An improved hybrid backtracking search algorithm based T–S fuzzy model and its implementation to hydroelectric generating units.

In order to realize the automatic selection of rule number in fuzzy space partition in the identification of the Takagi–Sugeno (T–S) fuzzy model, a new fuzzy clustering method is proposed in this paper. With the purpose of searching for the optimal fuzzy cluster number and the corresponding cluster centers simultaneously, a novel improved hybrid backtracking search algorithm (IHBSA) has been proposed by introducing the idea of a hybrid encoding scheme as well as a variable valid length chromosome to this optimization algorithm. With a proper cluster validity index taken as the objective function, IHBSA is capable of partitioning the fuzzy space and identifying premise parameters of the T–S fuzzy model without setting a deterministic value of cluster number as a priori. Through the experimental analysis, it is demonstrated that the proposed method possesses higher approximation accuracy with relatively fewer rule number in comparison with traditional ones. Moreover, the T–S fuzzy model is implemented to the practical data of hydroelectric generating units (HGU), and preponderant trajectory matching performance has also been achieved when utilizing the proposed method. [ABSTRACT FROM AUTHOR]