Implementation enhancement of AVR control system within optimization techniques

Document Type : Research Paper

Authors

1 Department of Computer Techniques Engineering, Al-esraa University College, Baghdad, Iraq

2 College of Computer Science and Information Technology, Wasit University, Al-Kut, Iraq

Abstract

In this research, Jaya optimization algorithm has been introduced to develop and enhance the performance of the Automatic Voltage Regular system that known as (AVR) system with proposed techniques equilibrium optimizer and rider optimization algorithm which is contributed as additional algorithms to assist PID controller to find the optimum values for the controller in order to improve the performance of the AVR control system to achieve high stability and best for both rising times and settling time and these the best coefficients that made the proposed system work in the greatest performance in addition to that the step response on AVR control system also has been presented in this research and all these techniques implemented on MATLAB Simulink with optimized techniques.

Keywords

[1] P. Begon, F. Pierrot, and P. Dauchez, Fuzzy sliding mode control of a fast parallel robot, Proc. Int. Conf. Robot.
Autom. 1 (1995) 1178–1183.
[2] L. Beji, A. Abichou, and M. Pascal, Tracking control of a parallel robot in the task space, Proc. Int. Conf. Robot.
Autom. 3 (1998) 2309–2314.
[3] S. Cherdchoosilpa, S. Kuntanapreeda and N. Chaiyaratana, MIMO controller design for a parallel manipulator
system: A practitioner’s approach, IEEE Int. Conf. Indust. Tech. 2 (2002) 673–677.
[4] I.-F. Chung, H.-H. Chang, and C.-T. Lin, Fuzzy control of a six-degree motion platform with stability analysis,
IEEE SMC’99 Conf. Proc. 1999 IEEE Int. Conf. Syst. Man. Cyber. 1 (1999) 325–330.
[5] E. Cuevas, V. Osuna and D. Oliva, Evolutionary computation techniques: a comparative perspective, Springer,
2017.
[6] A. A. El-Fergany and M. A. El-Hameed, Efficient frequency controllers for autonomous two-area hybrid microgrid
system using social-spider optimiser, IET Gener. Transm. Distrib. 11 (2017) 637–648.
[7] F. H. Ghorbel, O. Ch´etelat, R. Gunawardana, and R. Longchamp, Modeling and set point control of closed-chain
mechanisms: Theory and experiment, IEEE Trans. Cont. Syst. Tech. 8 (2000) 801–815.[8] F. Ghorbel and R. Gunawardana, A validation study of PD control of a closed-chain mechanical system, Proc.
the 36th IEEE Conf. Decis. Cont. 2 (1997) 1998–2004.
[9] N. Lachhab, F. Svaricek, F. Wobbe and H. Rabba, Fractional order PID controller (FOPID)-toolbox, Euro. Cont.
Conf. (2013) 3694–3699.
[10] S.H. Lee, J. B. Song, W.C. Choi and D. Hong, Position control of a Stewart platform using inverse dynamics
control with approximate dynamics, Mechat. 6 (2003) 605–619.
[11] S.-H. Lee, J.-B. Song, W.-C. Choi and D. Hong, Controller design for a Stewart platform using small workspace
characteristics, IEEE/RSJ Int. Conf. Intel. Robot. Syst. Expand. Soc. Role Robot. Next Millen. 4 (2001) 2184–
2189.
[12] A. Luque-Chang, E. Cuevas, F. Fausto, D. Zald´─▒var, and M. P´erez, Social spider optimization algorithm: modifications, applications, and perspectives, Math. Probl. Eng. 2018 (2018).
[13] N. B. Maan Moutaz, Enhance of the steering control system for electric golf cart using MATLAB with FOPID,
Int. J. Adv. Trends Comput. Sci. Eng. 9 (2020) 4575–4579.
[14] N. B. Maan Moutaz, Enhance of the steering control system for electric golf cart Using MATLAB with FOPID,
Int. J. Adv. Trends Comput. Sci. Eng. 9 (2020) 4575–4579.
[15] L. Maurya, P.K. Mahapatra and A. Kumar, A social spider optimized image fusion approach for contrast enhancement and brightness preservation, Appl. Soft Comput. 52 (2017) 575–592.
[16] J.M. Mendel and R.I.B. John, Type-2 fuzzy sets made simple, IEEE Trans. fuzzy Syst. 10 (2020) 117–127.
[17] N.B. Mohamadwasel, Rider optimization algorithm implemented on the AVR control system using MATLAB with
FOPID, IOP Conf. Ser. Mater. Sci. Eng. 928 (2019) 032017.
[18] N.B. Mohamadwasel and M.A. Abdala, Design of WiMAX network for Istanbul universities with OPNET, Inform.
J. Appl. Mach. Electr. Electron. Comput. Sci. Commun. Syst. 1 (2020) 1–9.
[19] N.B. Mohamadwasel and O. Bayat, Improve DC motor system using fuzzy logic control by particle swarm optimization in use scale factors, Int. J. Comput. Sci. Mob. Comput. 8 (2019) 152–160.
[20] Y.R. Mohammed, N. Basil, O. Bayat and A. Hamid, A new novel optimization techniques implemented on the
AVR control system using MATLAB-SIMULINK, Int. J. Adv. Sci. Tech. 29 (2020) 4515–4521.
[21] S. Ouadfel and A. Taleb-Ahmed, Social spiders optimization and flower pollination algorithm for multilevel image
thresholding: a performance study, Expert Syst. Appl., 55 (2016) 566–584.
[22] P.R. Ouyang, W.J. Zhang and F.X. Wu, Nonlinear PD control for trajectory tracking with consideration of the
design for control methodology, IEEE Int. Conf. Robot. Autom. 4 (2002) 4126–4131.
[23] C. Pernechele, F. Bortoletto, and E. Giro, Neural network algorithm controlling a hexapod platform, IEEE-INNSENNS Int. Joint Conf. Neural Networks. IJCNN 2000. Neural Computing: New Challenges and Perspectives for
the New Millennium, 4 (200) 349–352.
[24] C. Sandra, A.N. Amudhan, A.T. Mathew and A.P. Sudheer, Trajectory tracking of Omni directional robot using
fuzzy controller with visual feedback, Int. Conf. Emerg. Tech. (2020) 1–6.
[25] O.A. Shareef, M.M. Abdulwahid, M.F. Mosleh and R.A. Abd-Alhameed, The optimum location for access point
deployment based on RSS for indoor communication, Int. J. Simul. Syst. Sci. Tech. 20(S1) (2019) 2.1-2.6.
[26] V. Sinlapakun and W. Assawinchaichote, Optimized PID controller design for electric furnace temperature systems
with Nelder Mead Algorithm, 12th Int. Conf. Elect. Engin. Elect. Comput. Telecomm. Inf. Tech. (2015) 1–4.
Volume 12, Issue 2
November 2021
Pages 2021-2027
  • Receive Date: 15 March 2021
  • Revise Date: 04 June 2021
  • Accept Date: 06 July 2021