An Improved Fruit Fly Optimization Algorithm and Its Application of PID Parameters Tuning

摘要

In the application process, the Fruit Fly Optimization Algorithm (FOA) is depending on a simple group behavior, and it ignores the individual behavior, which has aggravated the complexity of the optimization process. Thus, we put forward the Improved Fruit Fly Optimization Algorithm (IFOA) by adding the inertia weight which changes of the nonlinear decreasing and the behavior of the relationship between individual and group. The Shuffled Frog Leaping Algorithm is introduced in the paper and it has been together with IFOA. The purpose is avoiding local optimum and enhancing the ability of searching for the global optimum. IFOA is applicable to the tuning of PID controller. Finally, it concludes that our algorithm can balance the local and global optimization ability to the performance of the PID controller to achieve the better outcome by comparing with FOA.