The Research On The Application Of Bluetooth And Multi-agent Technology In The Workshop Control System

In order to satisfy the various demands of market rapidly and the severity of competition, the manufacturing enterprises are required to not only yield products with high-quality and low-cost, but also adapt the unpredictable changing environment automatically and increase rates of new product introduction. However, with the change of the interior and exterior environment in modern manufacturing system, the manufacturing system is becoming more and more complex. To solve the contradiction, this paper introduces the concept of agent in the area of Artificial Intelligent into manufacturing field and builds up some dynamic modeling of manufacturing system based on multi-agent system. These modeling can fulfill the distributing and autonomy of system and settle some problems of the traditional centralized and hierarchical structure.On the basis of analyzing Multi-agent technology thoroughly, this paper establishes a mapping of work piece and manufacturing equipments to a series of agents, and builds up four dynamic models of manufacturing system: domain based hierarchical structure, topology of cascading agent structure, proximity relation structure and bus-based network structure. This paper also illuminates the function of agents in these models and the mechanism of these models.Considering the actual situation of manufacturing, using wireless communication technology is the best way to accomplish the communication of multi-agent system. Bluetooth is the criterion of short distance of wireless communication. Therefore, we can use Bluetooth to realize the communication of agents. This paper successfully develops the communication plat based on Bluetooth, through which can receive and transmit the datum and information wirelessly and sets up manufacturing system control constitution based on the Bluetooth communication plat.In the multi-agents systems about manufacturing, whether an agent can adapt in the undefined environment and learn from the background knowledge is essential. To improve the adaptation of multi-agent system, we can strengthen the ability of learning from the environment. This paper analyzes the Reinforcement Learning in the field of Artificial Intelligent and puts forward improved reinforcement learning arithmetic that combines Reinforcement Learning with background knowledge, which can speed the Reinforcement Learning and satisfy the demand of real time. This paper detailedly analyzes the arithmetic of learning and finally uses a simple example to illuminate the feasibility of the improved reinforcement learning arithmetic.