Sensorless Position Control using Adaptive Wavelet Neural Network for PM BLDCM

Author(s):  
Yang Tian ◽  
Ting-na Shi ◽  
Chang-liang Xia ◽  
Dan Liu ◽  
Qian Zhang
2015 ◽  
Vol 764-765 ◽  
pp. 634-639
Author(s):  
Yen Bin Chen ◽  
Yung Lung Lee ◽  
Shou Jen Hsu ◽  
Chin Chun Chang ◽  
Yi Wei Chen

The study proposed adaptive wavelet neural network controller can achieve good and precise welding control performance and use synchrotron radiation research center developed multi-gun group automatic welding system to verify the validity of the research method. Multi-gun group welding system is applied in Taiwan Photon Source (TPS). Storage ring aluminum alloy vacuum chamber of Taiwan Photon Source .In the past aluminum alloy vacuum chamber welding, it all depends on the empirical welding rule of operator to give appropriate welding current, argon flow, wire feed speed and welding speed for control. Therefore, the paper uses automatic welding skill, which takes National Instruments PXI-8180 system as basic structure, and adaptive wavelet neural network controlled four optimized parameters, I.E. welding current, wire feed speed, flow rate of argon gas and welding speed, The vacuum chamber pressure value is also up to 6.2X10-10Torr/mA. It is successfully applied to the TPS system. Therefore, it can prove the effectiveness and practicality of the method proposed in this study.


2014 ◽  
Vol 625 ◽  
pp. 615-620
Author(s):  
Jin Wei Liang ◽  
Hung Yi Chen

This paper presents the design, fabrication and control of a piezoelectric-type droplet generator which is applicable for on-line dispensing. The piezoelectric-actuated dispensing system consists of a linear piezoelectric motor (LPM) actuated table, a plastic syringe, a nozzle, a linear encoder and a PC-based control unit. Adaptive wavelet neural network (AWNN) control is applied to overcome nonlinear hysteresis inherited in the LPM. The adaptive learning rates are derived based on the Lyapunov stability theorem so that convergence of the tracking error can be assured. Unlike open-loop dispensing system, the system proposed can potentially generate droplets with high accuracy. Experimental verifications including regulating and tracking control are performed firstly to assure the reliability of the proposed control schemes. Real dispensing is then conducted to validate the feasibility of the piezoelectric-actuated drop-on-demand droplet generator. The results demonstrate that the proposed scheme works well in developing the piezoelectric-actuated drop-on-demand dispensing system.


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