Optimization of aircraft flight control system based on an improved MOPSO algorithm

With regard to the disadvantage of the basic particle swarm optimization algorithm trapped into the local optimal easily, an improved multi-objective particle swarm optimization (MOPSO) is proposed. Firstly, a method of initial population assignment which based on the uniform design is adopted. And it could make the initial population distribute as evenly as possible in the whole decision space. Secondly, the improved generation distance index is used as the judging condition when the algorithm trapped into the local optimal, and the chaos mutation operator is adopted to jump out the local optimal. Additionally, a new adaptive inertia weight is used to maintain diversity of population. Finally, the improved algorithm is applied to design the longitudinal control system of a certain type of aircraft. The results of the numerical simulation show the effectiveness of the improved algorithm.