Two New Intelligent Control Systems

Intelligent control has obtained great success in modern industrial controls, so it has gained the specialists'great attention, but because it's just in the development stage, the research in various aspects is not mature. Especially, in multi-source and isomerous environment, the design of the intelligent controller is lack of effective methods. To overcome these problems, this paper proposed two new proposals.The main contributions of our study are as follows:1)A control algorithm based on information fusion estimation is proposed. It is on the basis of the traditional control theory and uses the modern multi-source's intelligent information processing ways to fusion all the information, and also follows the tracks of the output of the MIMO systems, and got good results.2)A new validity index is proposed. The validity is proposed based on the fuzzy membership, it not only can be used in FCM and HCM clustering algorithm, and also it can effectively determine the number of the data.3)A new fuzzy control algorithm based on clustering is proposed. For a fuzzy control system, the key of the design is to build the fuzzy control rules. The algorithm uses the cluster validity index to make sure the numbers of the rules, and then get the rules by clustering. For a traditional fuzzy control, the build of the fuzzy rules is got by Human Experience, so it has great subjectivity. But our algorithm has avoided the appearance of this kind of problems.4)In different control background, we carried simulation experiment by the two new proposed algorithms, and get good control effect.