| Steam turbine Digital Electro-Hydraulic (DEH) control system is the most important to ensure safe and economic operation of the unit. It is possible to realize the performance prediction, optimization control and condition monitor as well as fault diagnosis for steam turbine control system, identifying all components'parameters of governing system. The dissertation researched on two stochastic algorithms, one of which is genetic algorithms and the other is particle swarm optimization algorithm. Aiming at the two algorithms'defects, some modifications have been correspondingly proposed. By typical numerical examples, the results showed that the modified algorithms effectively improved the speedy and accuracy of calculation. Finally, the hybrid algorithm consisted of improved genetic algorithm and modified particle swarm algorithm is used for parameter identification of all DEH components. The identification accuracy is satisfactory.
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