Adaptive Robust Kalman Filtering Based Predictive Control Method of Outlet Molten Salt Temperature of Receiver

SHAO Min; YANG Xiaolei; CAO Zhi; CHEN Zhiqiang; LU Junyang; ZHANG Quanrui; LI Yiguo

doi:10.19805/j.cnki.jcspe.2026.250108

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Adaptive Robust Kalman Filtering Based Predictive Control Method of Outlet Molten Salt Temperature of Receiver

更新时间：2026-07-16

- Adaptive Robust Kalman Filtering Based Predictive Control Method of Outlet Molten Salt Temperature of Receiver
- Chinese Journal of Power Engineering Vol. 46, Issue 7, Pages: 96-103(2026)
- 作者机构：
  
  1. 山东电力工程咨询院有限公司,山东,济南,250013
  2. 东南大学能源与环境学院,江苏,南京,210096
- 作者简介：
- 基金信息：
- DOI：10.19805/j.cnki.jcspe.2026.250108
  CLC： TK513;TP273
- Published：2026
- 稿件说明：
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邵旻, 杨晓雷, 曹植, 陈志强, 陆骏阳, 张权锐, 李益国. 基于自适应鲁棒Kalman滤波的吸热器出口熔盐温度预测控制方法[J]. 动力工程学报, 2026, 46(7): 96-103.
邵旻, 杨晓雷, 曹植, 陈志强, 陆骏阳, 张权锐, 李益国. 基于自适应鲁棒Kalman滤波的吸热器出口熔盐温度预测控制方法[J]. 动力工程学报, 2026, 46(7): 96-103. DOI： 10.19805/j.cnki.jcspe.2026.250108.

DOI： 10.19805/j.cnki.jcspe.2026.250108

摘要

针对塔式光热发电系统的吸热器出口熔盐温度因大迟延、非线性特性而难以通过常规比例积分微分(PID)控制算法取得满意控制效果的工程问题

提出了一种基于自适应鲁棒Kalman滤波的吸热器出口熔盐温度预测控制方法。该方法通过引入模型误差容限

并自适应更新测量噪声协方差矩阵

处理预测模型与实际对象的失配问题

从而提高控制系统的鲁棒性。针对太阳辐射量大范围扰动的仿真结果表明

所提方法的超调量相较于基于鲁棒Kalman滤波的预测控制、基于标准Kalman滤波的预测控制及动态矩阵控制(DMC)分别降低了2.45、4.74和12.43 K

对应下降幅度依次为7.37%、12.48%与27.21%。在各类扰动工况下

所提方法均展现出更优的动态偏差抑制效果与更快的调节速度

充分验证了自适应鲁棒Kalman滤波策略应对大迟延、非线性对象模型失配问题的有效性。

Abstract

For the engineering problem where satisfactory control of the outlet molten salt temperature of the receiver in a tower solar thermal power system is difficult to achieve with using conventional proportional integral derivative (PID) control algorithms due to large time delay and nonlinear characteristics

a predictive control method for the outlet molten salt temperature of the receiver based on adaptive robust Kalman filtering was proposed. In this method

the mismatch between the prediction model and the actual object was addressed by introducing a model error tolerance bound and adaptively updating the measurement noise covariance matrix

thus enhancing the robustness of the control system. Simulation results under large-magnitude solar radiation disturbances show that

compared with predictive control based on robust Kalman filtering

predictive control based on standard Kalman filtering

and dynamic matrix control (DMC)

the overshoot of the proposed method is reduced by 2.45

4.74

and 12.43 K

respectively

with corresponding reduction percentages of 7.37%

12.48%

and 27.21%. Under various disturbance conditions

the proposed method is demonstrated to exhibit superior dynamic deviation suppression and faster adjustment speed

fully validating the effectiveness of the adaptive robust Kalman filtering strategy in addressing the large time delay and model mismatch problems of nonlinear objects.

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references

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