Title :
Neural network speed controller for drive system with elastic joint
Author_Institution :
Inst. of Electr. Machines Drives & Meas., Wroclaw Univ. of Technol., Wroclaw, Poland
Abstract :
This paper presents application of neural network for speed control of drive system with elastic connection. Analyzed object is characteristic due to complexity of the mechanical part of the drive. Motor machine is connected with load using long elastic shaft. Such form of electromagnetic torque transmission leads to appearing of oscillation in state variables transients. In result precise control of the speed or position is difficult to obtain. In article application of neural network trained on-line is applied in speed control loop. Weights coefficients are recalculated according to backpropagation algorithm based on error from reference model placed in control structure. Several simulation tests are presented. Obtained results presents quality of control using described neural model. In addition robustness against parameter changes is shown. Moreover influence of introduction of nonlinear elements (backlash) on achieved results is analyzed. Simulations are verified experimentally on laboratory benchmark. Control algorithm is implemented in dSPACE 1104.
Keywords :
backpropagation; machine control; motor drives; neural nets; torque control; velocity control; backlash; backpropagation algorithm; dSPACE 1104; drive system; elastic connection; electromagnetic torque transmission; laboratory benchmark; long elastic shaft; motor machine; neural network; nonlinear elements; oscillation; parameter changes; reference model error; speed control loop; state variables transients; weights coefficients; Mathematical model; Neural networks; Shafts; Torque; Transient analysis; Velocity control; electrical drive; neural networks; on-line training; speed control; two-mass system;
Conference_Titel :
EUROCON, 2013 IEEE
Conference_Location :
Zagreb
Print_ISBN :
978-1-4673-2230-0
DOI :
10.1109/EUROCON.2013.6625267
