Application of Multi-model Active Fault-tolerant Sliding Mode Predictive Control in Solar Thermal Power Generation System
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摘要: 针对太阳能热发电系统的随机性和干扰性强的特点,以解决太阳能热发电的平稳性问题,本文设计了多模型主动容错滑模预测控制器.对实测的数据进行模糊聚类,再用递推最小二乘法建立集热子系统的多模型;采用基于累计误差最小的切换策略在线选择最优控制模型;为降低在建立多模型的过程中数据的缺失、故障和强扰动引起的误差,建立太阳能集热系统的自适应预测模型;设计主动容错滑模预测控制器提高输出的跟踪精度和鲁棒性;最后,验证该算法应用的有效性和优势.Abstract: To address the stability of solar thermal power generation system which is characterized by the presence of random and strong disturbance, a multi-model active fault-tolerant controller is designed in this paper. Actually measured data is used to make fuzzy clustering, then multi-model of the collector subsystem is established through recursive least square method. A switching strategy based on the minimum cumulative error is applied to select the optimal control model online. In order to reduce the error caused by missing data, fault and strong disturbance in the process of building the multi-model, the adaptive prediction model of solar collector system is established. Active fault tolerant sliding mode predictive controller is designed to improve the tracking accuracy and robustness of the output. Finally, the validity and advantage of the proposed algorithm are verified.
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Key words:
- Active fault-tolerant control /
- adaptive switching /
- fuzzy clustering /
- multi-model /
- solar thermal power generation
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Fig. 5 Control efiect of [3].
Fig. 6 Tracking error of [3].
Fig. 7 Oil flow of [3].
Table Ⅰ Clustering Results
C 2 3 4 5 6 7 8 9 DB 1.3893 1.0168 0.6306 0.7065 0.1746 0.9135 0.4936 0.6304 -
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