Fuzzy Sliding Mode Control of Multi-Agent Systems Using Artificial Potentials

In this paper a fuzzy control strategy of autonomous multi-agent systems is presented. The main purpose is to obtain an improvement on the results of designed sliding mode controllers in previous articles using supervisory fuzzy controller. Similarly, a quasi-static swarm model in n-dimensional space is introduced wherein the inter-individual interactions are based on artificial potential functions; and the motions of members are in direction with the negative gradient of the combined potentials which are the result of a balance between inter-individual interactions and the simultaneous interactions of the swarm members with their environment. Then a general model for vehicle dynamics of each agent has been studied. The aim is to reach the desirable formation of swarm by forcing agent’s motion to follow the quasi-static model. In literature a sliding mode controller is used to perform this task. In this work, same control structure is applied with a difference in control parameters. In this paper, fuzzy rules are introduced for some major control parameters which are efficacious on the results in order to get better performances along with less error during the formation control approach.