Finite‐time adaptive output synchronization of uncertain nonlinear heterogeneous multi‐agent systems

Abstract

This article deals with finite‐time adaptive output synchronization of heterogeneous leader‐follower multi‐agent systems with uncertain dynamics. Two types of uncertainties are considered: 1) uncertainty in the dynamics of follower agents and 2) uncertainty in the leader's trajectory caused by unknown leader dynamics. To this aim, a novel adaptive distributed finite‐time observer is first proposed by which the followers can estimate the leader's state and dynamics in finite time. Moreover, the leader's unknown output matrix is estimated in finite time by another distributed dynamic observer. To cope with uncertainty in its own dynamics, then, each follower agent utilizes a novel filtered‐regressor‐based identifier, decoupled from the leader's state estimator, to learn about its uncertain dynamics without the requirement of measuring the state derivatives. Finally, the presented distributed finite‐time observers are leveraged by an adaptive distributed controller to guarantee finite‐time output synchronization of each follower agent to the leader. To show the efficiency of the proposed approach, a simulation example is provided.

Design and Analysis of a Novel Distributed Gradient Neural Network for Solving Consensus Problems in a Predefined Time

“…In this section, we will describe the concept of consensus and its tools: graph theory [34], as well as the GNN framework [30].…”

“…This subsection explains the basis of graph theory involved in this paper [34]. The directed graph network of the system with n linked nodes is expressed as follows:…”

Finite‐time disturbance rejection for nonlinear systems using an adaptive disturbance observer based on experience‐replay

“…For example, in rotating systems, the disturbance source often consists of many periodic components with unknown frequencies (e.g., engine noise in automobile and aircraft). Modeling the disturbance with exosystem dynamics is a standard practice and has been widely considered by many researchers 5‐9 …”

“…Modeling the disturbance with exosystem dynamics is a standard practice and has been widely considered by many researchers. [5][6][7][8][9] For the disturbance cancellation, the most common approach is the internal model principle 9,10 under which the disturbance dynamics are incorporated into the controller design. A related problem is the output regulation 11 for which the system is supposed to track a reference trajectory and/or reject a disturbance with known exosystem dynamics.…”