DocumentCode :
2676400
Title :
CPT system with multiple soft-switch operating point control of particle swarm optimization BP neural network
Author :
Lihong, He ; Qingbin, Liu ; Xiaohong, Zhang ; Yingying, Guo
Author_Institution :
Inf. Sci. & Eng. Coll., Northeastern Univ., Shenyang, China
fYear :
2012
fDate :
23-25 May 2012
Firstpage :
4104
Lastpage :
4109
Abstract :
We take primary edge of LCL and secondary edge series resonant CPT system as the research object and design BP neural network controller based on the power transmission characteristic differences of the CPT system with multiple soft-switch operating points. The system can switch back and forth between multiple soft-switch operating points according to error feedback information, so that effective power control can be achieved. For some defects such as long convergence time and easily falling into partial minimum, Particle Swarm Optimization is applied to optimize BP network weights for the improvement of BP network controller. The simulation results show that it not only accelerate the convergence process of BP, but also improve training and inspection accuracy of BP neural network. It not only satisfy the control requirements of CPT system, but also satisfy the working conditions of the soft switches. Higher transmission efficiency can be achieved.
Keywords :
backpropagation; control system synthesis; inductive power transmission; neurocontrollers; particle swarm optimisation; power control; zero current switching; CPT system control requirements; LCL; contactless power transfer; convergence process; error feedback information; inspection accuracy; multiple soft switch operating point control; particle swarm optimization BP neural network controller design; power control; power transmission characteristic differences; secondary edge series resonant CPT system; training; Inverters; Neural networks; Particle swarm optimization; Resonant frequency; Switches; Training; CPT system; Neural Network; Particle Swarm Optimization; Soft-switch Working Points;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control and Decision Conference (CCDC), 2012 24th Chinese
Conference_Location :
Taiyuan
Print_ISBN :
978-1-4577-2073-4
Type :
conf
DOI :
10.1109/CCDC.2012.6244656
Filename :
6244656
Link To Document :
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