Title :
Design of electric dynamic load simulator based on recurrent neural networks
Author :
Wang Mingyan ; Ben, Guo ; Yudong, Guan ; Hao, Zhang
Author_Institution :
Dept. of Electr. Eng., Harbin Inst. of Technol., China
Abstract :
This paper describes the electric dynamic load simulator (DLS) driving by permanent magnet synchronous motor. It can reproduce desired load torque acting on loaded objective to test its performance. A simplified dynamic model is derived to clarify the causation of redundancy torque caused by the motion of loaded objective and illustrate the drawbacks of applying conventional control strategy. Real-time recurrent neural networks based iterative learning control strategy is adopted. It can restrain redundancy torque and improve the accuracy of load torque in spite of the nonlinearity and uncertainty in the system. The expected results have been obtained from simulation and experiment.
Keywords :
iterative methods; machine control; neurocontrollers; permanent magnet motors; recurrent neural nets; synchronous motors; torque control; electric dynamic load simulator; iterative learning control strategy; load torque; loaded objective; permanent magnet synchronous motor; real-time recurrent neural networks; recurrent neural networks; redundancy torque causation; redundancy torque restraint; Actuators; Mathematical model; Mechanical sensors; Motion control; Nonlinear dynamical systems; Permanent magnet motors; Proportional control; Recurrent neural networks; Rotors; Torque control;
Conference_Titel :
Electric Machines and Drives Conference, 2003. IEMDC'03. IEEE International
Print_ISBN :
0-7803-7817-2
DOI :
10.1109/IEMDC.2003.1211264
