Adaptive ant colony algorithm and its application to parameters optimization of PID controller

Ant colony algorithm (ACA) is a new simulated evolutionary optimization algorithm with the characteristics of positive feedback, distributed computing and strong robustness, but it has the limitations of poor convergence and is easy to fall in local optima. An adaptive ant colony algorithm (AACA) is introduced to improve overall importance of solutions grounded on the basic principles of ACA, and it has been applied to parameters optimization design of PID controller. The simulation results show that it is an effective and feasible algorithm with good performance index.