發(fā)布時間：2018-10-05 09:22

【摘要】：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.
[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.
【作者單位】： School
【基金】：partially supported by the National Natural Science Foundation of China(51667013)
【分類號】：TM615;TP273

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本文編號：2252849