Protocol For Multi-agent System Research Articles

Particle swarm optimization based leader-follower cooperative control in multi-agent systems

Multi-agent systems (MAS) have attracted significant attention in recent years due to their wide applications in cooperative control, formation control, synchronization of complex networks, and distributed coordination. A fundamental problem in MAS is the leader-follower consensus or cooperative tracking, where the followers are required to track the state trajectory of the leader agent. To solve the leader-follower consensus problem, we propose a novel evolutionary computation approach to design the optimal distributed control protocols for leader-follower MAS. First, we formulate the design of distributed control gains for leader-follower consensus as an optimization problem to minimize tracking errors. Then, we leverage particle swarm optimization as an efficient evolutionary technique for distributed gain optimization in multi-agent networks. Finally, we guarantee stability for the closed-loop dynamics under directed communication topologies based on algebraic graph theory. The simulation results indicate that the proposed method yields a diminished tracking error, expedites the convergence process, and minimizes the requisite control effort while enhancing computational efficiency. Furthermore, these results exemplify the method's versatility when applied to nonlinear dynamic scenarios, directed network topologies, fluctuating disturbances, and optimization across multiple domains.

Observer-Based Adaptive Time-Varying Formation-Containment Tracking for Multiagent System With Bounded Unknown Input

In this article, the time-varying formation (TVF)-containment tracking problem is investigated for linear multiagent systems (MASs), in which the input of tracking leader is unknown and bounded. A novel kind of adaptive discontinuous TVF-containment tracking protocol for linear MAS is proposed. Based on the Lyapunov stability theory, it is shown that under the appropriate assumptions the leaders can achieve an expected TVF and track the trajectory of the tracking leader, while the follower agents can move into the convex hull formed by leader agents. Furthermore, the continuous protocols are also presented to avoid undesirable chattering from the tracking leader’s nonzero input, under which the errors are uniformly ultimately bounded and the upper bound of errors can be made arbitrarily small. In the end, simulation example verifies the feasibility of the desired theoretical results.

Adapting Interaction Protocols in Multiagent Systems at Runtime: A Promising Approach for Self-Adaptive Ambient Assisted Applications

Adapting Interaction Protocols in Multiagent Systems at Runtime: A Promising Approach for Self-Adaptive Ambient Assisted Applications

Consensus in multi-agent systems subject to input saturation and time-varying delays

This paper deals with the problem of consensus in multi-agent systems. The consensus is investigated considering directed networks composed by identical agents described by linear models of arbitrary order, subject to input saturation and non-uniform time-varying delays. The main results are sufficient conditions for consensus analysis and design of distributed consensus protocols for multi-agent systems. In addition, because the saturation might prevent the multi-agent system to attain consensus on some set of initial conditions, it is also proposed a strategy to calculate a region in which the consensus is guaranteed. The results follow from the Lyapunov–Krasovskii theory and are formulated in the linear matrix inequalities (LMIs) framework. Finally, we present examples to illustrate the effectiveness of the proposed method in contrast with similar approaches existing in the literature.

Min-Consensus for Heterogeneous Higher-Order Integrators Under Switching Digraph

For a multi-agent system (MAS), researchers have explored min-consensus for single-integrators under uniformly strongly-connected digraph, and double-integrators under jointly-connected graphs. However, the extension of these works is non-trivial for heterogeneous higher-order integrators under switching digraphs. This letter proposes a min-consensus protocol for MAS with higher-order integrators under uniformly strongly-connected digraph. The protocol consists of a distributed observer and a decentralized tracking controller. Each agent distributively estimates the minimum of initial values of all agents by using its neighbors’ information only. The decentralized controller ensures that the agents follow their respective estimated values. This structure of the protocol allows a set of heterogeneous higher-order integrators to achieve min-consensus. Theoretical proofs and numerical simulations validate the proposed min-consensus protocol. Through numerical example, we also establish that a group of heterogeneous integrators cannot achieve min-consensus, in general, without a uniformly strongly-connected digraph.

Adaptive synchronization of multi-agent systems with resilience to communication link faults

The resilience of multi-agent systems (MAS) measures the capability of recovering the cooperative performance after experiencing faults or uncertainties. In this paper, we seek the improvement of the synchronization resilience for MAS by means of addressing unknown faults on communication links. To this end, we first transform the resilient control problem into designing distributed state observers. In addition, we show that the proposed state observers are resilient to communication link faults. Finally, we provide the main result of this paper as a synchronization protocol for MAS even in the presence of communication link faults.

A clustered neighbourhood consensus algorithm for a generic agent interaction protocol

This paper significantly contributes a consensus algorithm to enhance the efficiency of existing generic interaction protocol for multiagent systems (GIPMAS). The proposed algorithm is marriage of neighbourhood algorithm and discrete time consensus protocol and the neighbourhood algorithm focuses on providing more weight to communication links/edges joining two clusters as compared to links joining two agents in a cluster, which increases rate of convergence of information. Thus, in clustered network of agents, cluster head and executive cluster head would be responsible for deriving consensus in the received information. Simulation reflects that proposed mechanism improves time of convergence of information. However, slight increase in task execution is also observed due to trade-off between quality of output and complexity of mechanism.

