Adaptive Predefined-Time Bounded Consensus Tracking Control of Multiagent Systems Under Input/Output Quantization
Tao Jiang, Yan Yan, Shuzhi Sam Ge · IEEE Transactions on Systems Man and Cybernetics Systems · 2025
This article addresses the velocity-free predefined-time consensus tracking for multiagent systems (MASs) with input and output quantization via adaptive sliding mode control (SMC). First, a distributed predefined-time state observer is introduced to estimate the unmeasurable states. Therein, only the quantized position information is used, and the observation errors are ensured to be predefined-time bounded (PTB). Second, a class-${\mathcal {K}}_{\infty }$function is employed as the adaptive gain in the SMC to diminish the dependence on prior knowledge of lumped uncertainties and quantization parameters. Subsequently, a novel SMC-based quantized consensus tracking protocol is designed using time-varying functions to achieve the predefined-time consensus tracking of MASs. Specifically, with the proposed protocol, the consensus tracking errors are guaranteed to be PTB under input and output quantization. Finally, simulations are employed to validate the performance of the proposed protocol.