques in system analysis and control
• Part V: Computational intelligence in engineering applications

Parts I-IV include general overviews, new techniques and practical CI algorithms for system analysis, identification, optimization and control, and Part V contains nine important applications of CI dealing with robot control, collision avoidance of dangerous ships, automated visual inspection, control of fed-batch bioprocesses, identification of naval turbochargers, semi-active suspension design of ground vehicles, ecological populations' modeling, vehicle navigation, state estimation of electric power systems, and multi-robot cooperative control.
The book can be used as a reference volume by researchers and practitioners in the field, and as a rich unified information source by teachers and students in related postgraduate programs, thus saving considerable time in searching the scattered literature in the field.

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Table of Contents

Preface. Contributors. Part I: Neural Network-Based Intelligent Estimation and Control. 1. Intelligent Forecasting and Fault Diagnosis Using Neural Estimators; E.S. Tzafestas, S.G. Tzafestas. 2. Parameter Identification of Dynamical Systems Using Neural Networks; N. Yadaiah, et al. 3. Recent Developments in Neural Network PID Autotuning; A.E.B. Ruano. 4. Adaptive Self-Tuning Neural-Network-Based Controller; P. Ponik, I. Grabec. 5. Neuro-Control for Multivariable Systems; S. Omatu, M. Yoshioka. Part II: Fussy Logic-Based Intelligent Estimation and Control. 6. Orthogonal Least Squares Based Fuzzy Model For Short Term Load Forecasting; P.A. Mastorokostas, et al. 7. An Unsupervised Fussy Classification Algorithm for Non Elliptic Classes; P. Billaudel, et al. 8. Necessary and Sufficient Conditions for Stability of Dynamic Fuzzy Systems; F. Matía, et al. 9. Fuzzy Behavior-Based Control with Local Learning; K. Izumi, K. Watanabe. 10. A Stable and Robust Fuzzy Controller for the Position Control of Robots; Z. Doulgeri, D. Biskas. 11. Stability Analysis and Fuzzy Self-Tuning Control of a Nonlinear Process with Limit Points; D.I. Sagias, et al. Part III: Genetic Algorithm-Based System Analysis and Design. 12. Application of the Genetic Algorithm (Approach) to a Cellular Dynamic Channel Allocation Model; H.G. Sandalidis, et al. 13. Applying Genetic Algorithms to Workshop Cell Decomposition; P. De Lit, et al. 14. A Genetic Algorithm for Efficient Video Content Representation; A.D. Doulamis, et al. 15. Fast Synthetic Genetic Algorithm Combined with BP – Application to Short-Term Economic Dispatch of Hydrothermal Power Systems; X. Meng, et al. 16. Parallel Platform Design and Kinematics Analysis Using Evolution Strategy Via Regeneration; A.E. Kanarachos, K.S. Roussis. Part IV: Hybrid Intelligent Techniques in System Analysis and Control. 17. A Hybrid Neural-Classical Structure for the Modelling of a Bioprocess; A. Hanomolo, et al. 18. Estimation of State Variable in Power System Combining Theoretical Knowledge with Neural Network; T. Atanasova, et al. 19. Route Selection in a Neuro-Fuzzy Vehicle Navigation System; G.K.H. Pang. 20. Hierarchical Position Control Using Fuzzy Logic: Opportunities and Limitations; A. Zilouchian, et al. 21. Impedance Control for Multi-DOF Manipulator by Learning Environment Models; F. Nagata, et al. Part V: Computational Intelligence in Engineering Applications. 22. Engineering Applications of N-Step Ahead Neurocontrol; A. Hountras, et al. 23. Neural Classification of Dangerous Ships in Collision Situations; J. Lisowski, et al. 24. Neural Computing in Fabrics Inspection System; H. Liu, et al. 25. Control of a Fed-Batch Bioprocess by Using Neural Network Observers; Y.S. Boutalis, O.I. Kosmidou. 26. Neural Networks for the Model Identification of the Naval Turbochargers; N.G. Pentelelis, et al. 27. An Optimum Suspension System for Vehicles Using Fuzzy Reasoning; A. Kanarachos, et al. 28. Fuzzy Markov Systems for the Description of Population Dynamics; M.A. Symeonaki, et al. 29. Concerning Hopfield Networks: An Overview with Application to System Identification and Control; S.G. Tzafestas, D. Vogiatzis. 30. Cooperative Control Using Multiple Manipulators with different Command Inputs; K. Izumi, et al. Index.

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