Distributed Intelligent Adaptive Controller for Disturbance Rejection in Multiagent Systems

A cooperative task consisting of multiple agents has the advantages of reducing cost, enhancing configurability, and increasing robustness in a large set of mission applications. A distributed strategy, applied using intelligence and adaptability characteristics, can provide the extended potential to achieve high levels of mission protection, especially under disturbances that might lead to operation degradation. This paper describes the design and development of a novel bioinspired distributed adaptive control architecture designed to increase the resilience of multiagent systems. The architecture is formulated using nonlinear bounded functions that characterize the immune system responses of living organisms. Numerical simulations are performed to evaluate the capabilities of this architecture to solve a consensus problem under bounded disturbances. Stability analysis is presented using the Lyapunov direct method to estimate the radius of convergence of the global tracking error under a time-varying disturbance. The proposed distributed controller successfully ensures that consensus is achieved among all agents while simultaneously mitigating the effect of disturbances.