Application Improved particle swarm algorithm in parameter optimization of Hydraulic turbine Governing systems
The dynamic characteristics of a hydraulic turbine governing system is determined by the parameters of the hydraulic turbine governor.There are several drawbacks of the conventional particle swarm algorithm in parameter optimization,such as low speed of convergence,low accuracy and being inclined to result in partial optimization during the process of optimization.This paper introduced concave function form as the inertia weight into the conventional particle swarm algorithm and established a mathematical model for a Francis hydraulic turbine governing system.The index of ITAE was chosen as the objective function in the model and the modified particle swarm algorithm was applied into the parameter optimization of the hydraulic turbine governing system.Meanwhile,the performance of the optimization process of the modified particle swarm algorithm was compared with the conventional parameter optimization methods by means of simulation experiment.The results show superior performance of control system can be obtained from the optimization results of the modified particle swarm algorithm.
Particle swarm optimization The concave and convex function The hydraulic turbine governing system Parameter optimization
Guo Lei
Jiangxi Province Key Laboratory of precision drive & control,Nanchang Institute of Technology Nanchang,China
国际会议
重庆
英文
1135-1138
2017-10-03（万方平台首次上网日期，不代表论文的发表时间）