Supercritical unit fuzzy modeling method combined with improved bald eagle search algorithm

The invention discloses a supercritical unit fuzzy modeling method combined with an improved bald eagle search algorithm to improve the flexibility of a unit. Firstly, dynamic characteristics and modeling difficulties of the supercritical unit coordinated control system are analyzed; and then a novel T-S fuzzy model incremental structure is established, automatic data clustering based on a chaos adaptive bald eagle search algorithm is realized, and then model identification of the supercritical unit is completed through an exponential weighted least square method. Finally, it is verified through a simulation platform that the established supercritical unit model has high precision and adaptability. 本发明公开了一种结合改进秃鹰搜索算法的超临界机组模糊建模方法以提高机组的灵活性。首先，分析超临界机组协调控制系统的动态特性和建模难点；然后建立新型的T-S模糊模型增量结构，实现基于混沌自适应秃鹰搜索算法的数据自动聚类，随后通过指数加权最小二乘法完成超临界机组的模型辨识。最后依托仿真平台验证了本发明所建立的超临界机组模型具有较高的精度和适配性。