![]() Communication Control Agent: establishes communication with other MAS. Data Base Agent: manages the information storage means.Applications Management Agent: administer the use of applications (software) of the system.Resource Management Agent: administers the use of the resources.Agent Administering Agents: coordinates the multi-agent society.Human Agent: supervises the SCIDA Agents of the Service Management Environment (SME): It is the base of the distribution system given that it manages the communication of the IDCSA model and permit the distribution of the control system and heterogeneity among geographically dispersed agents.Observation Agent: measures and processes the variables of the plant.Actuator Agent: executes the control action.Controller Agent: obtains control action.Specialized Agent: carry out specific jobs that serve to support the coordinating agent.Coordinating Agent: make decisions and plan control jobs.In the IDCSA model two categories of agents exist: Control Agents: Carry out the jobs of control, measurement, control decision making, and putting the decisions into practice, among others. The dynamic interaction of the multiple agents happens between levels and in the interior of the levels. This way, the agents are distributed through the control hierarchy and can be geographically dispersed. As such, the details of each agent (objectives, communication, jobs, intelligence, etc.) come according to the levels to which the given agents belong in the IDCSA model. The IDCSA is seen as a net- work of autonomous agents, with different responsibilities according to the level to which it belongs. The incorporation of the MAS to the reference model permits the control to emerge from the interactions of those entities (agents). These agents carry out diverse jobs looking towards reaching the specific control objective. This SCD model is complemented with a group of agents in each one of the levels of the hierarchy, this is the IDCSA model shown in Figure 2. The Supervisory level adjusts the parameters of the controllers, the control signal is obtained at the Local Control level, to later be incorporated at the plant at the Process level. At the business and planning levels decisions are made at the managerial level, and the control process jobs are carried out at the lowest levels. ![]() Figure 1 shows hierarchical reference architecture to develop a Distributed Control System (SCD), that permits the automation of an industrial plant. The control jobs and information management needed in automation processes can be distributed and expressed through a hierarchical logical structure. The description of the agents in this reference model is based on the MASINA methodology which has an extension of MAS-Common KAD methodology to incorporate other characteristics of agents such as emerging behavior, the reasoning, and the possibility of using intelligent techniques (expert systems, artificial neuronal networks, genetic algorithms, fuzzy logic, etc.) for carrying out their jobs. Our model will be made up of entities called agents, that work together dynamically to satisfy the control systems local and global objectives and whose design can be made completely independent of the system could be developed. In this work, a reference model for Intelligent Distributed Control System (IDCS) based on Agents is proposed. The main preoccupation of the MAS is the coordination between the groups of autonomous agents, perhaps intelligent, to coordinate their objectives, skills, knowledge, tasks, etc. On the other and, a MAS can be defined as a net- work of “problem- solvers” that work together to solve problems that could not be worked out individually. The integrated structure should permit the flow of information at all levels (management, operation, etc.) concerning the plant, the products obtained, and all the relevant information. Moreover, they should take into account production and economic criteria that can be applied as control commands or as part of a plant pro- gramming function. there is great interest in the development of integrated automation systems that permit monitoring different plant operation variables in a broad and dynamic way and to transform such variables in control commands that are later integrated into the plant through actuators.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |