Quantized output‐feedback event‐triggered distributed control of switched fractional multi‐agent systems subject to input nonlinearities and consensus error constraints

Abstract

In this paper, an adaptive quantized output feedback event‐triggered (ET) distributed consensus control approach for an uncertain nonstrict nonlinear switched fractional‐order (FO) multi‐agent system (SFOMAS) subject to communication limitation is proposed. By relying on the common Lyapunov function method, the switch signals are arbitrarily, and no information regarding the switching instants is required. The consensus error of each agent has its own asymmetric time‐varying constraints (ATCs). By adopting the common barrier Lyapunov function (BLF), violation of these constraints is prevented. For each agent, different input nonlinearities can be considered in different modes, and the controllers need no information about their types and characteristics. The communication burden between outputs sensors and the controllers is reduced by applying uniform‐logarithmic‐hysteresis quantizers to the outputs signals. By using FO filters, which can be considered as a FO version of the dynamic surface control (DSC) method, the so‐called explosion of complexity is avoided and the discontinuity problem of FO derivatives of virtual controllers due to outputs quantization is resolved. Observers are designed to estimate the unmeasured states. Also, function approximators (FAs) are employed to approximate uncertainties. A novel lemma that correlates observer states to consensus errors and their constraints, FO filters errors, adaptive parameters and backstepping error surfaces, has been proposed to establish the observer stability. To reduce the communication burden between the controllers and actuators, relative threshold ET mechanisms have been applied to control signals. The combination problem of unmeasured states with the mentioned input constraints for SFOMASs is coped with another novel lemma. Utilizing the common Lyapunov functions (CLFs) and the backstepping technique, virtual controllers, adaptive law and control signal for each agent have been designed and boundedness of closed‐loop signals and avoidance of Zeno behavior have been proved. The effectiveness of the proposed control scheme is demonstrated through a simulation study.