Ant search based control optimisation strategy for a class of chaotic system

In this paper the authors propose a logistic mapping using chaotic model to describe the time-variable pest population. Two kinds of fuzzy rule embedded control strategies are investigated, three segment control and five segment control. They are designed to reduce the pest population. The simulation results show that the objective function is non-convex and anomalous along the control parameters. To find the optimal parameter combinations we develop an ant search approach. By imitating the food hunting and nest moving behaviours of Pachycondyla apicalis ants, this method can adaptively and effectively explore solution areas and arrive at the optimal solution. When we compared the performance curves with the one without control strategy, the method is better and can be used for a wide range of pest control problems in real life.