Showing papers on "Multi-agent system published in 2016"
TL;DR: A smart factory framework that incorporates industrial network, cloud, and supervisory control terminals with smart shop-floor objects such as machines, conveyers, and products is presented and an intelligent negotiation mechanism for agents to cooperate with each other is proposed.
1,074 citations
TL;DR: A novel event-triggered control scheme with some desirable features, namely, distributed, asynchronous, and independent is proposed and it is shown that consensus of the controlled multi-agent system can be reached asymptotically.
Abstract: This paper studies the consensus problem of multi-agent systems with general linear dynamics. We propose a novel event-triggered control scheme with some desirable features, namely, distributed, asynchronous, and independent. It is shown that consensus of the controlled multi-agent system can be reached asymptotically. The feasibility of the event-triggered strategy is further verified by the exclusion of both singular triggering and Zeno behavior. Moreover, a self-triggered algorithm is developed, where the next triggering time instant for each agent is determined based on its local information at the previous triggering time instant. Continuous monitoring of measurement errors is thus avoided. The effectiveness of the proposed control schemes is demonstrated by two examples.
545 citations
TL;DR: It is shown that the finite settling time of the proposed general framework for robust consensus design is upper bounded for any initial condition, which makes it possible for network consensus problems to design and estimate the convergence time offline for a multi-agent team with a given undirected information flow.
Abstract: This paper investigates the robust finite-time consensus problem of multi-agent systems in networks with undirected topology. Global nonlinear consensus protocols augmented with a variable structure are constructed with the aid of Lyapunov functions for each single-integrator agent dynamics in the presence of external disturbances. In particular, it is shown that the finite settling time of the proposed general framework for robust consensus design is upper bounded for any initial condition. This makes it possible for network consensus problems to design and estimate the convergence time offline for a multi-agent team with a given undirected information flow. Finally, simulation results are presented to demonstrate the performance and effectiveness of our finite-time protocols.
496 citations
TL;DR: It is proved that under the proposed ETCC there is no Zeno behavior exhibited, and a self-triggered consensus controller (STCC) is proposed to relax the requirement of continuous monitoring of each agent's own states.
377 citations
TL;DR: The proposed algorithm is applied to the distributed economic dispatch problem in power grids, to demonstrate how it can achieve the global optimum in a scalable way, even when the generation cost, or system load, or network configuration, is changing.
375 citations
TL;DR: A new class of distributed observer-type containment protocols based only on the relative output measurements of the neighboring agents is proposed, removing the impractical assumption in some of the existing approaches that the observers embedded in the multiple dynamic agents have to share information with their neighbors.
Abstract: This technical note addresses the distributed containment control problem for a linear multi-leader multi-agent system with a directed communication topology. A new class of distributed observer-type containment protocols based only on the relative output measurements of the neighboring agents is proposed, removing the impractical assumption in some of the existing approaches that the observers embedded in the multiple dynamic agents have to share information with their neighbors. Under the mild assumption that, for each follower, there exists at least one leader having a directed path to that follower, some sufficient conditions are derived to guarantee the states of the followers to asymptotically converge to a convex hull formed by those of the dynamic leaders. Finally, some numerical simulations on containment of a multi-vehicle system are given to verify the effectiveness of the theoretical results.
349 citations
21 Mar 2016
TL;DR: This work surveys and analyzes the current state of the industrial application of agent technology in CPSs, and provides a vision on the way agents can effectively enable emerging CPS challenges.
Abstract: Future industrial systems can be realized using the cyber–physical systems (CPSs) that advocate the coexistence of cyber and physical counterparts in a network structure to perform the system’s functions in a collaborative manner. Multiagent systems share common ground with CPSs and can empower them with a multitude of capabilities in their efforts to achieve complexity management, decentralization, intelligence, modularity, flexibility, robustness, adaptation, and responsiveness. This work surveys and analyzes the current state of the industrial application of agent technology in CPSs, and provides a vision on the way agents can effectively enable emerging CPS challenges.
326 citations
TL;DR: Within this framework, the development on this topic is systematically reviewed and the representative outcomes can be sorted out from four aspects: 1) agent dynamics; 2) network topologies; 3) feedback and communication mechanisms; 4) collective behaviors.
Abstract: Collective control of a multiagent system is concerned with designing strategies for a group of autonomous agents operating in a networked environment. The aim is to achieve a global control objective through distributed sensing, communication, computing, and control. It has attracted many researchers from a wide range of disciplines, including the literature of automatic control. This paper aims to give a general framework that is able to accommodate many of these outcomes. Within this framework, the development on this topic is systematically reviewed and the representative outcomes can be sorted out from four aspects: 1) agent dynamics; 2) network topologies; 3) feedback and communication mechanisms; and 4) collective behaviors. Thus, the state-of-the-art approach and technology is described. Moreover, within this framework, further interesting and promising directions on this research topic are envisioned.
