Non-singular fixed-time consensus tracking of high-order multi-agent systems with unmatched uncertainties and practical state constraints

In this study, a fixed-time consensus-tracking problem of an uncertain nonlinear multi-agent system with practical state constraints that can be fully or partially constrained is considered. A novel unified transformation is proposed to address practical state constraints. Based on the proposed transformation function, a distributed fixed-time observer is designed for the followers to approximate the transformation of a leader's output. Furthermore, we apply an adaptive neural network technique and add a power integrator technique to design a nonsingular fixed-time controller that ensures practical fixed-time consensus tracking and satisfies state constraints. Finally, simulations are performed to verify the theoretical results.