Fixed-time resource allocation algorithm for high-order MIMO nonlinear multi-agent systems

Abstract

This article develops a distributed nonsingular fixed-time algorithm for the resource allocation problem of high-order multiple-input multiple-output (MIMO) nonlinear multi-agent systems (MASs). Different from well-known resource allocation issues, our research considers the inequality constraint and high-order dynamics of systems. In order to make the MASs fixed-time stable while the optimization problem converge to the optimal solution within fixed time, we design the optimization protocol leveraging the integral type Lyapunov function and fractional power nonlinear filter. What’s more, we construct the distributed estimators to estimate the gradient information of other agents instead of directly using it. This protocol ensures that all the signals remain semi-global practical fixed-time stable (SGPFTS), and concurrently, all the agents’ outputs converge to the neighborhood of optimal solutions of the global objective function. Finally, the validity of the theoretical results is verified by a simulation.