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- W2365748717 abstract "The way of tuning proportional-integralderivative(PID) parameters for hydro-turbine governor is usually based on empirical formula.However,it is difficult to reach the optimum parameters.A novel tuning strategy based on multi-objective genetic algorithm and multi-attribute decision-making(MADM) method was proposed,which aimed at three controller performances simultaneously,which are accurate setpoint tracking,disturbance attenuation,and robust stability.The parallel multi-population genetic algorithm,which improved the intercommunion and migration among each population,and the concordance evolutionary modes,was applied to reach the global optimization.Two exterior archives were taken as containers.The one kept the estimated Pareto optimal set for MADM as possible as the algorithm searched.The other used niched technology and the distance between the two individuals in vector space to adjust the unevenly Pareto front set.An evenly distributed Pareto optimal subset was formed for migration guidance.So the multi-population could search Pareto front in a coordinated fashion.In the subsequent stage,a multi-attribute decision making approach was adopted to find the compromising one among Pareto optimal solutions to the best of algorithm's ability.Simulation result indicates that the performance of hydro-turbine governor could be improved by the proposed method and the method is simple and feasible." @default.
- W2365748717 created "2016-06-24" @default.
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- W2365748717 date "2012-01-01" @default.
- W2365748717 modified "2023-09-23" @default.
- W2365748717 title "Optimization of Hydro-turbine Governor Parameters Based on Parallel Genetic Algorithm With Exterior Archive Method" @default.
- W2365748717 hasPublicationYear "2012" @default.
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