Fixed-time containment control for stochastic multi-agent systems with state constraints

This paper addresses the fixed-time containment control issue of stochastic $p$-normal nonlinear multi-agent systems with input saturation and state constraints via event-triggered strategy. The uncertain dynamics of the systems are parameterized by fuzzy logic systems. Two nonlinear transformation functions are introduced to handle the state constraint issue. To deal with the input saturation, the saturation degree function is introduced. In multi-agent networks with limited communication resources, event-triggered distributed mechanisms for each agent are designed, in which the threshold parameters are adjustable according to the tracking performance. An adaptive fuzzy containment control scheme is proposed such that the multi-agent system is practically fixed-time stability in probability. Finally, the theoretical results are validated by computer simulation.