Improved BES Algorithm for Steady-State Optimal Control of Propfan Engine

In view of the unique structure and complex control variables of the propfan engine, this paper introduces the bald eagle search algorithm for the performance optimization control of the propfan engine. An adaptive weight bald eagle search algorithm based on simulated annealing and chaotic mapping is proposed to perform performance optimization control under maximum thrust mode, minimum fuel consumption mode, and minimum turbine inlet temperature mode. To overcome the shortcomings of the standard bald eagle search (BES) algorithm, an improved BES algorithm is presented by analyzing the principles of the standard BES algorithm. The improved algorithm analyze the principles of chaos mapping, dynamic adaptive weighting, and simulated annealing, and simulation results are compared between the improved and standard BES algorithms. The simulation results show that in the steady-state performance optimization control of the propfan engine, the proposed algorithm has the same calculation and optimization control results as the standard vulture search algorithm, but the calculation efficiency is increased by about 50%.