243 citations
TL;DR: In this paper, a distributed event-triggered algorithm is proposed to solve the multi-agent average consensus problem for networks whose communication topology is described by weight-balanced, strongly connected digraphs, and the resulting network executions provably converge to the average of the initial agents' states exponentially fast.
236 citations
TL;DR: It is proved that the proposed design can solve the exact optimization problem with rejecting disturbances and is proposed a distributed optimization controller for heterogeneous and nonlinear agents in the form of continuous-time minimum-phase systems with unity relative degree.
Abstract: The paper studies the distributed optimization problem for a class of nonlinear multiagent systems in the presence of external disturbances. To solve the problem, we need to achieve the optimal multiagent consensus based on local cost function information and neighboring information and meanwhile to reject local disturbance signals modeled by an exogenous system. With convex analysis and the internal model approach, we propose a distributed optimization controller for heterogeneous and nonlinear agents in the form of continuous-time minimum-phase systems with unity relative degree. We prove that the proposed design can solve the exact optimization problem with rejecting disturbances.
TL;DR: The extended linear matrix inequalities (LMIs) are used to reduce the conservativeness of the SFDCC results by introducing additional matrix variables to eliminate the couplings of Lyapunov matrices with the system matrices.
TL;DR: In this paper, a new nonlinear distributed control protocol is proposed to achieve finite-time consensus for multi-agent systems with fixed and switching network topologies, and two sufficient conditions are proposed.
TL;DR: Under the designed event-triggered protocol, by selecting suitable parameters, for any directed digital network containing a spanning tree, the distributed average consensus can be always achieved with an exponential convergence rate based on merely one bit information exchange between each pair of adjacent agents at each time step.
Abstract: In this paper, we consider the event-triggered distributed average-consensus of discrete-time first-order multiagent systems with limited communication data rate and general directed network topology. In the framework of digital communication network, each agent has a real-valued state but can only exchange finite-bit binary symbolic data sequence with its neighborhood agents at each time step due to the digital communication channels with energy constraints. Novel event-triggered dynamic encoder and decoder for each agent are designed, based on which a distributed control algorithm is proposed. A scheme that selects the number of channel quantization level (number of bits) at each time step is developed, under which all the quantizers in the network are never saturated. The convergence rate of consensus is explicitly characterized, which is related to the scale of network, the maximum degree of nodes, the network structure, the scaling function, the quantization interval, the initial states of agents, the control gain and the event gain. It is also found that under the designed event-triggered protocol, by selecting suitable parameters, for any directed digital network containing a spanning tree, the distributed average consensus can be always achieved with an exponential convergence rate based on merely one bit information exchange between each pair of adjacent agents at each time step. Two simulation examples are provided to illustrate the feasibility of presented protocol and the correctness of the theoretical results.
TL;DR: This paper considers optimal output synchronization of heterogeneous linear multi-agent systems and shows that this optimal distributed approach implicitly solves the output regulation equations without actually doing so.
TL;DR: Multiagent systems have been a major area of research for the last 15 years motivated by tasks that can be executed more rapidly in a collaborative manner or that are nearly impossible to carry out otherwise.
Abstract: Multiagent systems have been a major area of research for the last 15 years. This interest has been motivated by tasks that can be executed more rapidly in a collaborative manner or that are nearly impossible to carry out otherwise. To be effective, the agents need to have the notion of a common goal shared by the entire network (for instance, a desired formation) and individual control laws to realize the goal. The common goal is typically centralized, in the sense that it involves the state of all the agents at the same time. On the other hand, it is often desirable to have individual control laws that are distributed, in the sense that the desired action of an agent depends only on the measurements and states available at the node and at a small number of neighbors. This is an attractive quality because it implies an overall system that is modular and intrinsically more robust to communication delays and node failures.
TL;DR: This work shows how the two concepts of formation shape control and flocking behavior can be combined when one changes from an agent with single integration to one with double integration.
Abstract: Steepest descent control laws can be used for formation shape control based on specified inter-agent distances, assuming point agents with single integration of the control action to yield velocity. Separately, it is known how to achieve equal velocity for a collection of agents in a formation using consensus ideas, given appropriate properties for the graph describing information flows. This work shows how the two concepts of formation shape control and flocking behavior can be combined when one changes from an agent with single integration to one with double integration.
TL;DR: A multi-agent-based supply chain management system that incorporates big data analytics that can exert autonomous corrective control actions and incorporates semantic web information and a big data ontology in the agent society is developed.
