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Research On Autonomous Control Theory And Key Technologies Of Manufacturing Equipment Based On Embedded System

Posted on:2010-04-03Degree:DoctorType:Dissertation
Country:ChinaCandidate:J H ZhangFull Text:PDF
GTID:1101360275999031Subject:Communication and Information System
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Manufacturing equipment is the key basic element of a modern manufacturing system. Its function strength and performance quality determines the success or failure of advanced manufacturing modes. At present, the research on manufacturing process planning, coordination and collaboration mainly focuses on the system level and lacks in-depth study on how to address the heterogeneous nature of the equipment, the complex interaction and collaboration between the equipment, as well as search for collaboration capacity up to the heterogeneous resources. The research on how digital manufacturing equipment to adapt to the network-based digital manufacturing environment most remains in the settlement of network communication, remote control and data exchange. It pays very little attention to the bottom digital equipment's initiative aware and adapting to complex dynamic manufacturing environment. In this paper, the embedded technology, network and communication technology and theory of intelligence and technology are used to do research on manufacturing equipment in manufacturing systems to adapt to the networked digital environment, in order to achieve manufacturing equipment's capacities of self-adapting to the manufacturing environment, self-controlling its action on the processing, and integrating with heterogeneous manufacturing equipment. This paper has carried out the following research:(1) The connotation of autonomous control of numerical control equipment is studied. And it is introduced and described from three aspects of the NC equipment self-discipline control concept, conceptual model and features. Also, through the analysis of network-based digital manufacturing environment, numerical control equipment autonomous control abilities are studied. The paper does the detailed analysis of NC autonomous control systematically from points of the static model (level and structure of the modules) and the dynamic model (workflow and information flow). The research on manufacturing equipment autonomous control theory and key technologies based on embedded system is carried out based on the connotation and analysis of function and model of manufacturing equipment. (2) On the basis of the study on the mathematical model of the closed-loop location control, the analysis of contour error in the process motion control and error calculation model, according to the lack of using normal contour error model not to calculate contour error of curve in real-time, combining real-time contour error compensation control strategy and fuzzy logic theory, the fuzzy logic and real-time contour error calculation based self-discipline control strategy is proposed. The strategy can be based on the absolute value of the curve contour error and changes in contour curvature to independently adjust the feed rate, and to calculate in real-time contour error approximation. Under the condition of the simulation experiments of two-axis contour control movement with second-order axis closed-loop position mathematical model and the axis position controlled by the conventional controller, simulation results show that the effectiveness of the strategy.(3) Based on the analysis of resource sharing theory including resource sharing concept model, control modes and the level of resource sharing, the characteristics of numerical control equipment in the network-based digital manufacturing environment are described. And the numerical control equipment manufacturing unit resource model and networked manufacturing resource models based on the numerical control equipment manufacturing unit are proposed. The study on autonomous control strategy of numerical control equipment in network-based digital environment is done. It is the autonomous collaborative strategy of NC equipment resource sharing. The collaboration strategy applies processing tasks-driven consensus mechanism. Through the autonomous collaboration strategy, CNC manufacturing equipment has the autonomy capability to adapt to the network-based digital manufacturing environment.(4) On the basis of research on autonomous control theory of numerical control equipment, combining modern information technology and for the aim of network information and numerical control resource sharing under network for numerical control surpporting system platform, the research on key technologies of embedded system-based CNC equipment self-discipline control are done from three aspects of the embedded technology-based manufacturing equipment network communication technology, the integration technology with network-based digital manufacturing environment and numerical control manufacturing equipment self-discipline control architecture based on embedded system. Research on XML-based information integration of manufacturing equipment is done and XML Schema of manufacturing equipment information is given. And according to embedded technology based numerical control self-discipline control architecture design requirements and design patterns, two kinds of NC equipment self-discipline control architecture based on embedded technology are proposed. That is self-discipline control basic architecture and network self-discipline control service architecture of numerical control manufacturing equipment based on embedded system.(5) Based on the above manufacturing equipment autonomous control theory and key technologies research based on embedded system and according two types of embedded technology-based numerical control equipment self-discipline control architecture, embedded system based numerical control equipment self-discipline control basic system and embedded system based NC equipment network self-discipline control service system are studied. It covers the system function target, hardware and software architecture, the key technologies.
Keywords/Search Tags:Network-based digital manufacturing, embedded system, manufacturing equipment, autonomous control, resource sharing
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