Coordinated Controller Tuning of a Boiler Turbine Unit with New Binary Particle Swarm Optimization Algorithm

Coordinated controller tuning of the boiler turbine unit is a challenging task due to the nonlinear and coupling characteristics of the system.In this paper,a new variant of binary particle swarm optimization （PSO） algorithm,called probability based binary PSO （PBPSO）,is presented to tune the parame...

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Published in国际自动化与计算杂志 Vol. 8; no. 2; pp. 185 - 192
Main Author Muhammad Ilyas Menhas Ling Wang Min-Rui Fei Cheng-Xi Ma
Format Journal Article
LanguageChinese
Published 2011
Subjects
PSO算法
二进制
协调控制器
汽轮机组
涡轮机组
粒子群优化算法
调整参数
锅炉
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Summary:Coordinated controller tuning of the boiler turbine unit is a challenging task due to the nonlinear and coupling characteristics of the system.In this paper,a new variant of binary particle swarm optimization （PSO） algorithm,called probability based binary PSO （PBPSO）,is presented to tune the parameters of a coordinated controller.The simulation results show that PBPSO can effectively optimize the control parameters and achieves better control performance than those based on standard discrete binary PSO,modified binary PSO,and standard continuous PSO.
Bibliography:Coordinated controller tuning of the boiler turbine unit is a challenging task due to the nonlinear and coupling characteristics of the system.In this paper,a new variant of binary particle swarm optimization （PSO） algorithm,called probability based binary PSO （PBPSO）,is presented to tune the parameters of a coordinated controller.The simulation results show that PBPSO can effectively optimize the control parameters and achieves better control performance than those based on standard discrete binary PSO,modified binary PSO,and standard continuous PSO.
Muhammad Ilyas Menhas 1 Ling Wang 1 Min-Rui Fei 1 Cheng-Xi Ma 2 1 Shanghai Key Laboratory of Power-Station Automation Technology,Shanghai University,Shanghai 200072,PRC 2 East China Electric Power Design Institute,Shanghai 200063,PRC
11-5350/TP
Coordinated control; boiler turbine unit; particle swarm optimization （PSO）; probability based binary particle swarm optimization （PBPSO）; controller tuning.
ISSN:1476-8186
1751-8520