DocumentCode :
2719851
Title :
Hybrid Control of Inverse Model Wavelet Neural Network and PID and Its Application to Fin Stabilizer
Author :
Li, Hui ; GUO, Chen ; Jin, Hongzhang
Author_Institution :
Automation and Elec. Eng. College, Dalian Maritime University, Dalian 116026, P.R.China. delxf@263.net
Volume :
1
fYear :
2006
fDate :
21-23 June 2006
Firstpage :
436
Lastpage :
440
Abstract :
A hybrid control combining inverse model wavelet neural network (IMWNN) and conventional PID controller for ship fin stabilizer system is presented in the paper. The IMWNN is employed to implement the feed-forward control, and obtain the inverse dynamics model of the process. The conventional PID controller is adopted to carry out feedback control, and assure the stability of closed loop system and restrain the disturbances. The simulation results illustrate the efficiency of the proposed method, and prove that the hybrid model can make sure the stability and robustness of control system and effectively improve the system adaptive ability. This method not only can be applied to ship roll-reducing control, but also can be used in other complexity, non-linearity system control.
Keywords :
Fin stabilizer; Hybrid control; PID control; Wavelet neural network; Closed loop systems; Control systems; Feedback control; Feedforward systems; Inverse problems; Marine vehicles; Neural networks; Robust control; Robust stability; Three-term control; Fin stabilizer; Hybrid control; PID control; Wavelet neural network;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Control and Automation, 2006. WCICA 2006. The Sixth World Congress on
Print_ISBN :
1-4244-0332-4
Type :
conf
DOI :
10.1109/WCICA.2006.1712354
Filename :
1712354
Link To Document :
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