| As the most general control method in industrial control, PID controller has many advantages, such as its simple structure, strong robustness, stable state without steady-state error and easy to operate etc. Thus its characters make PID control has been used in industry for a long time. But the limitation for the application of complex controlled object is one of important factors of restricting its development. With the development of IC (intelligent control), fuzzy control theory has been mature and fuzzy control technology has been come into being. This brings new vitality for the development of PID control. During the combination course of fuzzy control and PID control, on the one hand the coming of fuzzy control remedies the shortage of PID control for complex object.For example, the object with great delay, nonlinear and without accurate mathematics model etc. On the other hand, the combination of PID control and fuzzy control gets improvement in rough control quality and low steady-state precision in great degree. These characters make up for each other. This makes Fuzzy-PID controller have fuzzy control advantages of flexibility, strong adaptability, good rapidity and PID control characters of high control precision. Further the application in control field has also shown that Fuzzy-PID control has better performance. It becomes an important branch of IC development.On the base of studying the development course of the PID control system and its characters, in this thesis aimed at the defect of the pure Fuzzy-PID composite control we use RS (rough sets) theory to extract the fuzzy rules reasonably and make MEA (mind evolutionary algorithm) as a parameter optimization for PID controller. By this method the entire control system performance is raised further.RS can analyse, inference and excavate the implicit knowledge and rules from numbers of data. It is resolving this difficult problemthat intelligent control handles the knowledge, especially the uncertain knowledge. RS is promoting IC forward. The original data can be handled by use of knowledge reduction of RS in the thesis. The fuzzy rules can be extracted from data directly, which reduces the difficulty of obtaining rules in fuzzy controller. In the course of attribute reduction, a modified attribute reduction algorithm is put forward in this thesis, which is based on the redefined significance of attributes about the independence degree and information entropy, at the beginning of relative cores. The sample proves the algorithm is viable and the calculate space has been certain reduced.Every parameter determination of PID controller is the key that if it can reach the satisfactory control effect. A kind of new evolution algorithm method —MEA is applied in this thesis to optimize the parameters of PID. MEA carries on research globally and locally by similartaxis and dissimilation operators. The ability of convergence performance and efficiency is obviously higher than GA (genetic algorithm). The PID parameter optimization algorithm based on MEA has the advantages of rapid convergence speed, highcalculate precision and convenient operation.In this thesis two optimization methods introduced in the upper article are blend in tradition Fuzzy-PID composite control to realize the Fuzzy-PID control system intelligent. Aimed the defect of switching course of this controller, a switching algorithm based on fuzzy rules is used to modify. The simulation result proved this method superiority on improving the controller performance.Eventually a composite Fuzzy-PID control system with fuzzy controller based on RS and PID controller based on MEA has been designed in the thesis. And make an experiment on a complex and unlinear object in the industrial course, the simulation results show control performance of this intelligent control system is super. It is a designing than can make control effect satisfying. |
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