A Review on Hybrid Controller Using Soft Computing Algorithms

Lokesh Kumar Agrawal^1, , Bhavesh Kumar Chauhan² and G. K. Benerjee¹

¹Department of Electrical Engineering, IFTM University, Moradabad(U.P.), India

²Department of Electrical Engineering, ABESIT, Ghaziabad (U.P.), India

Cite this paper:
Lokesh Kumar Agrawal, Bhavesh Kumar Chauhan and G. K. Benerjee. A Review on Hybrid Controller Using Soft Computing Algorithms. American Journal of Electrical and Electronic Engineering. 2016; 4(2):49-61. doi: 10.12691/ajeee-4-2-2

Abstract

Aadaptability and self-organization of a system is two key factors, when it comes to how well the system is surviving for the changes to the environment and how these work within the plant. Different tuning methods and soft computing techniques improve these two factors in controllers. Considering the increasing complexity of dynamic systems along with their need for feedback controls, using more complicated controls has become necessary and these techniques can be a suitable response to this necessity. This paper briefly describes a review on different techniques used for PID tuning as well as soft computing algorithm for hybrid controllers. This paper provides a comprehensive reference source for people working with hybrid controllers.

Keywords:
PI Controller PID Controller FLC Neuro-fuzzy system Tuning ANFIS

This work is licensed under a Creative Commons Attribution 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

References:

[1]	Emad Ali, “Automatic Fuzzy Tuning of Proportional-Integral Controller Based on Time-Domain Specification”, Journal of King Saud University, 17, Eng. Sci. (2), 171-196, 2005.
[2]	Hari Om Bansal, Rajamayyoor Sharma, P. R. Shreeraman, “PID Controller Techniques: A Review”, Journal of Control Engineering and Technology, Volume 2, Issue 4, October 2012, Pages 168-176.
[3]	Amit Kr Singh, Manjari Mehrotra, and AK Pandey, “Improvement of the Performance of Different Order System with Adaptive Fuzzy PID Controller”, VSRD-IJEECE, Volume 2, Issue 2, 27-38, 2012.
[4]	Prajakta S.Taywade, K.N.Kasat, “A Review on Implementation of Neuro-fuzzy PID Controller using FPGA”, International Journal of Engineering Research and General Science, Volume 3, Issue 1, January-February 2015, Pages 1145-1152.
[5]	Y.M. Zhao, W.F. Xie, X.W. Tu , “Performance-based parameter tuning method of model-driven PID control systems”, ISA Transactions, Volume 51, Issue 3, May 2012, Pages 393-399.
[6]	Mohamed S. Zaky, “A self-tuning PI controller for the speed control of electrical motor drives”, Electric Power Systems Research, Volume 119, February 2015, Pages 293-303.
[7]	Dao Thanh Liem, Dinh Quang Truong, Kyoung Kwan Ahn, “A torque estimator using online tuning grey fuzzy PID for applications to torque-sensorless control of DC motors”, Mechatronics, Volume 26, March 2015, Pages 45-63.
[8]	Juing-Shian Chiou, Shun-Hung Tsai, Ming-Tang Liu, “A PSO-based adaptive fuzzy PID-controllers”, Simulation Modelling Practice and Theory, Volume 26, August 2012, Pages 49-59.
[9]	Rajani K. Mudi, Chanchal Dey, Tsu-Tian Lee, “An improved auto-tuning scheme for PI controllers”,ISA Transactions, Volume 47, Issue 1, January 2008, Pages 45-52.
[10]	Chanchal Dey, Rajani K. Mudi, “An improved auto-tuning scheme for PID controllers,”ISA Transactions, Volume 48, Issue 4, October 2009, Pages 396-409.
[11]	Muguo Li, Da Liu, “A Novel Adaptive Self-turned PID controller based on Recurrent-Wavelet-Neural-Network for PMSM Speed Servo Drive System”, Procedia Engineering, Volume 15, 2011, Pages 282-287.
[12]	Muawia A. Magzoub, Nordin B. Saad, Rosdiazli B. Ibrahim, “Efficiency Improvement of Induction Motor Variable Speed Drive Using a Hybrid Fuzzy-fuzzy Controller”, Energy Procedia, Volume 75, August 2015, Pages 1529-1535.
[13]	Sakuntala Mahapatra, Raju Daniel, Deep Narayan Dey, Santanu Kumar Nayak, “Induction Motor Control Using PSO-ANFIS”, Procedia Computer Science, Volume 48, 2015, Pages 753-768.
[14]	Sharda Patwa, “Control of starting current in three phase induction motor using fuzzy logic controller,” International Journal of Advanced Technology in Engineering and Science, Volume 1,Issue 12, pages 27-32, December 2013.
[15]	P.M.Menghal, A.Jaya Laxmi, “Adaptive Neuro Fuzzy based dynamic simulation of induction motor drives”, IEEE International Conference Fuzzy Systems (FUZZ-IEEE 2013) 7-10 July 2013.
[16]	P.M.Menghal, A.Jaya Laxmi, N.Mukhesh, “Dynamic simulation of induction motor drive using neuro controller”, International Journal on Recent Trends in Engineering and Technology, Volume 10, Issue 2, January 2014.
[17]	Ahmed J. Fattah, Ikhlas Abdel-Qader, “Performance and Comparison Analysis of Speed Control of Induction Motors using Improved Hybrid PID-Fuzzy Controller”, Electro/Information Technology (EIT), 2015 IEEE International Conference on Year 2015, Pages 575-580.
[18]	Mohammed Abdelbar Shamseldin and Adel A. EL-Samahy, “Speed Control of BLDC Motor by using PID Control and Self-tuning Fuzzy PID Controller”, 15th International Workshop on Research and Education in Mechatronics (REM), September 9-11, 2014, IEEE Conference Publication.
[19]	Bemal K. Bose, “Modern Power Electronics and Ac Drives”, 1st ed., Bernard Goodwin, Ed. USA: Prentice Hall, Inc., 2002.
[20]	Raul Rojas, “Neural Network a Systematic Introduction”, Springer-Verlag, Berlin 1996.