Coordinated consensus for smart grid economic environmental power dispatch with dynamic communication network

Combined economic environmental dispatch problem (CEEDP) is one of the greatest challenges of the future smart grids. It aims at reducing the total cost during the power production process considering the growing environmental impact due to the emission of gaseous pollutants of fossil fuels. This study develops a robust distributed algorithm based on consensus protocols in multi-agent systems, to solve the smart grid CEEDP with a practical communication network consisting of a dynamic communication network, randomly communication failure, transmission delay and noise in communication channels. The proposed algorithm is fully distributed and cooperative in such a way that it eliminates the need for a central energy-management unit, or a leader. The performance of the fully decentralised consensus protocol was evaluated on the IEEE 30-bus and the IEEE 118-bus test system. A comparison with previous consensus algorithms proves the supremacy of the proposed approach in terms of its robustness under dynamic communication network with randomly link failure.

Optimization-Based AC Microgrid Synchronization

This paper casts the synchronization phenomena in inverter-based ac microgrids as an optimization problem solved using alternating direction method of multipliers (ADMM). Existing cooperative control techniques are based on the standard voting protocols in multiagent systems, and assume ideal communication among inverters. Alternatively, this paper presents a recursive algorithm to restore synchronization in voltage and frequency using ADMM, which results in a more robust secondary control even in the presence of noise. The performance of the control algorithm, for an islanded microgrid test system with additive noise in communication links broadcasting reference signals and communication links connecting neighboring inverters, is evaluated for a modified IEEE 34-bus feeder system. An upper bound for the deviation due to communication noise from the reference set point is analytically derived and verified by the simulated microgrid test system.

Designing a novel consensus protocol for multiagent systems with general dynamics under directed networks

The consensus problem for general linear multi-agent systems (MASs) under directed topology is investigated. First, a novel consensus protocol based on proportional-integral-derivative (PID) control is proposed. Second, the consensus problem is converted into an asymptotic stability problem through transformations. Third, through a state projection method the consensus condition is proved and the explicit expression of the consensus function is given. Then, a Lyapunov function is constructed and the gain matrices of the protocol are given based on the linear matrix inequality. Finally, two experiments are conducted to explain the advantages of the method. Simulation results show the effectiveness of the proposed algorithm.

A novel leader following consensus approach for multi-agent systems with data loss

The objective of this paper is to develop a novel consensus algorithm or protocol for multi-agent systems in the event of communication link failure over the network. The structure or topology of the system is modeled by an algebraic graph theory, and considered as a discrete time-invariant system with a second-order dynamics. Bernoulli distribution is applied to represent the data dropout during operation. The sufficient conditions for the stabilization controller design is developed by Lyapunov-based methodologies and Linear matrix inequality (LMIs) techniques. The feasibility of the given LMIs is analyzed to verify the stabilization of controller design, which ensures the MAS to achieve the consensus. Leader-following numerical simulations with a group of agents are successfully conducted based on the effect of data losses, initial values, communication weights, and number of agents to demonstrate the effectiveness of the novel consensus algorithm in this paper. Finally, experimental studies are carried out by using two Pioneer 3-DX mobile robots and one Pioneer 3-AT mobile robot as a team to verify the proposed work.

Nonlinear finite-time bipartite consensus protocol for multi-agent systems associated with signed graphs

In this paper, finite-time multi-agent consensus problems are considered under networks associated with signed graphs whose edge weights can be not only positive but also negative. A nonlinear consensus protocol is proposed to guarantee the states of all agents to converge in a finite time. If the signed graph is structurally balanced, then the final consensus states of all agents are the same in modulus but not in sign. Otherwise, if the signed graph is structurally unbalanced, then the states of all agents converge to zero. Moreover, the final consensus states of agents can be provided uniformly regarding a signed-average quantity that depends on both the initial states of agents and the topology structure of the whole multi-agent network. Numerical simulations illustrate that the protocol is effective in achieving the finite-time consensus of agents under signed graphs and can particularly solve the finite-time average consensus problem of agents when their associated graph has all positive edge weights.

Application of Artificial Capital Market in Task Allocation in Multi-robot Foraging

AbstractBecause of high speed, efficiency, robustness and flexibility of multi-agent systems, in recent years there has been an increasing interest in the art of these systems. Artificial market mechanisms are one of the well-known negotiation multi-agent protocols in multi-agent systems. In this paper artificial capital market as a new variant of market mechanism is introduced and employed in a multi-robot foraging problem. In this artificial capital market, the robots are going to benefit via investment on some assets, defined as doing foraging task. Each investment has a cost and an outcome. Limited initial capital of the investors constrains their investments. A negotiation protocol is proposed for decision making of the agents. Qualitative analysis reveals speed of convergence, near optimal solutions and robustness of the algorithm. Numerical analysis shows advantages of the proposed method over two previously developed heuristics in terms of four performance criteria.

