Abstract
This paper deals with the asymptotic consensus problem for a class of multiagent systems with time-varying additive actuator faults and perturbed communications. TheL2performance of systems is also considered in the consensus controller designs. The upper and lower bounds of faults and perturbations in actuators and communications and controller gains are assumed to be unknown but can be estimated by designing some indirect adaptive laws. Based on the information from the adaptive estimation mechanism, the distributed robust adaptive sliding mode controllers are constructed to automatically compensate for the effects of faults and perturbations and to achieve any given level ofL2gain attenuation from external disturbance to consensus errors. Through Lyapunov functions and adaptive schemes, the asymptotic consensus of resulting adaptive multiagent system can be achieved with a specified performance criterion in the presence of perturbed communications and actuators. The effectiveness of the proposed design is illustrated via a decoupled longitudinal model of F-18 aircraft.
Highlights
The consensus behavior of multiagent systems has received significant attention over the last few years
We develop the adaptive laws to estimate unknown controller gains for designing robust adaptive sliding mode controllers to eliminate the effects of communication perturbations and actuator faults and, simultaneously, to achieve any given L2 performance criterion of the closedloop system (12)
We have shown an adaptive design method to solve the robust asymptotic consensus problem for a class of multiagent systems with perturbed communications and faulted actuators
Summary
The consensus behavior of multiagent systems has received significant attention over the last few years. It involves in lots of practical control systems and many physical phenomenon, such as synchronization of coupled oscillators [1], rendezvous in space [2], aircraft formation control [3], and flocking theory [4]. Lots of researchers have focused on the development of methodologies to solve consensus problem with some usual issues existed in communications such as time-delays [5, 6], perturbations [7,8,9,10,11,12,13,14,15], and faulty communication links [16,17,18]. From the Laplacian eigenvalue standpoint, paper [10] focused on maximizing the second smallest eigenvalue of a state-dependent graph
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