Conference paper
Subspace identification of dynamical neurofuzzy system using LOLIMOT
Electrical Eng. Dept., Faculty of Eng., Islamic Azad University of Tehran-Science and Research Branch., Iran1
Control Dept., Faculty of Electrical Eng., K. N. Toosi University of Technology, Tehran, Iran2
In this paper a novel method for identification of dynamical neurofuzzy system is proposed. The proposed method benefits from both LOLIMOT as the premise part optimizer of the system and the subspace identification method of N4SID to optimize the state space parameters of the conclusion part. The resulting neurofuzzy system is a nonlinear dynamical system which is modeled by some locally linear state space models. using this model it is then possible to use different parallel distributed control techniques such as linear matrix inequality to control the identified system.
The proposed approach is tested on a flexible robot arm and satisfactory results are generated.
| Language: | English |
|---|---|
| Year: | 2010 |
| Pages: | 366-372 |
| Proceedings: | 2010 IEEE International Conference on Systems, Man and Cybernetics - SMC |
| ISBN: | 1424465869 , 1424465877 , 1424465885 , 9781424465866 , 9781424465873 and 9781424465880 |
| ISSN: | 1062922x and 25771655 |
| Types: | Conference paper |
| DOI: | 10.1109/ICSMC.2010.5641736 |
LOLIMOT LOLIMOT algorithm N4SID N4SID algorithm distributed control dynamical neurofuzzy system flexible manipulators flexible robot arm fuzzy control linear matrix inequalities linear matrix inequality locally linear model tree neurocontrollers neurofuzzy nonlinear control systems nonlinear dynamical system nonlinear identification numerical algorithms parallel distributed control techniques state space parameter state-space methods subspace identification subspace identification method subspace state space system identification trees (mathematics)
