Research on Pressurizer Pressure Control Based on Adaptive Prediction Algorithm

Hong Qian, Yuan Yuan, Yu Wang, Gaofeng Jiang and Ting Yang

Complexity, 2019, vol. 2019, 1-10

Abstract:

According to the high control quality requirements of nuclear power plants and the features of the pressurizer pressure with large inertia, time-varying, nonlinear, multi-interference, difficulty in obtaining accurate mathematical model, and open-loop unstable dynamic characteristic, the advanced control strategy is needed for pressurizer pressure control performance optimization. To tackle the problem, an adaptive predictive control method for pressurizer pressure is devised in this paper. Firstly, the non-self-regulating system is stabilized and the adaptive dynamic matrix controller is designed by identifying the controlled object online. In order to realize the engineering application for this controller, then the control signal output is obtained. Finally, the control system simulation platform is built. Simulation results reveal a superior control performance, disturbance rejection, and adaptability. Furthermore, it provides a solution for the application of dynamic matrix control algorithm in non-self-regulating system.

Date: 2019
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Persistent link: https://EconPapers.repec.org/RePEc:hin:complx:2470376

DOI: 10.1155/2019/2470376

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