<![CDATA[Saguling Generation Business Unit (GBU) is one of hydro powerplants under PT. Indonesia Power which has vital role to produce and distribute electricity in Indonesia. The demand for electricity in Indonesia, which is fluctuative, force the plant to operate in immediate and responsive pattern. Saguling need 2 minute to connect to the transmission system from its non operating state. Plant response is controlled by manipulating guide vane opening so the water entering the turbine chamber can be maintained. 5.6 % maximum overshoot still occurs in start up process due to manual mechanism. This paper provide a design of control system using Model Predictive Control (MPC) to optimize the plant performance which is indicated by faster response time and reduced overshoot. Neural Network with Back Propagation algorithm is used to model the turbine with guide vane opening as input variable and turbine angular speed as output variable. The model is then used in MPC algorithm to compute the optimum control signals.Keywords: Neural Network, Model Predictive Control, Guide Vane, Cost Function. ]]>
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