Fault-Tolerant Consensus Tracking Control for Linear Multiagent Systems Under Switching Directed Network

In this paper, for linear leader-follower networks with multiple heterogeneous actuator faults, including partial loss of effectiveness fault and actuator bias fault, a cooperative fault-tolerant control (CFTC) approach is developed. Assume that the interaction network topology among all nodes is a switching directed graph. To address the difficulty of designing the distributed compensation control laws under the time-varying asymmetrical network structure, a novel distributed-reference-observer-based fault-tolerant tracking control approach is established, under which the global tracking errors are proved to be asymptotically convergent in the presence of actuator failures. First, by constructing a group of distributed reference observers based on neighborhood state information, all followers can estimate the leader's state trajectories directly. Second, a decentralized adaptive fault-tolerant tracking controller via local estimation is designed to achieve the global synchronization. Furthermore, the reliable coordination problem under switching directed topology with intermittent communications is solved by utilizing the presented CFTC approach. Finally, the effectiveness of the proposed coordination control protocol is illustrated by its applications to a networked aircraft system.

I. Introduction

The coordination problem of multiagent systems (MASs) is inspired by naturally occurring phenomena. In nature, the collective behavior of animal groups (such as flocking of birds, swarming of fishes, etc.) has shown that all individuals can make up a single entity to perform a cluster behavior by means of communications and distributed decisions [1]–[3]. In engineering practice, the cooperative control problem of distributed agent networks has attracted a considerable amount of attention, where distributed subsystems can be applied to perform complex coordination tasks with intergroup cooperation, such as formation coordination of aircrafts/robots, distributed energy resources in microgrids, and so on [4]–[8].