基于SPSA的蒸汽发生器液位MPC系统性能优化方法研究

核电厂蒸汽发生器（SG）液位变化过程具有强非线性且存在“虚假水位”现象，传统SG液位控制系统多采用固定参数比例-积分-微分（PID）控制器，但传统PID控制方法不具备自优化、自适应、自学习等能力，使得控制系统性能难以达到并保持最佳。为提高机组瞬态响应能力以及核电厂的稳定性、安全性和经济性，提出了一种基于并行摄动随机逼近（SPSA）算法的模型预测控制（MPC）方法。该方法采用MPC系统代替传统PID控制系统，并利用SPSA实现液位控制系统参数的整定优化，从而实现SG液位控制系统的性能优化。通过仿真试验验证了本方法能够有效提高SG液位控制参数的整定效率以及控制系统稳定性。 

SPSA-based Performance Optimization Method for Steam Generator MPC System

The level change process of steam generator (SG) in nuclear power plant has strong nonlinearity and the phenomenon of "false water level" exists. Traditional SG level control systems mostly use fixed-parameter proportional-integral-derivative (PID) controllers, but traditional PID control methods do not have the capabilities of self-optimization, self-adaptation, and self-learning, making it difficult to achieve and maintain optimal control system performance. In order to improve the transient response ability of the unit and the stability, safety and economy of the nuclear power plant, a model predictive control (MPC) strategy based on simultaneous perturbation stochastic approximation (SPSA) algorithm is proposed. In this method, MPC system is used to replace the traditional PID control system, and SPSA is used to optimize and set the parameters of the level control system, so as to optimize the performance of the SG level control system. The simulation results show that this method can effectively improve the setting efficiency of SG level control parameters and the stability of the control system.