| In this dissertation, we develop the indexed fuzzy control system which can select the best fit membership functions in a fuzzy environment. Indexed fuzzy control represents a control system closer to human thinking than traditional fuzzy control. Fuzzy control has not been very successful in controlling systems, such as those with varying membership functions for the input variables when certain parameters change. Indexed fuzzy control could be effective in controlling this type of system, particularly when the control system models the operator's control actions. We also apply some stochastic processes into the indexed fuzzy control system in the analysis of problems and in the decision-making process. In the last part of the dissertation, we apply indexed fuzzy control into a distillation factory in an oil refinery. We have built the indexed fuzzy control model and a simulation system to simulate the control process of the factory. |