Abstract: Purpose: Decision support systems have become an indispensable tool for managing complex supply chains. This paper develops a multi-agent based supply chain management system that incorporates big data analytics that can exert autonomous corrective control actions. The effects of the system on supply chain agility are explored.
Design/methodology/approach: For the development of the architecture of the system, a sequential approach is adopted. First three fundamental dimensions of supply chain agility are identified – responsiveness, flexibility and speed. Then the organisational design of the system is developed. The roles for each of the agents within the framework are defined and the interactions among these agents are modelled.
Findings: Applications of the model are discussed, to show how the proposed model can potentially provide enhanced levels in each of the dimensions of supply chain agility.
Research limitations/implications: The study shows how the multi-agent systems can assist to overcome the trade-off between supply chain agility and complexity of global supply chains. It also opens up a new research agenda for incorporation of big data and semantic web applications for the design of supply chain information systems.
Practical implications: The proposed information system provides integrated capabilities for production, supply chain event and disruption risk management under a collaborative basis.
Originality/value. A novel aspect in the design of multi-agent systems is introduced for inter-organisational processes, which incorporates semantic web information and a big data ontology in the agent society.
TL;DR: An event-triggered strategy able to guarantee the existence of a minimum lower bound between inter-event times for broadcasted information and for control signal updating is proposed, thus allowing applications where both the communication bandwidth and the maximum updating frequency of actuators are critical.
TL;DR: A distributed consensus control protocol is proposed which extends the first order system results of Ren and Beard to agents represented by a general higher order controllable linear system and it is shown that the consensus can be achieved asymptotically by the group of agents under this proposed distributed control protocol.
Abstract: In 2005, Ren and Beard, under the network connectivity assumption that the union of the directed interaction graphs contains a spanning tree frequently enough, proposed a control protocol to solve the distributed consensus control problem for a multi-agent system with first order integrator agent dynamics. The consensus control protocol for second order systems proposed by the same authors, Ren and Beard, requires that the switching directed interaction graph has a spanning tree at every time instant to guarantee consensus. In this technical note, we propose a distributed consensus control protocol which extends the first order system results of Ren and Beard to agents represented by a general higher order controllable linear system, under the same network connectivity assumption that the union of the directed interaction graphs contains a spanning tree frequently enough. We show that the consensus can be achieved asymptotically by the group of agents under our proposed distributed control protocol. Simulation study illustrates the effectiveness of our proposed method.
TL;DR: It is found that the reverse group consensus problem can be achieved if the mirror graph is strongly connected, and the explicit expression of the error level is derived, which would be vanished for multi-agent systems with some special kinds of inputs.
Abstract: In this paper, a reverse group consensus problem is investigated for the dynamic agents with the inputs in the cooperation-competition network which can be divided into two sub-networks. The weights between the agents in the same sub-network are positive, while the weights between the agents among different sub-networks are negative. Then, the reverse group consensus is firstly studied without the in-degree balance condition. By defining the mirror graph and establishing the solution of the multi-agent system, it is found that the reverse group consensus problem can be achieved if the mirror graph is strongly connected. The explicit expression of the error level is also derived, which would be vanished for multi-agent systems with some special kinds of inputs. Furthermore, as an extension, the decomposing of the cooperation-competition network is discussed, where the concept of the condensation undirected graph and the path balance condition are defined, and several effective sufficient conditions are obtained. Finally, numerical simulation demonstrates the effectiveness of the theoretical analysis.
TL;DR: An impulsive framework to analyze the effect of the clustered event-triggered information transmission on the dynamics of multiagent systems is proposed, which guarantees all followers to track the leader eventually.
Abstract: This paper proposes an impulsive framework to analyze the effect of the clustered event-triggered information transmission on the dynamics of multiagent systems. Under this framework, we study three cases and propose different types of event-triggered protocols. First, if agents’ states are available, a clustered event-triggered protocol based on agents’ states is designed, which guarantees all followers to track the leader eventually. Second, the first case is further investigated when the agents’ states are under disturbance. Hence, a modified event-triggered protocol is introduced to reach $\mathcal {L}_\infty$ leader-following consensus. Third, for the case where agents’ states are not available, a clustered event-triggered observer-type protocol is developed based on the agents’ outputs. It is worth noting that Zeno behavior is excluded in these cases. Finally, some numerical examples and an application of unmanned aerial vehicle helicopters are given to verify our theoretical analysis.
TL;DR: It is shown that global leader-following consensus is achieved under these feedback control laws when the communication topology among follower agents is a strongly connected and detailed balanced directed graph and the leader is a neighbor of at least one follower.
TL;DR: An alternative definition torational synthesis is suggested, in which the agents are rational but not cooperative, and it is shown that strong rational synthesis is 2ExpTime-complete, thus it is not more complex than traditional synthesis or rational synthesis.
