Robustness Improvement of a Model Reference & Sensitivity Model-based Self-learning Fuzzy Logic Controller (CROSBI ID 467306)
Prilog sa skupa u zborniku | izvorni znanstveni rad | međunarodna recenzija
Podaci o odgovornosti
Kovačić, Zdenko ; Bogdan, Stjepan ; Balenović, Mario
engleski
Robustness Improvement of a Model Reference & Sensitivity Model-based Self-learning Fuzzy Logic Controller
In this paper, improved robustness of a PD type self- learning fuzzy logic controller (SLFLC) is described. The SLFLC utilizes a second-order reference model and a sensitivity model for learning of SLFLC parameters. The robustness has been improved by adding an integral term whose gain coefficient is also synthesized by learning. The additional learning algorithm is activated after completion of the main learning algorithm. The effectiveness of the SLFLC in case of using the additional learning algorithm has been tested by simulation on the models of static linear and nonlinear systems. The results have proved that the SLFLC provides desired closed-loop behavior and eliminates a steady-state error in the presence of external disturbance.
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Podaci o prilogu
643-647-x.
1998.
objavljeno
Podaci o matičnoj publikaciji
Proceedings of the 1998. IEEE Conference on Control Applications
Lewis, Frank L.
Trst: Institute of Electrical and Electronics Engineers (IEEE)
Podaci o skupu
1998 IEEE International Conference on Control Applications
predavanje
01.09.1998-04.09.1998
Trst, Italija