TY - GEN
T1 - Application of fuzzy control in switched reluctance motor speed regulating system
AU - Liu, Weiguo
AU - Song, Shoujun
PY - 2006
Y1 - 2006
N2 - The applications of switched reluctance motors have being increased day by day, but it is a multivariable and strong-coupling highly nonlinear system, there are lots of difficulties to build its model. In this paper, combining with the quasi-linear model brought forward by Miller, the small-signal dynamic model of the switched reluctance motor is built based on matlab/simulink environment. This model is very suitable for research of control strategies. In industrial automation fields, conventional PID control is acting a very important role, but its robustness is very weak. In this paper, on the basis of conventional PID controller, fuzzy control technique is introduced. Two improved PID controller are proposed: Fuzzy_PID compound control and fuzzy parameters self-tuning PID control. The former combines the advantages of PID and fuzzy control, while the latter uses fuzzy technique to adjust the parameters of PID controller dynamically. The simulation results show that the two control strategies can not only improve the dynamic and static performances of the system effectively, but also enhance robustness of the system.
AB - The applications of switched reluctance motors have being increased day by day, but it is a multivariable and strong-coupling highly nonlinear system, there are lots of difficulties to build its model. In this paper, combining with the quasi-linear model brought forward by Miller, the small-signal dynamic model of the switched reluctance motor is built based on matlab/simulink environment. This model is very suitable for research of control strategies. In industrial automation fields, conventional PID control is acting a very important role, but its robustness is very weak. In this paper, on the basis of conventional PID controller, fuzzy control technique is introduced. Two improved PID controller are proposed: Fuzzy_PID compound control and fuzzy parameters self-tuning PID control. The former combines the advantages of PID and fuzzy control, while the latter uses fuzzy technique to adjust the parameters of PID controller dynamically. The simulation results show that the two control strategies can not only improve the dynamic and static performances of the system effectively, but also enhance robustness of the system.
UR - https://www.scopus.com/pages/publications/38849098514
U2 - 10.1109/CIMCA.2006.48
DO - 10.1109/CIMCA.2006.48
M3 - 会议稿件
AN - SCOPUS:38849098514
SN - 0769527310
SN - 9780769527314
T3 - CIMCA 2006: International Conference on Computational Intelligence for Modelling, Control and Automation, Jointly with IAWTIC 2006: International Conference on Intelligent Agents Web Technologies ...
BT - CIMCA 2006
PB - IEEE Computer Society
T2 - CIMCA 2006: International Conference on Computational Intelligence for Modelling, Control and Automation, Jointly with IAWTIC 2006: International Conference on Intelligent Agents Web Technologies and International Commerce
Y2 - 28 November 2006 through 1 December 2006
ER -