Title :
SNPID adaptive control based on WNN nonlinear identification for ship fin stabilizer
Author :
Li, Hui ; GUO, Chen ; Li, Xiaofang
Author_Institution :
Inf. Sci. Technol. Coll., Dalian Maritime Univ., Dalian
Abstract :
Single neuron PID (SNPID) adaptive control based on wavelet neural network (WNN) nonlinear identification for ship fin stabilizer system is presented in the paper. The SNPID adaptive controller is adopted to carry out feedback control, and assure the stability of closed loop system and restrain the disturbances. The WNN is used to identify the model of plant and adjust the parameters of SNPID. The simulation results illustrate the efficiency of the proposed method, and prove that the control method 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 :
adaptive control; closed loop systems; neurocontrollers; ships; three-term control; SNPID; adaptive control; closed loop system; feedback control; ship fin stabilizer system; ship roll-reducing control; single neuron PID; system adaptive ability; wavelet neural network; Adaptive control; Closed loop systems; Control systems; Feedback control; Marine vehicles; Neural networks; Neurons; Programmable control; Robust stability; Three-term control;
Conference_Titel :
System Simulation and Scientific Computing, 2008. ICSC 2008. Asia Simulation Conference - 7th International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-1786-5
Electronic_ISBN :
978-1-4244-1787-2
DOI :
10.1109/ASC-ICSC.2008.4675550