期刊论文详细信息
Energies
Governor Design for a Hydropower Plant with an Upstream Surge Tank by GA-Based Fuzzy Reduced-Order Sliding Mode
Chang Xu2  Dianwei Qian3  Ånund Killingtveit1 
[1] id="af1-energies-08-12376">College of Energy and Electricity, Hohai University, No.1 Xikang Road, Gulou District, Nanjing 210098, Chi;College of Energy and Electricity, Hohai University, No.1 Xikang Road, Gulou District, Nanjing 210098, ChinaSchool of Control and Computer Engineering, North China Electric Power University, No.2 Beinong Road, Changping District, Beijing 102206, China;
关键词: hydropower generation;    governor;    sliding mode control;    order reduction;    fuzzy logic;    genetic algorithm;   
DOI  :  10.3390/en81212376
来源: mdpi
PDF
【 摘 要 】

This paper investigates governor design by reduced-order sliding mode for a hydropower plant with an upstream surge tank. The governing system is made up of a tunnel, a surge tank, a penstock, a wicket gate and servomechanism, a governor, a hydro-turbine and a grid. Concerning the components of the governing system, their mathematic models are established. Then, these models are interconnected to simulate the governing system. From the viewpoint of state space in modern control theory, the governing system is partially observed, which challenges the governor design. By introducing an additional state variable, the control method of reduced-order sliding mode is proposed, where the governor design is based on a reduced-order governing system. Since the governor is applied to the original governing system, the system stability is analyzed by means of the small gain theorem. An genetic algorithm is employed to search a group of parameters of the predefined sliding surface, and a fuzzy inference system is utilized to decrease the chattering problem. Some numerical simulations are illustrated to verify the feasibility and robustness of the control method.

【 授权许可】

CC BY   
© 2015 by the authors; licensee MDPI, Basel, Switzerland.

【 预 览 】
附件列表
Files Size Format View
RO202003190002736ZK.pdf 8333KB PDF download
  文献评价指标  
  下载次数:12次 浏览次数:21次