Distributed Prescribed Performance Control for Strict-Feedback Multi-Agent Systems with Input Constraints

In this paper, we consider the consensus control problem of multi-agent systems with dynamics in unknown strict-feedback form subject to input constraints. We propose a novel distributed prescribed performance control scheme which ensures that each agent’s output converges to the leader’s trajectory with predefined transient and steady-state performance while respecting input saturation limits. We introduce a distributed reference modification mechanism that adjusts local consensus errors in response to local control input saturation, preventing internal instability. Rigorous theoretical analysis establishes the stability and convergence properties of the proposed distributed control scheme and guarantees the boundedness of all closed-loop signals. Simulation results involving nonlinear agents demonstrate the effectiveness of the proposed method.