چکیده مقاله :
Designing of a PID controller is a very common method for industrial process control and due to its very simple and efficient function; it is used in a wide variety of industrial applications. PID controller to reduce the steady state error and dynamic response of the system is used. PID controller design is an inevitable problem in setting the coefficients need to try a lot of trial and error, therefore the optimization of parameters in this controller is attention of many researcher and there are many methods to find optimal parameters of PID controller. Fast and exactly adjustment of the parameters optimized controller is to create high quality answers. In this paper, an optimized tuning method for PID controller is presented. In this method the PSO algorithm is used to design the parameters of an AVR (Automatic Voltage Regulation) system using various fitness functions. Easy implementation, stable convergence characteristic and high computational efficiency are among advantages of presented method.
منابع و مأخذ:
[1] R. A. Krohling and J. P. Rey, “Design of Optimal
Disturbance Rejection PID Controllers Using Genetic
Algorithm”, IEEE Trans. Evolutionary Computation, Vol.5,
Iss.1, pp.78-82, Feb 2001.
[2] J. G. Ziegler and MB. Nichols., “Optimum Settlings for
Automatic Controllers”, Trans. On ASME., Vol.64 ,
pp.759-768, 1942.
[3] C.C. Hang, K.J. Astrom, W.K. Ho., “Refinements of The
Ziegler- Nichols Tuning Formula”, IEE proceedings-
Control Theory and Applications, Vol.138, No.2, pp.111-
118, March 1991.
[4] A.Visioli, “Tuning of PID Controllers With Fuzzy Logic”,
IEE proc. Control Theory App., Vol.148, pp.1-8, January
2001.
[5] Paul Acarnley, “Tuning PI Speed Controllers for Electric
Drives Using Simulated Annealing”, IEEE International
Symposium on Industrial Electronics, pp.1131-1135, 2002.
[6] E. Salim Ali and S. M. Abd-Elazim., “ Optimal PID Tuning
for Load Frequency Control Using Bacteria Foraging
Optimization Algorithm”, Proceedings of the 14th
International Middle East Power Systems Conference
(MEPCON’10), Cairo University, Egypt, PaperID191,
Dec.19-21, 2010.
[7] A. Ahmadi-Javid., “Anarchic Society Optimization: A
Human Inspired Method, Applied Soft Computing”, In
Proc. of IEEE Congress on Evolutionary Computation, New
Orleans, LA, pp.2586-2592, 2011.
[8] H. Gozde, M.C. Taplamacioglu., “Application Of Artificial
Bee Colony Algorithm in an Automatic Voltage Regulator
(AVR) System”, International Journal on Technical and
Physical Problems of Engineering, Vol.1, No.3, pp.88-92,
2010.
[9] V. Mukherjee, S.P. Ghoshal., “Intelligent Particle Swarm
Optimized Fuzzy PID Controller for AVR System”, Electric
Power Systems Research, Vol.77, pp.1689-1698, 2007.
[10] A.K. Kaviani, H.R. Baghaei, Gh.H. Riahi, “Optimized
Sizing of a Hybrid Wind Power Plant”, 22th International
Electrical Conference, Tehran (PSC), 2007.
[11] M. Abachizadeh, M.R.H. Yazdi, A. Yousefi Koma.,
“Optimal Tuning of PID Controllers Using Artificial Bee
Colony Algorithm”, Advanced Intelligent Mechatronics
Conference, pp.379-384, 2010.
[12] Niknam T, Narimani MR, Azizipanah-Abarghooee R., “A
Multi-Objective Fuzzy Adaptive PSO Algorithm for
Location of Automatic Voltage Regulators in Radial
Distribution Networks”, Int. J. on Control Autom. Syst.,
Vol.10, No.4, pp.772–780, 2012.
[13] Tang Y,Cui M,Hua C,Li L,Yang Y., “Optimum Design of
Fractional Order PI kDl Controller for AVR System Using
Chaotic Ant Swarm”, Expert Syst. Appl., 2012.
[14] Adel A. A. El-Gammal1 Adel A. El-Samahy., “A Modified
Design of PID Controller For DC Motor Drives Using
Particle Swarm Optimization PSO”, 1Energy Research
Centre, University of Trinidad and Tobago UTT (Trinidad
and Tobago), Lisbon, Portugal, Mar.18-20, 2009.
