Consensus Control for Discrete-Time Stochastic Multiagent Systems Under a Multiple Description Coding Mechanism

This article addresses the consensus control problem for a specific class of discrete-time stochastic multiagent systems (MASs). When transmitting the local measurement output to the local controller and neighboring agents, a multiple description coding (MDC) scheme is introduced to reduce the communication burden and enhance data transmission reliability in a resource-constrained environment. The MDC scheme encodes each signal into two descriptions, which are then transmitted through separate channels, and decoding schemes are employed to address the different characteristics of the arrival of the two descriptions, ensuring the boundedness of the decoding error. The proposed consensus control scheme uses the relative decoded measurement errors between local agents and their neighbors. The aim is to design an output-feedback control scheme that ensures the error dynamics of the controlled MAS reach exponentially mean-square boundedness. Sufficient conditions are established for the existence of the controllers through stochastic analysis techniques, and the desired controller gains are parameterized using the feasibility of certain matrix inequalities. The effectiveness of the proposed coding-decoding-based consensus control scheme is verified through a numerical simulation.