A modified kernel Hebbian algorithm (MKHA) was proposed to integrate with the kernel principal component regression (KPCR) method for recursive product quality modeling of a two-stage hydro-dearomatization process.The approach to calculating the eigenvalues of centering kernel matrix was derived and the whole algorithm is formulated in a recursive mode.The proposed modeling strategy has an advantage of no need to calculate and store the kernel matrix.The obtained recursive nonlinear dynamic flash point model showed satisfying precision under both normal and faulty operations

and comparison studies with traditional offline KPCR modeling were presented.