Robustification of cooperative consensus algorithms in perturbed multi-agents systems

In this chapter we show how the Integral Sliding-Mode Control design paradigm can be usefully applied in the framework of Multi-Agent Systems to allow the agents dynamics to be affected by unknown disturbances. Existing consensus-based algorithms for the distributed estimation of pre-specified quantities such as, e.g., the average or the median value of the agents initial conditions fail to converge when disturbances affect the agents dynamics. In the present chapter, is discussed how to redesign the original “non-robust” algorithms from an integral sliding mode perspective, such that restoration on the ideal unperturbed scenario (e.g., convergence to the average or median value) is guaranteed in spite of the unknown perturbations. The theoretical results are fully derived within a Lyapunov analysis approach. Finally, to corroborate the developed approaches, simulative results are also presented and discussed.