agents, in a multi agent system, communicate with each other through the process of exchanging messages which is called dialogue. multi agent organization is generally usedto optimize agents’ communications. Holonic organization demonstrates a self-similar recursive and hierarchical structure in which each holon may include some other holons. In a holonic system, lateral communication occurs between members of a determined holon and vertical communications are inter-level ones between different holons. When agents start a dialogue, according to their beliefs, they follow some rules that define the permissive speech acts called dialogue protocol. The dialogue strategy is the policy of agents to choose a particular speech act among the allowed ones by the protocol in order to achieve the common goals of holon. In this paper a formal model for dialogue strategy for lateral communication in a holon is proposed. This model tries to choose the most preferable speech acts considering at the same time local beliefs and goals along with public knowledge obtained from holonic organization. Moreover, the argumentation theory is applied to rank and define the values of speech acts. The proposed model finds the most preferable option to utter and it also decreases the number of exchanging messages. The proposed model of dialogue strategy is illustrated via a deliberation dialogue example in a holon. The example showed a significant efficiency in decreasing the number of exchanged messages and the effectiveness of deliberation.

In previous papers authors have considered agents as inertia less self driven particles and designed a flocking algorithm. Application of this algorithm to agents with considerable inertial characteristics needs a behavioural controller. The controller uses the local information and helps every agent to imitate the desired behaviour as a member of the flocking frame which covers the main issue in this paper. All agents are assumed to possess limited identical influencing/sensing radius. The sliding-mode control technique is used, hence; effect of bounded disturbances and uncertainties can be omitted too. Once inertial agents are equipped with the behavioral controller, the multi-agent system behaves similar to a group of self-driven inertia-less particles which; coordination control algorithms and cohesion analyses are previously designed for.

The objective of the current paper is to present an intelligent system for complex process monitoring, based on artificial intelligence technologies. This system aims to realize with success all the complex process monitoring tasks that are: detection, diagnosis, identification and reconfiguration. For this purpose, the development of a multi-agent system that combines multiple intelligences such as: multivariate control charts, neural networks, Bayesian networks and expert systems has became a necessity. The proposed system is evaluated in the monitoring of the complex process Tennessee Eastman process.

This paper describes how multi-agent system technology can be used as the underpinning platform for voltage control in power systems. In this study, some FACTS (flexible AC transmission systems) devices are properly designed to coordinate their decisions and actions in order to provide a coordinated secondary voltage control mechanism based on multi-agent theory. Each device here is modeled as an agent being able to cooperate and communicate with other devices. In this system, individual autonomous agents and intelligent decision makers learn to perform optimal actions through proper interactions with their environments. The SARSA Q-learning, which is an on-policy algorithm in reinforcement learning (RL) is then used and tested successfully in voltage control problem. In this research, the Java agent Development (JADE) platform is used to implement the agents and to simulate their communications. The power system is also fully implemented in Java. The proposed intelligent MA based method is finally applied to IEEE 39-buses New England power system. The results of simulation better highlight the merit of the method and its ability in coordinating FACTS devices for removing voltage disturbances.

This paper studies the problem of fault detection and isolation (FDI) for multi-agent systems (MAS) via complex Laplacian subject to actuator faults. Using simple and linear interaction rules related to complex Laplacian, a planar formation of agents in the plane is achieved. The communication network is a directed, and yet connected graph with a fixed topology. The loss of symmetry in the digraph Laplacian matrix is also considered. Both the partial actuator effectiveness and the actuator bias faults are taken into account. For this purpose, a virtual agent whose dynamics structure is identical to that of the leader agent is introduced to determine the center of the planar formation. The FDI scheme requires no additional fault isolation model which is an essential part in the traditional FDI scheme. Finally, numerical example results are presented to show the effectiveness of the proposed scheme.

This paper presents a cooperative control which is applied to the secondary control of a microgrid controlled via a multi-agent scheme. Balancing power that leads to voltage and frequency stability in a microgrid is essential. The voltage and frequency regulations are limiting within the specified limits and conveying them to their nominal values. Limiting and conveying the voltage and frequency to their nominal values is done by the primary and secondary controls, respectively. A Microgrid has both dispatchable and non-dispatchable sources. Dispatchable sources are controlled by the conventional P-ω and Q-E droop controls. A photovoltaic as a non-dispatchable source generates the active power according to weather conditions, but the reactive power is supplied using the E-Q droop method. The E-Q droop uses the idle capacity of the inverters in the reactive power supply. Distributed secondary control increases the stability due to good, accurate and reliable controls. The frequency is constant in the whole microgrid. Since line impedances are different, load terminal voltage control is necessary. The load is considered as another agent, who can request the desired voltage at its terminal bus.

This paper investigates a novel method to solve distributed optimization problems in the presence of communication delays between the networked agents that cooperate together to find an optimal solution of a global cost function composed of local ones. In the problem of distributed optimization in a network of multi-agent because of existing phenomena such as communication delay, deriving approaches having appropriate performance so that the states of all agents converge to the same value always has been a substantial challenge. Delay-dependent conditions in the form of linear matrix inequities are derived to analyze the convergence of the introduced scheme to the optimal solution. It is demonstrated that the maximum allowable time delay in the network and convergence rate of the optimization procedure are increased by the suggested strategy. Finally, comparative simulation results are considered to illustrate the superior performance of the introduced scheme compared to a rival one in the literature.