Multiple Input Multiple Output ( MIMO ) Process Optimization using Fuzzy GA Clustering
نویسنده
چکیده
Due to the unique characteristics such as handling complex, nonlinear, and sometimes intangible dynamic systems, fuzzy systems are used in the modeling of InputOutput data of the process. The combination of fuzzy rule-based systems with genetic algorithms can lead to very useful descriptions of several optimization and search problems. In this paper, clustering strategy is implemented in the design of a Fuzzy Logic Controller (FLC) and for the determination of the optimal values of clustering parameters such as weighting exponent and the number of clusters; Genetic Algorithm (GA) is used. Water treatment process, a MIMO process, is chosen here as an application example and GA based Minimum Cluster Volume (MCV) algorithm is proposed which minimizes the sum of the volumes of the individual clusters based on the elimination of redundant rules in the fuzzy rule base thereby reducing the rule firing and computational time and improving optimization.
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