Title :
Fuzzy modular networks for structural system identification
Author :
Cacmakci, A.M. ; Isik, Can
Author_Institution :
Dept. of Electr. & Comput. Sci., Syracuse Univ., NY, USA
Abstract :
We present a new approach to structural identification of complex dynamic systems by means of a fuzzy modular network. With all its advantages, extraction of structurally explainable models have been the envy of most system identification applications. A method based on fuzzy dynamic modeling in a pre-selected feature space is used in the self-organizing decomposition/modularization of the problem domain. A case example in a two-link manipulator arm is presented to further illustrate the ideas
Keywords :
fuzzy neural nets; identification; learning (artificial intelligence); manipulators; mathematics computing; complex dynamic systems; fuzzy dynamic modeling; fuzzy modular networks; self-organizing decomposition; structural system identification; two-link manipulator arm; Application software; Computer science; Fuzzy sets; Fuzzy systems; Input variables; Instruments; Learning systems; Robustness; System identification; Trajectory;
Conference_Titel :
Fuzzy Information Processing Society - NAFIPS, 1998 Conference of the North American
Conference_Location :
Pensacola Beach, FL
Print_ISBN :
0-7803-4453-7
DOI :
10.1109/NAFIPS.1998.715511
