Fixed-Time Distributed Time-Varying Optimization for Nonlinear Fractional-Order Multiagent Systems with Unbalanced Digraphs - Kun Wang; Ping Gong; Zhiyao Ma (Fractal and Fractional, 2023)
This paper investigates the problem of fixed-time distributed time-varying optimization of a nonlinear fractional-order multiagent system (FOMAS) over a weight-unbalanced directed graph (digraph), where the heterogeneous unknown nonlinear functions and disturbances are involved. The aim is to cooperatively minimize a convex time-varying global cost function produced by a sum of time-varying local cost functions within a fixed time, where each time-varying local cost function does not have to be convex. Using a three-step design procedure, a fully distributed fixed-time optimization algorithm is constructed to achieve the objective. The first step is to design a fully distributed fixed-time estimator to estimate some centralized optimization terms within a fixed time <semantics>T0</semantics>. The second step is to develop a novel discontinuous fixed-time sliding mode algorithm with nominal controller to derive all the agents to the sliding-mode surface within a fixed time <semantics>T1</semantics>, and meanwhile the dynamics of each agent is described by a single-integrator MAS with nominal controller. In the third step, a novel estimator-based fully distributed fixed-time nominal controller for the single-integrator MAS is presented to guarantee all agents reach consensus within a fixed time <semantics>T2</semantics>, and afterwards minimize the convex time-varying global cost function within a fixed time <semantics>T3</semantics>. The upper bound of each fixed time <semantics>Tm<mspace width="3.33333pt"></mspace>(m=0,1,2,3)</semantics> is given explicitly, which is independent of the initial states. Finally, a numerical example is provided to validate the results.