Abstract
Steam generator is a major component in a nuclear power plant (NPP). Properly controlling the water level of it is very important to guarantee the security of a NPP. In this paper, aimed at the shortcomings of steam generator water level system with time-variation and complex nonlinearity, the precision of traditional control method was low and the adaptive capacity was poor, a novel dynamic fuzzy neural network (DFNN) was put forward. It gave full play to the advantage of PID control and increased the abilities of self-learning and deal with quantitative data by combining fuzzy neural network with PID. For the key issue of how to confirm the fuzzy rules and the network structure, it dynamically constructed the fuzzy neural system online based on the sampling data through the DFNN algorithm. Then the fuzzy neural PID controller was designed to control the water level. The simulations show that it performs wonderfully in anti-jamming, fast and steadily responding, rapid convergence and small static error. The self-adaptation and robustness of these systems are good.
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Hong, J., Xia, H. (2017). Nuclear Steam Generator Water Level Control Based on DFNN. In: Jiang, H. (eds) Proceedings of The 20th Pacific Basin Nuclear Conference. PBNC 2016. Springer, Singapore. https://doi.org/10.1007/978-981-10-2317-0_15
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DOI: https://doi.org/10.1007/978-981-10-2317-0_15
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