DocumentCode :
2741860
Title :
Development of Soft Sensor for Sensorless Automatic Gantry Crane Using RBF Neural Networks
Author :
Solihin, Mahmud Iwan ; Wahyudi ; Albagul, Abdulgani
Author_Institution :
Dept. of Mechatronics Eng., Int. Islamic Univ. Malaysia, Kuala Lumpur
fYear :
2006
fDate :
7-9 June 2006
Firstpage :
1
Lastpage :
6
Abstract :
To attain a good control performance of automatic gantry crane system, sensors are indispensable instrument for feedback signals. However, sensing the payload motion of a real gantry crane, particularly swing motion, is not easy and sometimes costly. Therefore, a sensorless automatic gantry crane system is developed and proposed in this paper. A soft sensor based on artificial neural network is introduced to eliminate the real sensor. Instead, a sensor measuring armature current of DC motor driving the cart is used to provide dynamic information for the soft sensor. A simulation study using dynamic model of lab-scale automatic gantry crane is carried out to evaluate the effectiveness of the proposed soft sensor. The results show that the soft sensor can estimate effectively the unmeasured state. Moreover, the proposed method has robustness to deal with parameter variations
Keywords :
DC motors; cranes; loading equipment; neurocontrollers; radial basis function networks; robust control; state estimation; DC motor; RBF neural networks; armature current measurement; artificial neural network; radial basis function networks; robustness; sensorless automatic gantry crane control; soft sensor development; Artificial neural networks; Automatic control; Control systems; Cranes; Instruments; Neural networks; Neurofeedback; Payloads; Sensor systems; Sensorless control; gantry crane; radial basis function networks; soft sensor;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Cybernetics and Intelligent Systems, 2006 IEEE Conference on
Conference_Location :
Bangkok
Print_ISBN :
1-4244-0023-6
Type :
conf
DOI :
10.1109/ICCIS.2006.252278
Filename :
4017837
Link To Document :
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