Output regulation is a general framework, for it not only can achieve closed‐loop stability, but also can realise asymptotic tracking and disturbance rejection. Within this framework, the authors consider the containment problem of heterogeneous linear multi‐agent systems with directed graphs. Via dynamic compensator techniques, the containment problem can be converted into cooperative output regulation problem. Moreover, they artfully construct regulation equations, whose solutions are also given. Adaptive protocols are proposed here by assigning a time‐varying coupling weight to each node. Unlike most existing protocols that depend on certain global information, protocols presented in this paper are independent of any global information, and hence are fully distributed. By combining the compensator technique with adaptive control, they propose the distributed dynamic adaptive state feedback and adaptive output feedback protocols for driving followers into the moving convex hull spanned by leaders. The obtained results are applied to the containment control of a network of heterogeneous agents, where the followers are described by mass‐damper spring systems, and the leaders are specified by harmonic oscillators.

The increasing number of devices and frequent interactions of agents from networked multiagent systems (MASs) exacerbate the risks of potential cyber attacks, especially the different point attacks and multiple pattern attacks. This article considers the output formation-containment problem for MASs under multipoint multipattern false data injection (FDI) attacks. The multipoint describes the attacks simultaneously occurring on the sensors, actuators, and communication channels; the multipattern captures that sensor and actuator attack signals are both continuous deterministic variables, and the communication channel attack signals are intermittent random variables, obeying the Bernoulli distribution. For such compromised MASs, a novel hybrid protocol is proposed, which integrates a state observer, an attack estimator, an impulsive interactor and a compensation controller. Thereinto, the state observer and the attack estimator are constructed to recover the unmeasured system states and the unknown FDI attack signals, respectively; the impulsive interactor is designed to guarantee that the neighbor’s signals are transmitted only at impulsive instants, and meanwhile the channel attacks are randomly launched; using the recovered signals, the compensation controller is devised to alleviate the effect of attacks. A sufficient condition is identified, under which the output formation containment is achieved with cooperative uniform ultimate boundedness (UUB). Finally, simulation results are carried out to validate the effectiveness and advantages of the proposed approach.

Within the framework of multiagent systems, relative information can be directly acquired by vehicle-mounted sensors and the relative information constraints inevitably occur due to limited sensing capabilities. This paper investigates observer-based consensus of nonlinear multiagent systems subject to relative state estimate constraints. Each agent's state is constructed via a state observer, and the relative state estimate is assumed to be confined into a hypercube. In virtue of the edge Laplacian, the consensus problem of nonlinear multiagent systems under this constraint is converted into the stabilization problem of edge dynamics operating on the constrained set. Observer-based intermittent protocol and adaptive protocol are, respectively, designed for achieving consensus. A convergence analysis is provided with the help of state saturation theory, switched system theory and adaptive theory. Finally, the results on consensus with relate state estimate constraints are applied into the consensus problem while preserving the connectedness, and are validated by a simulation example.

This article investigates the consensus tracking of exponentially unstable multiagent systems with time-varying input delay. The truncated predictor feedback approach is utilized for designing delay-dependent state and output feedback protocols. And the explicit conditions that can realize consensus tracking are established in terms of parametric Lyapunov equations and scalar inequalities. Besides, the protocol design algorithms under the maximum allowable delay and the maximum convergence rate are, respectively, provided. Compared with the existing results, the salient characteristic of the current results is to reveal the quantitative relationship among the time delay, unstable plant, network topologies, and the convergence rate. Specifically, for achieving the consensus tracking, the synchronization force from network connectivity needs to dominate the anti-synchronization force from unstable open-loop poles and input delays; the maximum allowable input delay is inversely proportional to the sum of the unstable open-loop poles; the convergence rate becomes smaller as the input delay bounds or/and the sum of the unstable poles in plant increase. Numerical simulations confirm the effectiveness of the proposed theoretical design.

This paper investigates leaderless consensus and leader-following consensus of multiagent systems with Lipschitz nonlinearity and input delay. For such systems, the observer-based truncated prediction feedback protocols are designed via dropping the distributed term and remaining the exponential term of the solution of the system equation over the delay period. Using Lyapunov-Krasovskii functional approach, two sufficient criteria are, respectively, established for achieving leaderless and leader-following consensus. The observer and controller gains are then obtained by means of an iterative linear matrix inequality procedure. A numerical simulation verifies the effectiveness of the proposed control design approach.