Title :
A new fuzzy adaptive combined-inversion control of two-motor drive system
Author :
Yaojie Mi ; Guohai Liu ; Wenxiang Zhao ; Hao Zhang ; Deshui Hu ; Duo Zhang
Author_Institution :
Sch. of Electr. & Inf. Eng., Jiangsu Univ., Zhenjiang, China
Abstract :
Multi-motor drive system have been widely applied in many industrial fields, such as electric vehicles and rail transit. It is a multi-input multi-output (MIMO), nonlinear and strong-coupling complicated system. Therefore, it is hard to obtain good performance by traditional control methods. In addition, due to the accuracy of sensors or external disturbance, some system states are very difficult to be measured accurately in practice. To solve these problems, a new control method, termed as artificial neural network combined-inversion (ANNCI), is proposed for coupling control and soft-sensing. This control strategy adopts the left-inversion as a soft-sensor and the right-inversion as a decoupling control. Furthermore, fuzzy adaptive control is introduced into ANNCI to improve operation performance. Simulations are performed for verification.
Keywords :
MIMO systems; adaptive control; fuzzy control; machine control; motor drives; neurocontrollers; ANNCI; MIMO-nonlinear-strong-coupling complicated system; artificial neural network combined-inversion; coupling control; decoupling control; electric vehicles; fuzzy adaptive combined-inversion control; industrial fields; left-inversion; multimotor drive system; multiple-input multiple-output system; rail transit; right-inversion; soft-sensing; soft-sensor; system states; two-motor drive system; Education; Interconnected systems; MIMO; Observers; Rotors; Shafts;
Conference_Titel :
Electrical Machines and Systems (ICEMS), 2013 International Conference on
Conference_Location :
Busan
Print_ISBN :
978-1-4799-1446-3
DOI :
10.1109/ICEMS.2013.6713237