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Gas turbine engine has the highest performance in the engine rotation. The performance of the types of modern gas turbines could able up to 44%. In specific applications, gas turbines are used for equipment such as electrical generators, aircraft engines, high-speed boat ... The applications of gas turbine are used to transmit turbine, cabinet pull in eneral. However, there have been no published works on the use of dual turbine. This paper presents an artificial neural network controller to control Double Differential Gas Turbine (DDGT) by use algorithm to synchronize the speed of two turbines at each variable turbine load to reduce low power balance in the system. From the Rowen's model of control for a turbine, the author analyzed and combined with the existing model to construct a dual turbine combinatorial structure coupled by differential coupling. Model-driven control algorithms are used as training grounds for artificial neural networks (ANNs) to replace traditional PID controllers. Because the double tubine construction is strong nonlinear system, modeling is directly transformed from the object model.
About the author
Dr. Mai N.H. born 1969. He received B.E. degree at 1992, MS. degree at 1996 and Ph. Dr. degree at 2008. He is a teacher of DUT now. His interest is electro-mechanic control and modern control.
