Distributed H∞ containment control of multiagent systems over switching topologies with communication time delay

In this study, we consider the problem of distributed H_∞ containment control for multiagent systems over switching communication topologies. There exists a constant time‐delay and the energy‐bounded communication disturbances in the information transmission process, which are considered. Using the relative output, we develop an observer‐based containment control scheme such that the followers asymptotically converge to the convex hull formed by the leaders with a guaranteed H_∞ performance level. By constructing a Lyapunov functional and using the inequality technique, sufficient conditions for the existence of such dynamic controllers are obtained in terms of linear matrix inequalities. Finally, a numerical example is provided to demonstrate the effectiveness of the proposed control protocol.     

Sampled‐data consensus of multiagent systems with switching jointly connected topologies via time‐varying Lyapunov function approach

Consensus problem of multiagent systems with switching jointly connected topologies under sampled‐data control is studied in this article. The main contribution is that the consensus problem for such system is solved without the assumption that the system matrices are stable or critically stable. For this purpose, a time‐varying Lyapunov function method is utilized to describe the state characteristics with switching jointly connected topologies. Based on the time‐varying matrix of Lyapunov function, the “decline” characteristics at the switching instants is derived to compensate the divergence among the agents with disconnected topologies. Utilizing the “decline” characteristics, the overall consensus of such system can be guaranteed in the framework of dwell time. Finally, the effectiveness of the proposed result is illustrated by two numerical examples.     

Complementary‐based coalition formation for energy microgrids

In recent years, the notion of electrical energy microgrids (MGs), in which communities share their locally generated power, has gained increasing interest. Typically, the energy generated comes from renewable resources, which means that its availability is variable, ie, sometimes there may be energy surpluses and at other times energy deficits. This energy variability can be ameliorated by trading energy with a connected electricity grid. However, since main electricity grids are subject to faults or other outages, it can be advantageous for energy MGs to form coalitions and share their energy among themselves. In this work, we present our model for the dynamic formation of such MG coalitions. In our model, MGs form coalitions on the basis of complementary weather patterns. Our agent‐based model, which is scalable and affords autonomy among the MGs participating in the coalition (agents can join and depart from coalitions at any time), features methods to reduce overall “discomfort” so that, even when all participating MGs in a coalition experience deficits, they can share energy so that their overall discomfort is reduced. We demonstrate the efficacy of our model by showing empirical studies conducted with real energy production and consumption data.     

Output consensus for heterogeneous multiagent systems with Markovian switching network topologies

This paper investigates the output consensus problem of heterogeneous continuous‐time multiagent systems under randomly switching communication topologies. The switching mechanism is governed by a time‐homogeneous Markov process, whose states correspond to all possible communication topologies among agents. A novel dynamic consensus controller is proposed. The controller gains are designed based on the information of the expectation graph and the solutions to regulator equations. Furthermore, a necessary and sufficient condition is presented for output consensus of the controlled multiagent system in mean square sense. Finally, a simulation example is provided to corroborate the effectiveness of the proposed controller.     

Robust finite‐time consensus formation control for multiple nonholonomic wheeled mobile robots via output feedback

The finite‐time formation control for multiple nonholonomic wheeled mobile robots with a leader‐following structure is studied. Different from the existing results, the considered mobile robot has the following features: (i) a higher‐order dynamic model, (ii) the robot's velocities cannot be measured, and (iii) there are external disturbances. To solve the problem, a finite‐time consensus formation control algorithm via output feedback is explicitly given. At the first step, some finite‐time convergent observers are skillfully constructed to estimate both the unknown velocity information and the disturbance in finite time by imposing certain assumptions on the disturbances. Then, on the basis of the integral sliding‐mode control method, a disturbance observer‐based finite‐time output feedback controller is developed. Rigorous proof shows that the finite‐time formation can be achieved in finite time. An example is finally given to verify the efficiency of the proposed method.     

Directed spanning tree–based adaptive protocols for second‐order consensus of multiagent systems

This paper discusses the consensus problem of second‐order multiagent systems with nonlinear dynamics. A directed spanning tree–based adaptive control protocol is developed, which overcomes the drawback that the spectrum of the Laplacian matrix must be known a priori. A scheme for reordering the nodes is proposed. Applying the developed method and the Lyapunov stability theory, some distributed adaptive laws are designed in the directed network. It is found that the consensus can be achieved by randomly choosing a directed spanning tree and using the developed distributed adaptive law. Finally, an example is presented to illustrate the theoretical analysis.     

Distributed event‐triggered fixed‐time consensus for leader‐follower multiagent systems with nonlinear dynamics and uncertain disturbances

This paper focuses on the distributed event‐triggered fixed‐time consensus control problem of leader‐follower multiagent systems with nonlinear dynamics and uncertain disturbances. Two distributed fixed‐time consensus protocols are proposed based on distributed event‐triggered strategies, which can substantially reduce energy consumption and the frequency of the controller updates. It is proved that under the proposed distributed event‐triggered consensus tracking control strategies, the Zeno behavior is avoided. Compared with the finite‐time consensus tracking, the fixed‐time consensus tracking can be achieved within a settling time regardless of the initial conditions. Finally, 2 examples are performed to validate the effectiveness of the distributed event‐triggered fixed‐time consensus tracking controllers.     

Controllability of discrete‐time multiagent systems with switching topology

The current theoretical investigation on the controllability of switched multiagent systems mainly focuses on fixed connected topology or union graph without nonaccessible nodes. However, for discrete‐time multiagent systems with switching topology, it is still unknown whether the existing results are valid or not under the condition of arbitrary topology. Based on graph distance partitions and Wonham's geometric approach, we provide the lower and upper bounds for the dimension of controllable subspaces of discrete‐time multiagent systems. Unlike the existing results of controllability with switching topology, the proposed results have the advantage of being applicable to multiagent systems with arbitrary graphic topologies, union graph (strongly connected or not), and coupling weights. We also provide 2 algorithms for computing the lower and upper bounds for the dimension of controllable subspaces, respectively. Furthermore, as a remarkable application, we present how the proposed lower bound can be utilized for achieving the targeted controllability if the dimension of the controllable subspace of the switched system satisfies certain conditions.     

Decentralized and adaptive control of multiple nonholonomic robots for sensing coverage

This work deals with decentralized control of multiple nonholonomic mobile sensors for optimal coverage of a given area for sensing purposes. We assume a density function over the region to be covered, which can be viewed as a probability density of the phenomena to be sensed. The density function is unknown but assumed to be linearly parameterized with unknown parameter weights. We consider a second‐order dynamic model for the mobile agents and derive decentralized adaptive control laws to achieve optimal coverage of the region. We then consider the case where the dynamic model of the agents are not fully known, and then develop parameter adaptation laws to achieve the optimal coverage objective. We test the derived algorithms using simulations and compare our proposed controllers with kinematics‐based controllers. We find that the feedback control design based on the dynamic model performs significantly better than controllers solely relying on kinematic models. Furthermore, for the unknown dynamics case, our controller outperforms the nonadaptive controller with poor initial parameter estimates.     

多智能体控制系统的设计与实现

本文提出了利用多智能体技术实现控制系统的思想,分析了该系统的结构,采用黑板结构及产生式规则表达方法,对多智能体控制系统进行了设计,并对系统的设计做了进一步的探讨。