A Heuristic T-S Fuzzy Model for the Pumped-Storage Generator-Motor Using Variable-Length Tree-Seed Algorithm-Based Competitive Agglomeration

A Heuristic T-S Fuzzy Model for the Pumped-Storage Generator-Motor Using Variable-Length Tree-Seed Algorithm-Based Competitive Agglomeration

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With the fast development of artificial intelligence techniques, data-driven modeling approaches are becoming hotspots in both academic research and engineering practice.This paper proposes a novel data-driven T-S fuzzy model to precisely describe the complicated dynamic behaviors of pumped storage generator motor (PSGM).In premise fuzzy partition of the proposed argan oil pure purple T-S fuzzy model, a novel variable-length tree-seed algorithm based competitive agglomeration (VTSA-CA) algorithm is presented to determine the optimal number of clusters automatically and improve the fuzzy clustering performances.

Besides, in order turbo air m3f24-1-n to promote modeling accuracy of PSGM, the input and output formats in the T-S fuzzy model are selected by an economical parameter controlled auto-regressive (CAR) model derived from a high-order transfer function of PSGM considering the distributed components in the water diversion system of the power plant.The effectiveness and superiority of the T-S fuzzy model for PSGM under different working conditions are validated by performing comparative studies with both practical data and the conventional mechanistic model.