Advanced Fuzzy-Neural Control 2001
A Proceedings Volume from the Ifac Workshop, Valencia, Spain, 15-16 October 2001
Published on 17. May 2002
Book
Paperback/Softback
198 pages
978-0-08-043963-1 (ISBN)
Description
Containing the papers presented at the first IFAC Workshop on Advanced Fuzzy-Neural Control, held at Valencia, Spain, on 15-16 October 2001, this is the first IFAC technical meeting specifically devoted to fuzzy and neural control. The use of artificial intelligence techniques has been expanded to many engineering areas. Fuzzy systems, neural networks, genetic algorithms and, in general, soft computing techniques are regarded as alternatives for the solution of complex problems involving non-linear systems, optimisation and/or dealing with approximate knowledge. Fuzzy logic controllers are undoubtedly one of the most successful applications of fuzzy logic theory. The issues covered in the proceedings include: stability, robustness and adaptation; learning and local models; structures; design methodologies; heuristics versus model based design; applications in process control and applications in robotics. In addition to the papers, the text also includes a section which summarises ideas and conclusions on fuzzy logic controllers from the experts attending the IFAC Workshop.
More details
Series
Language
English
Place of publication
Amsterdam
Netherlands
Publishing group
Elsevier Science & Technology
Target group
College/higher education
Professional and scholarly
ISBN-13
978-0-08-043963-1 (9780080439631)
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Schweitzer Classification
Content
Stability, robustness and adaptation: stability issues in fuzzy control, J. Aracil, F. Gordillo; stabilization of nonlinear systems based on fuzzy lyapunov function, K. Tanaka et al.; conditions for non quadratic stabilization of discrete fuzzy models, T.M. Guerra, L. Vermeiren; stability analysis of nonlinear control systems with fuzzy DMC controllers, P. Marusak, P. Tatjewski; conicity and lyapunov stability analysis of reactive navigation with fuzzy perception and fuzzy control, F. Cuesta, A. Ollero; on the robust performance of fuzzy linear systems, J. Bondia, J. Pic ; fuzzy control manoeuvring of tractor-trailer vehicles using lyapunov functions and bifurcation theory; A. Gonz lez-Cantos et al. Applications in process control: using fuzziness for causal diagnosis in engine dyno test benches, S. Boverie et al; linear and fuzzy control for machining process - design and experiments, R.E. Haber et al; gain-scheduled control of a servo pneumatic actuator using Takagi-Sugeno fuzzy models, H. Schulte; multivariable fuzzy control of fedbatch bioreactors, E. Pic -Marco et al. Learning and local models: open-loop fuzzy control - iterative learning, M. Olivares et al; single and multi-objective genetic programming design for B-spline neural networks and neuro-fuzzy systems, C. Cabrita et al; identification for local-model control with fuzzy clustering, J.L. Diez et al; direct inverse control using learning automata, E. Ikonen et al. Structures: neuro and neuro-fuzzy identification for model-based control, A. Fink et al; state space neural networks in non-linear adaptive system identification and control, J. Henriques et al; a comparative analysis of PID methods using fuzzy objective, F. Mesa Varela et al. Applications in robotics: development of an aerial robot toward real applications, M. Sugeno; skills learning in an autonomous mobile robot using continuous reinforcement, M.J.L. Boada, M.A. Salichs; biologically inspired architecture for multisensorial control of robotic systems, J.L. Pedreno-Molina et al; parametric neurocontroller for positioning of a tendon-driven transmission system, J.I. Mulero-Martinez et al. Design methodologies: fuzzy backstepping control technique for mechanical systems, P. Carbonell, Z.-P. Jiang; decentralized decoupled sliding-mode control for two-dimensional inverted pendulum using neuro-fuzzy modelling, M. Farrokhi, A. Ghanbari; centralized and decentralized neural-network sliding-mode robot controller, R. Safaric, K. Jezernik; hybrid state feedback control for T-S-fuzzy systems with nonminimum phase, S.S. Kim, J.Y. Choi; a multivariable neural predictive control algorithm, M. Lawrynczuk, P. Tatjewski. Heuristics: model-based or heuristic-based fuzzy logic controllers? foundations and examples, L. Foulloy et al; biomimicry, mathematics, and physics for control and automation - conflict or harmony, K. Passino.