Non-Singular Practical Fixed-time Prescribed Performance Adaptive Fuzzy Consensus Control for Multi-Agent Systems Based on an Observer

In this paper, the problem of non-singular fixed-time control with prescribed performance is studied for multi-agent systems characterized by uncertain states, nonlinearities, and nonstrict feedback. To mitigate the nonlinearity, a fuzzy logic algorithm is applied to approximate the intrinsic dynamics of the system. Furthermore, a fuzzy logic system state observer based on leader state information is designed to address the partial unob-servability of followers. Subsequently, the power integral method is incorporated into the backstepping approach to avoid singularities in the fixed-time controller. A command filter method is introduced into the standard backstepping approach to reduce the computational complexity of controller design. Then, a non-singular fixed-time adaptive control strategy with prescribed performance is proposed by constraining the tracking error within a prescribed range. Rigorous theoretical analysis ensures the convergence of consensus error in the multi-agent system to the prescribed performance region within a fixed time. Finally, the practicality of the algorithm is validated through numerical simulations.