DocumentCode :
113912
Title :
Application of additional momentum in PID neural network
Author :
Hua Shu ; Yuan-kun Xu
Author_Institution :
Inst. of Mech. & Electr. Eng., Guangzhou Univ., Guangzhou, China
fYear :
2014
fDate :
26-28 April 2014
Firstpage :
172
Lastpage :
175
Abstract :
PID neural network (PIDNN) is a new type of feed-forward neural network which has been found by Huai-lin Shu, in which neural network is integrated with PID control law. The priori knowledge of PID control can be used to choose the initial weights to make sure that PIDNN control systems are initial stable. Without priori knowledge and using the random initial weights, initial stable of the PIDNN system may be uncertain. The paper proposes an improved algorithm which has momentum factor to overcome the local minimum of the PIDNN. The distinct improvement of the PIDNN control system is proved by simulation results.
Keywords :
feedforward neural nets; neurocontrollers; random processes; three-term control; PID control law; PID neural network; PIDNN control systems; additional momentum application; feedforward neural network; momentum factor; random initial weights; Neural networks; Neurons; PD control; Simulation; Stability analysis; Training; PIDNN; initial weight; momentum factor; stability;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Science and Technology (ICIST), 2014 4th IEEE International Conference on
Conference_Location :
Shenzhen
Type :
conf
DOI :
10.1109/ICIST.2014.6920358
Filename :
6920358
Link To Document :
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