| Hierarchical intelligence control theory is an important research topic in control domain. With the fast development of computer technologies and intelligent techniques, many control models and analysis colligate methods has been found. New theory and research achievement have been published in resent year. Their applications in engineering have been shown it抯 tremendous powers and huge potentials. In this dissertation, we mainly research and analyze the hierarchical intelligence control system including its modeling, analysis and control etc. and discuss optimal control method for the complex industry produce process. We design a three-level hierarchical intelligence control system for papermaking industry process. It抯 an integrative control system containing the functions of production, attempered and control. The main contributions of the dissertation are as follows: 1. We make an overview on hierarchical intelligence control theory in detail, including generation, development and the last achievement in this field. We also make a discussion on some difficulty and problem for hierarchical intelligence control theory including theory analysis and application. 2. We study harmony-level of hierarchical intelligence control system, analyze Petri net theory, algorithm of attemper and disperse event system in detail. We propose a new method by using matrix theory for Controlled Hybrid Petri (CtrHPN) base on research on CtrHPN. We simulate scene bus-wire by Using Petri net model and construct corresponding immediateness time Petri net (ITPN). This offered a new idea for Petri net research on engineering technology field. 3. Bases on intelligence control and Petri net theory, we discuss application of harmony-level of hierarchical intelligence control to industrial process with the background of practicality industrial processes- papermaking process ration Iv I)~f~ fr~{~Sc moisture expert drive. We implement the modeling and analyze of this process, realize some intelligence function including layout, decision-making and learning etc. 4. Algorithm and design method of forecast control system are discussed. Firstly, we introduce the generation of forecast control and compare general feedback with forecast control and emphatically study MIC. MIC is adopted for papermaking process ration control. Stability and robust of system are analyzed. Because many steps forecast, scroll optimize and feedback emendation are adopted, this system is excellent and strong robustness. It Suits complex industrial production control that can抰 be described by using exact mathematics model. 5. NN-Decoupling intelligence control is discussed. When the model of system is unbeknown, the computation is very complex for the decouple condition of disperse time multi-variable non-linearity system which be constituted by using input-output model. Ration and moisture are importance parameter to appraise quality of paper, but there is strong coupling between them. They influenced each other between regulate variable and regulated variable. Aim at this question author analyze many kinds of decoupling control methods and adopt NN-Decoupling method. We acquire excellent character of decoupling control. This will provide a foundation of improving the robustness of the nonlinear decoupling control system. This indicates it is effective for...
|
PDF Full Text Request