Title :
CMAC neural networks based combining control for marine diesel engine generator
Author :
Weifeng Shi ; Tang, Tianhao
Author_Institution :
Dept. of Electr. Autom., Shanghai Maritime Univ., China
Abstract :
In neural networks control system, CMAC neural networks control is provided with characteristic of learning online and rapidly. Combine with CMAC neural networks and PID controlling, a combining control was built for marine diesel engine generator system. The CMAC neural networks control was not simply copy from PID control in the generator combining control system. Through learning of CMAC neural networks continuously, the CMAC neural networks control become main effect control. In a power system control simulation of a marine electric propulsion vessel, this control method was used. Under the simulating test of adding 50% or 16% active load of generator rating value suddenly and simulating test of three phase grounding fault, the control dynamic characteristic was satisfactory with CMAC neural networks combine control of marine diesel engine generator system.
Keywords :
adaptive control; cerebellar model arithmetic computers; diesel engines; diesel-electric generators; earthing; electric propulsion; electrical faults; learning systems; marine systems; neurocontrollers; power system control; three-term control; CMAC neural networks; PID control; active load; combining control system; control dynamic characteristic; generator rating value; marine diesel engine generator; marine electric propulsion vessel; neural networks control system; online learning control; power system control simulation; three phase grounding fault; Character generation; Control systems; Diesel engines; Grounding; Neural networks; Power system control; Power system simulation; Propulsion; System testing; Three-term control;
Conference_Titel :
Intelligent Control and Automation, 2004. WCICA 2004. Fifth World Congress on
Print_ISBN :
0-7803-8273-0
DOI :
10.1109/WCICA.2004.1342078