In this paper

a design scheme for thrust estimator was proposed based on K-means clustering and reduced least squares support vector regression. Firstly

the K-means clustering algorithm was utilized to cluster the data in the full flight envelope

and the

a sub-estimator was designed in each cluster using the recursive reduced least squares support vector regression (RRLSSVR). In the process of designing the sub-estimator with RRLSSVR

the Cholesky factorization was utilized to replace the original iteration method for achieving higher numerical stability. Finally

the simulation experiments show that the thrust estimator can satisfy the requirement of direct thrust control for aeroengines

and as compared with other scheme for thrust estimator

the proposed scheme in this paper is also superior.