Turbo-Shaft Engine Model Compensation Based on LSSVR

Abstract

Considering the larger modeling errors between the turbo-shaft engine and on-board model, the model correction method based on least squares support vector regression is proposed. Firstly, the modeling principle of on-board turbo-shaft engine model is introduced, and then the structure of model combined with a compensation module is designed. The algorithm of LSSVR is used to build up the model compensation module, which is trained off-line and corrected on-line. Simulation studies on turbo-shaft engine have shown that the LS-SVM method can effectively reduce the model errors, and comparison with the interpolation correction, neural network one, the method proposed has better precision.