Title :
Hybrid feedforward and feedback controller design for nuclear steam generators over wide range operation using genetic algorithm
Author :
Zhao, Yangping ; Edwards, Robert M. ; Lee, Kwang Y.
Author_Institution :
Dept. of Nucl. Eng., Pennsylvania State Univ., University Park, PA, USA
fDate :
3/1/1997 12:00:00 AM
Abstract :
In this paper, a simplified model with a lower order is first developed for a nuclear steam generator system and verified against realistic environments. Based on this simplified model, a hybrid multi-input and multi-out (MIMO) control system, consisting of feedforward control (FFC) and feedback control (PEC), is designed for wide range conditions by using the genetic algorithm (GA) technique. The FFC control, obtained by the GA optimization method, injects an a priori command input into the system to achieve an optimal performance for the designed system, while the GA-based FBC control provides the necessary compensation for any disturbances or uncertainties in a real steam generator. The FBC control is an optimal design of a PI-based control system which would be more acceptable for industrial practices and nuclear power plant control system upgrades. The designed hybrid MIMO FFC/FBC control system is first applied to the simplified model and then to a more complicated model with a higher order which is used as a substitute of the real system to test the efficacy of the designed control system. Results from computer simulations show that the designed GA-based hybrid MIMO FFC/FBC control can achieve good responses and robust performances. Hence, it can be considered as a viable alternative to the current control system upgrades
Keywords :
MIMO systems; control system analysis computing; control system synthesis; feedback; feedforward; fission reactor theory; genetic algorithms; nuclear engineering computing; nuclear power stations; nuclear reactor steam generators; optimal control; power engineering computing; robust control; two-term control; MIMO control system; a priori command input; computer simulation; control design; control response; control simulation; disturbance compensation; genetic algorithm technique; hybrid feedforward/feedback controller design; nuclear power plant control system upgrades; nuclear steam generators; robust performance; uncertainty compensation; Adaptive control; Algorithm design and analysis; Control system synthesis; Control systems; Feedback control; Genetic algorithms; MIMO; Nuclear power generation; Optimal control; Power system modeling;
Journal_Title :
Energy Conversion, IEEE Transactions on