The distributed propulsion configuration (DPC) is a new aircraft design concept proposed for the future and the design causes the tight coupling between aerodynamics, flight and propulsion system and creates the redundancy of control input. Therefore, an integrated optimal control that can improve flight performance is required. In this paper, particle swarm optimization (PSO) based on Gaussian Process Regression (GPR) (GPR-PSO) is proposed to solve the optimization control problem. GPR has obvious advantages in small sample, high dimensional, and non-linear modeling problems. GPR is used to model L/D and control inputs based on sample data. PSO is a global optimization method with high accuracy and fast speed. The model given by GPR is used as the objective function for PSO to search for the optimal solution in the feasible region, and a control allocation strategy can be determined based on the optimization result. Simulation results of example and flight/propulsion integrated optimization control show that GPR-PSO leads better accuracy compared to PSO based on piecewise linear interpolation and their convergence speed is similar.
Integrated Flight/Propulsion Optimal Control for DPC Aircraft Based on GPR-PSO
Lect. Notes Electrical Eng.
2021-10-30
11 pages
Article/Chapter (Book)
Electronic Resource
English
Integrated Flight/Propulsion Optimal Control for DPC Aircraft Based on GPR-PSO
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