Multi-objective Optimization Of Aeroengine Control Based On Multi-Objective Genetic Algorithms

Multi-objective evolutionary algorithm (MOEA) is a new powerful tool for Multi-objective optimization. It is being rapidly developed in recent years. Because of its high efficiency and practicability, MOEA attaches more and more importance to the academe. The purpose of this dissertation is to study the issue of multi-objective optimization, the basic theory, typical algorithms, and its applications to multi-objective optimization of aeroengine control systems of MOEA are fully studied.The development and significance of MOEA are introduced at the beginning.Chapter 2 gives a full-scale study and analyses about MOEA. On the basis of analyses the basic principles and operations of genetic algorithm, the principles and operations of MOEA are presented, then emphasis is given on analyses of four typical MOEAs.At the end of this chapter, the excellent performance of MOEA is demonstrated in two succedent examples about multi-objective optimization.In chapter 3, the PID controller parameters of an aeroengine model is optimized by MOEA NSGA-II .The simulation results indicate that the speed control system shows good dynamic and steady performance in many operation points, the result is satisfactory.In chapter 4, MOEA is proposed as a solution to the multi-objective optimization problem in Integrated Flight/Propulsion Control (IFPC). The objectives of the IFPC modes are optimized by NSGA-II at the same time. The final result indicates good control performance in many operation points, the result is satisfactory.