Optimal pid controller design based on PSO-RBFNN for wind turbine systems

Energies

Volumn 7, Issue 1, 2014, Pages 191-209

  Perng, Jau Woei ^a   Chen, Guan Yan ^a   Hsieh, Shan Chang ^a  

^a NATIONAL SUN YAT SEN UNIVERSITY   (Taiwan)

Author keywords

Particle swarm optimization (PSO); Proportional integral derivative (PID) control; Radial basis function (RBF); Stability boundary; Time delay; Wind turbine

Indexed keywords

COMPUTER AIDED SOFTWARE ENGINEERING; CONTROLLERS; DELAY CONTROL SYSTEMS; ELECTRIC CONTROL EQUIPMENT; FUNCTIONS; OPTIMIZATION; PARTICLE SWARM OPTIMIZATION (PSO); RADIAL BASIS FUNCTION NETWORKS; STABILITY; THREE TERM CONTROL SYSTEMS; TIME DELAY; TWO TERM CONTROL SYSTEMS; WIND TURBINES;

INTELLIGENT ALGORITHMS; OPTIMAL OPERATING POINT; PID CONTROLLER DESIGN; PROPORTIONAL INTEGRAL DERIVATIVE CONTROL; PROPORTIONAL INTEGRAL DERIVATIVE CONTROLLERS; RADIAL BASIS FUNCTION NEURAL NETWORKS; RADIAL BASIS FUNCTION(RBF); STABILITY BOUNDARIES;

PROPORTIONAL CONTROL SYSTEMS;

EID: 84893360876     PISSN: None     EISSN: 19961073     Source Type: Journal    
DOI: 10.3390/en7010191     Document Type: Article

References (24)

1. Jauch, C.; Islam, S.M.; Sorensen, P.; Jensen, B.B. Design of a wind turbine pitch angle controller for power system stabilization. Renew. Energy 2007, 85, 2334-2349.
2. Vidal, Y.; Acho, L.; Luo, N.; Zapateiro, M.; Pozo, F. Power control design for variable-speed wind turbines. Energies 2012, 5, 3033-3050.
3. Wang, J.; Tse, N.; Gao, Z. Synthesis on PI-based pitch controller of large wind turbines generator. Energy Convers. Manag. 2011, 52, 1288-1294.
4. Li, Y.; Sheng, A.; Wang, Y. Synthesis of PID-type controllers without parametric models: A graphical approach. Energy Convers. Manag. 2008, 49, 2392-2402.
5. Bozorg, M.; Termeh, F. Domains of PID controller coefficients which guarantee stability and performance for LTI time-delay systems. Automatica 2011, 47, 2122-2125.
6. λDμ controller. Commun. Nonlinear Sci. Numer. Simul. 2012, 17, 979-991.
7. Madady, A.; Alikhani, H.R.R. Stabilization of control loops consisting of FOPDT process and parameter-dependent PID controller. J. Process Control 2012, 22, 1688-1701.
8. Soylemez, M.T.; Munro, N.; Baki, H. Fast calculation of stabilizing PID controllers. Automatica 2003, 39, 121-126.
9. Camblong, H. Digital robust control of a variable speed pitch regulated wind turbine for above rated wind speeds. Control Eng. Pract. 2008, 16, 946-958.
10. Geng, H.; Yang, G. Output power control for variable-speed variable-pitch wind generation systems. IEEE Trans. Energy Convers. 2010, 25, 494-503.
11. Corcuera, A.D.D.; Pujana-Arrese, A.; Ezquerra, J.M.; Segurola, E.; Landaluze, J. H-infinity based control for load mitigation in wind turbines. Energies 2012, 5, 938-967.
12. Poultangari, I.; Shahnazi, R.; Sheikhan, M. RBF neural network based PI pitch controller for a class of 5-MW wind turbines using particle swarm optimization algorithm. ISA Trans. 2012, 51, 641-648.
13. Lee, C.M.; Ko, C.N. Time series prediction using RBF neural networks with a nonlinear time-varying evolution PSO algorithm. Neurocomputing 2009, 73, 449-460.
14. Lin, W.M.; Hong, C.M.; Cheng, F.S. Design of intelligent controllers for wind generation system with sensorless maximum wind energy control. Energy Convers. Manag. 2011, 52, 1086-1096.
15. Yilmaz, A.S.; Özer, Z. Pitch angle control in wind turbines above the rated wind speed by multi-layer perceptron and radial basis function neural networks. Expert Syst. Appl. 2009, 36, 9767-9775.
16. Chen, Y.; Xu, J.; Yang, B.; Zhao, Y.; He, Y. A novel method for prediction of protein interaction sites based on integrated RBF neural networks. Comput. Biol. Med. 2012, 42, 402-407.
17. Hasanien, H.M.; Muyeen, S.M. Design optimization of controller parameters used in variable speed wind energy conversion system by genetic algorithms. IEEE Trans. Sustain. Energy 2012, 3, 200-208.
18. Das, D.C.; Roy, A.K.; Sinha, N. GA based frequency controller for solar thermal diesel-wind hybrid energy generation/energy storage system. Electr. Power Energy Syst. 2012, 43, 262-279.
19. Anderson, C.G.; Richon, J.B.; Campbell, T.J. An aerodynamic moment-controlled surface for gust load alleviation on wind turbine rotors. IEEE Trans. Control Syst. Technol. 1998, 6, 577-595.
20. FAST: An Aeroelastic Computer-Aided Engineering (CAE) Tool for Horizontal Axis Wind Turbines. Available online: http://wind.nrel.gov/designcodes/simulators/fast (accessed on 3 January 2014).
21. Shi, Y.; Eberhart, R.C. Particle Swarm Optimization: Developments, Applications and Resources. In Proceedings of the 2001 Congress on Evolutionary Computation, Seoul, Korea, 27-30 May 2001; Volume 1, pp. 81-86.
22. Shi, Y.; Eberhart, R.C. Tracking and Optimizing Dynamic Systems with Particle Swarms. In Proceedings of the 2001 Congress on Evolutionary Computation, Seoul, Korea, 27-30 May 2001; Volume 1, pp. 94-97.
23. Fang, H.; Chen, L.; Shen, Z. Application of an improved PSO algorithm to optimal tuning of PID gains for water turbine governor. Energy Convers. Manag. 2011, 52, 1763-1770.
24. Lin, C.T.; Lee, C.S.G. Neural Fuzzy Systems: A Neuro-Fuzzy Synergism to Intelligent Systems, International ed.; Prentice Hall: Taipei, Taiwan, August 2003; pp. 328-330.