DYNAMIC CONSEQUENCE AND PUBLIC ANNOUNCEMENT

AbstractIn van Benthem (2008), van Benthem proposes a dynamic consequence relation defined as ${\psi _1}, \ldots ,{\psi _n}{ \models ^d}\phi \,{\rm{iff}}{ \models ^{pa}}[{\psi _1}] \ldots [{\psi _n}]\phi ,$ where the latter denotes consequence in public announcement logic, a dynamic epistemic logic. In this paper we investigate the structural properties of a conditional dynamic consequence relation $\models _{\rm{\Gamma }}^d$ extending van Benthem’s proposal. It takes into account a set of background conditions Γ, inspired by Makinson (2003) wherein Makinson calls this reasoning ‘modulo’ a set Γ. In the presence of common knowledge, conditional dynamic consequence is definable from (unconditional) dynamic consequence. An open question is whether dynamic consequence is compact. We further investigate a dynamic consequence relation for soft instead of hard announcements. Surprisingly, it shares many properties with (hard) dynamic consequence. Dynamic consequence relations provide a novel perspective on reasoning about protocols in multi-agent systems.

Data mining agent conversations: A qualitative approach to multiagent systems analysis

This paper presents a novel method for analysing the behaviour of multiagent systems on the basis of the semantically rich information provided by agent communication languages and interaction protocols specified at the knowledge level. More low-level communication mechanisms only allow for a quantitative analysis of the occurrence of message types, the frequency of message sequences, and the empirical distributions of parameter values. Quite differently, the semantics of languages and protocols in multiagent systems can help to extract qualitative properties of observed conversations among agents. This can be achieved by interpreting the logical constraints associated with protocol execution paths or individual messages as the context of an observed interaction, and using them as features of learning samples. The contexts “mined” from such analyses, or context models, can then be used for various tasks, e.g. for predicting others’ future responses (useful when trying to make strategic communication decisions to achieve a particular outcome), to support ontological alignment (by comparing the properties of logical constraints attached to messages across participating agents), or to assess the trustworthiness of agents (by verifying the logical coherence of their behaviour). This paper details a formal approach that describes our notion of context models in multiagent conversations, an implementation of this approach in a practical tool for mining qualitative context models, and experimental results to illustrate its use and utility.

Interaction Protocols in Multi-Agent Systems based on Agent Petri Nets Model

This paper deals with the modeling of interaction between agents in Multi Agents System (MAS) based on Agent Petri Nets (APN). Our models are created based on communicating agents. Indeed, an agent initiating a conversation with other can specify the interaction protocol wishes to follow. The combination of APN and FIPA Protocols schemes leads to a set of deployment formal rules for points where model interaction can be successfully implemented. We introduce some models FIPA standard protocols.

Leader-Following Protocol Design for Switched Multiagent Systems with Randomly Occurring Self-Delay

This paper designs a delay-dependent leader-following protocol for multiagent systems with both communication delay and randomly occurring self-delay. Based on the randomly occurring mode of self-delay, a new model of switched multi-agent systems which have not been introduced yet is constructed. By constructing a newly piecewise Lyapunov-Krasovskii functional, a leader-following stability criterion of the switched multi-agent systems is derived by the framework of linear matrix inequalities (LMIs) and the average dwell time with the randomly occurring mode. Based on the result of the derived stability criterion, a designing leader-following protocol for the system will be proposed. One numerical example is included to show the effectiveness of the proposed method.

Learning specifications of interaction protocols and business processes and proving their properties

In this paper we overview our recent research activity concerning the induction of Logic Programming specifications, and the proof of their properties via Abductive Logic Programming. Both the inductive and abductive tools here briefly described have been applied to respectively learn and verify (properties of) interaction protocols in multi-agent systems, Web service choreographies, careflows and business processes.

Programming of agents in the PRALU language

A method of specifying agent interaction protocols in multiagent systems in the PRALU language (parallel logic control algorithms) is considered. A methodology for programming agents in the PRALU language based on a two-block architecture, a synchronization block and a functional block, is proposed. It is shown that through use of a description of the behavior of agents in the PRALU language it becomes possible to simulate the behavior of a multiagent system as a whole.

AN ACL FOR SPECIFYING FAULT-TOLERANT PROTOCOLS

Agent communication languages (ACLs) should allow the developer to adopt human-like communication mechanisms in agent programming, facilitating the development of distributed protocols in multi-agent systems (MASs). However, to implement robust protocols, ACLs should provide a way to deal with the failures of agents, as MASs are prone to the same failures that can occur in any distributed software system. In this paper, we address this issue showing how an asynchronous ACL that provides high-level mechanisms to deal with crash failures of agents can be effectively used to specify fault tolerant protocols.