Design of a fractional-order PID controller for a pumped storage unit using a gravitational search algorithm based on the Cauchy and Gaussian mutation

被引:141
作者
Li, Chaoshun [1 ]
Zhang, Nan [1 ]
Lai, Xinjie [1 ]
Zhou, Jianzhong [1 ]
Xu, Yanhe [1 ]
机构
[1] Huazhong Univ Sci & Technol, Sch Hydropower & Informat Engn, Wuhan 430074, Peoples R China
基金
中国国家自然科学基金;
关键词
Pumped storage unit; Pump turbine governing system; Fractional order PID controller; Cauchy mutation; Gravitational search algorithm; DIFFERENTIAL EVOLUTION; OPTIMIZATION; PARAMETERS; SYSTEMS; IDENTIFICATION; ENSEMBLE; PLANT;
D O I
10.1016/j.ins.2017.02.026
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
A pumped storage unit (PSU) is more difficult to control compared to a conventional hydropower generation unit due to the frequent switching of working conditions and the S-shaped characteristics of pump turbine. The traditional proportional integral derivative (PID) controller typically cannot easily provide high quality control. To overcome these difficulties, a fractional-order PID (FOPID) controller is designed for a PSU in this study. Although the FOPID controller is more effective compared to the traditional PID controller, it is more complex to optimize the parameters of this controller for a pump turbine governing system (PTGS). Thus, a gravitational search algorithm combined with the Cauchy and Gaussian mutation, named as CGGSA, is proposed and used to optimize the FOPID controller parameters. The experimental results indicate that the CGGSA has shown excellent optimization ability compared with some popular meta-heuristics on benchmark functions. Results have also proved that the FOPID-CGGSA controller shows significant advantages over other PID-type controllers with different optimization strategies. Meanwhile the optimally designed controller has shown great potential to improve the control quality of PTGS under multiple water heads. (C) 2017 Elsevier Inc. All rights reserved.
引用
收藏
页码:162 / 181
页数:20
相关论文
共 45 条
[1]   Improving the performance of differential evolution algorithm using Cauchy mutation [J].
Ali, Musrrat ;
Pant, Millie .
SOFT COMPUTING, 2011, 15 (05) :991-1007
[2]   Modeling of pumped-storage generation in sequential Monte Carlo production simulation [J].
Allan, RN ;
Li, R ;
Elkateb, MM .
IEE PROCEEDINGS-GENERATION TRANSMISSION AND DISTRIBUTION, 1998, 145 (05) :611-615
[3]  
[Anonymous], 1942, T ASME
[4]   Adaptive acceleration coefficients for a new search diversification strategy in particle swarm optimization algorithms [J].
Ardizzon, Guido ;
Cavazzini, Giovanna ;
Pavesi, Giorgio .
INFORMATION SCIENCES, 2015, 299 :337-378
[5]   ITAE Optimal Sliding Modes for Third-Order Systems With Input Signal and State Constraints [J].
Bartoszewicz, Andrzej ;
Nowacka-Leverton, Aleksandra .
IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 2010, 55 (08) :1928-1932
[6]   Design of fractional-order PIλDμ controllers with an improved differential evolution [J].
Biswas, Arijit ;
Das, Swagatam ;
Abraham, Ajith ;
Dasgupta, Sambarta .
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE, 2009, 22 (02) :343-350
[7]   A maiden application of gravitational search algorithm with wavelet mutation for the solution of economic load dispatch problems [J].
Chatterjee, A. ;
Ghoshal, S. P. ;
Mukherjee, V. .
INTERNATIONAL JOURNAL OF BIO-INSPIRED COMPUTATION, 2012, 4 (01) :33-46
[8]   Improved gravitational search algorithm for parameter identification of water turbine regulation system [J].
Chen, Zhihuan ;
Yuan, Xiaohui ;
Tian, Hao ;
Ji, Bin .
ENERGY CONVERSION AND MANAGEMENT, 2014, 78 :306-315
[9]   A real-coded genetic algorithm with a direction-based crossover operator [J].
Chuang, Yao-Chen ;
Chen, Chyi-Tsong ;
Hwang, Chyi .
INFORMATION SCIENCES, 2015, 305 :320-348
[10]   Novel Gaussian quantum-behaved particle swarm optimiser applied to electromagnetic design [J].
Coelho, L. S. .
IET SCIENCE MEASUREMENT & TECHNOLOGY, 2007, 1 (05) :290-294