Application of NMEC-based parameter optimization in main steam temperature control system

Niche technology was introduced in mind evolutionary computation to classify populations, reduce repetitive search and maintain population diversity as well as improve searching efficiency. Based on parameter optimization and tuning for the main steam temperature cascade control systems in power pla...

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Bibliographic Details
Main Authors: Liu QingSong, Yue Jingpin
Format: Conference Proceeding
Language:English
Subjects:
cascade control systems
Computational complexity
Computational modeling
Control system synthesis
Delay effects
Evolutionary computation
mind evolutionary computation
Niche
parameter optimization
Power generation
Robust control
Temperature control
Three-term control
Uncertain systems
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Summary:Niche technology was introduced in mind evolutionary computation to classify populations, reduce repetitive search and maintain population diversity as well as improve searching efficiency. Based on parameter optimization and tuning for the main steam temperature cascade control systems in power plants with serious parameter uncertainty, multi-disturbance and large delay, the simulation results show that the niche-based mind evolutionary algorithm has the advantages of fast optimization and low computational complexity; it is very effective for PID parameter optimization and endues main steam temperature control systems with better control qualities and better system robustness.
DOI:10.1109/ICICISYS.2009.5358355