NEURAL NETWORK CONTROL SCHEMES FOR PM SPHERICAL STEPPER MOTOR DRIVE
This paper presents three control schemes for PM spherical stepper motor drive. In the neural network PD control scheme, the neural network is used to train the control parameters online. Based on the non-linear system dynamic model under continuous trajectory tracking mode, the robust neural network control scheme is presented to eliminate uncertainties to improve the trajectory tracking robust stability and overcome the undesired influence of the uncertainties. The adaptive fault accommodation neural network control scheme assures the convergence of the estimate errors of the neural network and the fault-monitoring system in the presence of system uncertainties. Simulations of the proposed control scheme on the spherical stepper motor system demonstrate the effectiveness on satisfactory tracking performance.
Tracking Permanent magnet Spherical stepper motor Dynamic model Neural network control
ZHENG LI QUN-JING WANG
School of Electrical Engineering and Information Science, Hebei University of Science and Technology School of Electrical Engineering and Automation, Hefei University of Technology, Hefei 230009, China
国际会议
2008 International Conference on Machine Learning and Cybernetics(2008机器学习与控制论国际会议)
昆明
英文
2042-2047
2008-07-12（万方平台首次上网日期，不代表论文的发表时间）