Intelligent Control of Complex Nonlinear Systems with Electric Power Application

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9301168 Mohler This research is on "intelligent control systems" with electric power applications. Model-based nonlinear adaptive and optimal control methodologies are to be used. Linear, bilinear, and higher-order nonlinear approximations may be used. The potential role of artificial neural networks as a means to adapt to state space changes resulting from switching events or faults will be studied. Fast adaptation to structural changes of the system being controlled is a key objective of the research. The investigator proposes a hierarchial configuration in which an upper level consists of a statistical detector and an artificial neural network classifier. The combination would act to select the optimal control configuration to respond to changing power system conditions. ***