Abstract: Synthesis is the automated construction of a system from its specification. The system has to satisfy its specification in all possible environments. The environment often consists of agents that have objectives of their own. Thus, it makes sense to soften the universal quantification on the behavior of the environment and take the objectives of its underlying agents into an account. Fisman et al. introduced rational synthesis: the problem of synthesis in the context of rational agents. The input to the problem consists of temporal logic formulas specifying the objectives of the system and the agents that constitute the environment, and a solution concept (e.g., Nash equilibrium). The output is a profile of strategies, for the system and the agents, such that the objective of the system is satisfied in the computation that is the outcome of the strategies, and the profile is stable according to the solution concept; that is, the agents that constitute the environment have no incentive to deviate from the strategies suggested to them. In this paper we continue to study rational synthesis. First, we suggest an alternative definition to rational synthesis, in which the agents are rational but not cooperative. We call such problem strong rational synthesis. In the strong rational synthesis setting, one cannot assume that the agents that constitute the environment take into account the strategies suggested to them. Accordingly, the output is a strategy for the system only, and the objective of the system has to be satisfied in all the compositions that are the outcome of a stable profile in which the system follows this strategy. We show that strong rational synthesis is 2ExpTime-complete, thus it is not more complex than traditional synthesis or rational synthesis. Second, we study a richer specification formalism, where the objectives of the system and the agents are not Boolean but quantitative. In this setting, the objective of the system and the agents is to maximize their outcome. The quantitative setting significantly extends the scope of rational synthesis, making the game-theoretic approach much more relevant. Finally, we enrich the setting to one that allows coalitions of agents that constitute the system or the environment.
TL;DR: Investigating the group consensus phenomenon for multiple interacting clusters of double-integrator agents in the presence of both cooperative and competitive inter-cluster couplings shows that for most cases, there holds a consistent structural result that group consensus can be achieved if the underlying topology for each cluster of agents satisfies certain connectivity assumptions.
TL;DR: This paper focuses on improving profit, economy, security, and dynamic performance of the integrated hybrid energy system by means of developing different areas of management and control strategies upon four-level hierarchical multiagent system.
Abstract: Since a microgrid consists of various distributed energy resources and local loads, integration of a distributed grid and multiple microgrids leads to an integrated hybrid energy system. This paper focuses on improving profit, economy, security, and dynamic performance of the integrated hybrid energy system by means of developing different areas of management and control strategies upon four-level hierarchical multiagent system. The level 1 agent implements optimal price bidding strategies for high profit of the overall system. The level 2 agent optimizes the energy management strategies for economic operation of each microgrid. The level 3 agent executes coordinated switching control for maintaining security of each microgrid. The level 4 agent facilitates local hybrid control of each distributed energy resource for guaranteeing dynamic performance. Finally, validity of the proposed scheme is tested by means of simulation study.
TL;DR: In this paper, the recent developments of distributed coordination control problems are summarized in a graph-theory-based framework, where the graph is used to describe the interconnections among agents, and different distributed control problems, such as consensus, formation control, rendezvous, alignment, swarming, flocking, containment control and circumnavigation control, are adopted to this description by considering different cooperative objects.
TL;DR: A novel distributed regulator for groups of identical and non-identical linear agents based on their transient state components or estimates thereof in the output feedback case to improve the cooperative behavior of the group in transient phases and guarantee a desired decay rate of the synchronization error.
TL;DR: A framework and associated engineering approach combines multi-agent system with Service Oriented Architectures for the development of intelligent automation control and execution of manufacturing systems.
TL;DR: In this article, a multiscale modeling, control, and simulation of self-organizing agents leaving an unknown area under limited visibility, with special emphasis on crowds is presented.
Abstract: In this paper we are concerned with multiscale modeling, control, and simulation of self-organizing agents leaving an unknown area under limited visibility, with special emphasis on crowds. We first introduce a new microscopic model characterized by an exploration phase and an evacuation phase. The main ingredients of the model are an alignment term, accounting for the herding effect typical of uncertain behavior, and a random walk, accounting for the need to explore the environment under limited visibility. We consider both metrical and topological interactions. Moreover, a few special agents, the leaders, not recognized as such by the crowd, are “hidden” in the crowd with a special controlled dynamic. Next, relying on a Boltzmann approach, we derive a mesoscopic model for a continuum density of followers, coupled with a microscopic description for the leaders' dynamics. Finally, optimal control of the crowd is studied. It is assumed that leaders aim at steering the crowd towards the exits so to ease the evacuation and limit clogging effects, and locally optimal behavior of leaders is computed. Numerical simulations show the efficiency of the control techniques in both microscopic and mesoscopic settings. We also perform a real experiment with people to study the feasibility of such a bottom-up control technique.