Multi-agent Based Control System Research Articles

Design of a Multiagent‐Based Voltage Control System in Peer‐to‐Peer Networks for Smart Grids

AbstractEnergy management in distribution grids is one of the key challenges that needs to be overcome to increase the share of fluctuating renewable energies. Current control systems for energy management mainly demonstrate centralized‐ or decentralized‐hierarchical control structures. Very few systems manifest a fully decentralized multiagent‐based control structure. Multiagent‐based control systems promise to be an advantageous approach for the future distributed energy supply system because no central control entity is necessary, which eases parameterization in case of grid topology changes, and the agents are more stable against failures and changes of control topologies. Research is necessary to prove these benefits. In this study, we introduce a design of a multiagent‐based voltage control system for low‐voltage grids. In detail we introduce cooperative decision‐making processes and software solutions that allow the agents to perceive and control their environment, the agent‐discovery and localization in different types of communication networks, agent‐to‐agent communication, and the integration of the multiagent system in existing grid‐control infrastructures. Furthermore, the study proposes how different existing technologies can be combined into an applicable multiagent‐based voltage control system: the Java/OSGi‐based OpenMUC framework allows a generic field–device interaction; peer‐to‐peer discovery and session establishment functionalities are combined with the agent communication defined by the Foundation for Intelligent Physical Agents (FIPA). The ripple control‐signal technology is applied as a fallback communication between the agent and a central grid‐control center.

406 組み立て工程におけるエージェントベース制御システム(OS5 : 製造の見える化(2))

406 組み立て工程におけるエージェントベース制御システム(OS5 : 製造の見える化(2))

402 状況変化に適応可能な組み立て工程の制御システム(OS4-1 生産の見える化と制御)

In the assembly process of high-mix low-volume production line, the control system must be flexible and robust to adapt to changes in state of manufacturing line such as switching product types, stopping for a short time, and out of stock of parts. In this paper, we propose a multi-agent based control system of the assembly process. Proposed agents work with BOM and their behavior depends on BOM tree structure. And we show mechanism of the multi-agent based control system to work with limited resources. In addition, a simulation system is developed to verify behavior of agents in various status changes.

Dynamic explicitly specified behaviors in distributed agent-based industrial solutions

Currently, the manufacturing domain is primarily characterized by the flexibility, adaptability and robustness of the production system. The manufacturing flow processes lead to shorter cycle times to efficiently meet customer needs. Mentioned features can be more easily achieved in a distributed system, such as holonic or multi-agent system, which becomes strongly influenced by the advancement of semantic technologies. In the majority of existing multi-agent based control systems, which are responsible for acting, sensing, computing and production planning, the ontology (necessary for knowledge bases and communication) is usually hard-coded directly in the agent code. In this case, the hard-coded system behavior can be hardly maintained--usually system reprogramming is needed from time to time to satisfy customer requirements. In this paper we discuss the necessity of explicit definition of both declarative and procedural knowledge and propose explicit procedural knowledge handling. Sharing and distribution of such knowledge is discussed and illustrated on an implemented transportation system example. We also introduce the utilization of discussed architecture for explicit specification of agent behavior in failures patterns handling and smart grid configuration scenario. Such a solution greatly increases the possibility of system integration, openness, flexibility, and extensibility, all without having to restart the running distributed system. The topic discussed in this paper shows the ability of the dynamic reconfigurable multi-agent system to participate in development of industrial control systems and solutions.

A multiagent-based control system applied to an educational shop floor

This paper addresses the design and implementation of a multiagent-based control architecture to support modular reconfigurable production systems. The requirements for plugability of modules (manufacturing components) and product changes were considered and tested against an educational platform based on Fischertechnik, which resembles a production system composed of several workstations connected by a crane and conveyors.

Multi-Agent Based Operation and Control of Isolated Power System with Dispersed Power Sources Including New Energy Storage Device

This paper presents a multi-agent based operation and control of isolated power systems with dispersed power sources such as photo-voltaic units, wind generation units, diesel generation units, and new energy storage devices such as the Energy Capacitor System (ECS). An advanced automatic generation control (AGC) scheme has been proposed through the coordination between the diesel unit and the ECS with small capacity. All the required information for the proposed multi- agent based AGC is distributed among intelligent agents through the computer network. All the AGC function is achieved by using the proposed multi-agent based control system. To demonstrate the efficiency of the proposed multi- agent based scheme, analog simulator tests have been performed. Simulations results indicate that the AGC performance has been highly improved by the proposed multi- agent based AGC scheme even in the existence of the communication delay time through computer networks.

Multiagent-based control systems: A hybrid approach to distributed process control

This paper presents a general architecture and a platform developed to implement distributed applications as a set of cooperating intelligent agents. It also shows how this architecture has been used to implement a distributed control system for a complex process: the economic control of a fossil-fuel fired power plant. Agents in this application encapsulate different distributed hardware/ software entities: neural and fuzzy controllers, a data-acquisition system, presentation manager, etc. These agents are defined in ADL (Agent Description Language), a high-level specification language, and interchange data/knowledge through service requests using a common knowledge-representation language.

Multiagent-Based Control Systems: An Hybrid Approach to Distributed Process Control

In this paper a general architecture and a platform developed to implement distributed applications, as a set of cooperating intelligent agents, is presented. Second, it will be shown how this architecture has been used to implement a distributed control system for a complex process: the economic control of a fossil power plant.Agents in this application encapsulate different distributed hardware/software entities: neural and fuzzy controllers, data acquisition system, presentation manager, etc. These agents are defined in ADL, a high level specification language, and interchange data/knowledge through service requests using a common knowledge representation language.