Analytical Redundancy of Variable Cycle Engine Based on Proper Net considering Multiple Input Variables and the Whole Engine’s Degradation - Zihao Zhang; Xianghua Huang; Tianhong Zhang (International Journal of Aerospace Engineering)
In this paper, Proper net is proposed to construct variable cycle engine’s analytical redundancy, when all control variables and environmental variables change simultaneously, also accompanied with the whole engine’s degradation. In another word, Proper net is proposed to solve a multivariable, strongly nonlinear, dynamic, and time-varying problem. In order to make the topological structure of Proper net physically explainable, Proper net’s topological structure is designed according to physical relationship between variables, by which means analytical redundancy based on Proper net achieves higher accuracy with less calculation time. Experiments were compared with performance of analytical redundancy based on Proper net, seven convolutional neural network topological structures, and five shallow learning methods. Results demonstrate that under condition of average relative error less than 1.5%, Proper net is the most accurate and the least time-consuming one, which proves not only the effectiveness of Proper net but also the feasibility of topological structures’ design method based on physical relationship.