Abstract:

An improved multi-objective particle swarm optimization algorithm is proposed and applied to the integrated optimization of environmental control system and engine of aircraft. A multi-objective optimization model is established by viewing the total entropy generation minimum at different flight phases as different objectives. Based on the basic multi-objective particle swarm optimization algorithm, an improved algorithm is proposed through a jump and cluster operation, and a new global optimal position distribution method. The simulation results show the good performance of the algorithm. The proposed algorithm is used to compute the multi-objective optimization model, the obtained pareto optimal set has good convergence and diversity. It provide a new way for integrated optimization of aircraft systems.

Key words:  multi-objective optimization, environmental control system, engine system, particle swarm optimization, pareto optimal set