Consensus in multi-agent networked system using adaptive neuro-fuzzy inference system

This paper, provides a new control scheme, to solve consensus problem in multi agent networked system. This controller design is based on adaptive neuro-fuzzy inference system. Because of changing network topology in wireless sensory networks and existence of noise in harsh industrial environments, it is important to use robust controller to tolerate these conditions. Fast convergence and less sensitivity to model uncertainties are the main benefits of our controller. Simulation results shows flexibility of this controller can decrease effects of noise and disturbance and improve the performance of networked system.