Design of Tuning Mechanism of PID Controller for Application in three Phase Induction Motor Speed Control
( Vol-4,Issue-11,November 2017 )

Alfred A. Idoko, Iliya. T. Thuku, S. Y. Musa, Chinda Amos


PID Controller, Modelling of Induction Motor, Design of PID Tuning Software.


This paper presents a design of tuning mechanism of Proportional Integral Derivative Controller for application in three phase induction motor speed controls. It demonstrates, in detail, how to employ the MatLab tool so as to search efficiently for the optimal PID controller parameters within a mechanism system. The proposed approach has superior features, including: easy implementation; stable convergence characteristics; and less computational effort. Three phase induction motors has complex mathematical modelling which makes it difficult to design the speed controller. Software PID Tuning Mechanismwas developed herein and used to obtain both the initial PID parameters under normal operating conditions and the optimal parameters of PID control under fully-loaded conditions. The proposed PID controller Tuning Mechanism will automatically tune its parameters within these ranges. In order to prove the performance of the proposed tuning mechanism for the PID controller, a three phase asynchronous motor was modelled in MATLAB, the transfer function was obtained using the software and a controller was designed using PID. The modelling and simulations results show the potential of the proposed controller to be very efficient.

ijaers doi crossref DOI:


Paper Statistics:
  • Total View : 63
  • Downloads : 6
  • Page No: 138-147
Cite this Article:
Show All (MLA | APA | Chicago | Harvard | IEEE | Bibtex)

[1] Singh, B. and G. Choudhuri, Fuzzy Logic Based Speed Controllers For Vector Controlled Induction Motor Drive IETE Journal of Research 2002. 48: p. 6.
[2] Z. Q. Zhu, Y.P., D. Howe, S. Iwasaki, R. Deodhar, and A. Pride, Analysis of Electromagnetic Performance of Flux-Switching Permanent-Magnet Machines by Nonlinear Adaptive Lumped Parameter Magnetic Circuit Model. IEEE TRANSACTIONS ON MAGNETICS, 2005. 41(11): p. 11.
[3] Chan, C.C. The State of the Art of Electric,Hybrid, and Fuel Cell Vehicles. in Proceedings of the IEEE 2007.
[4] ZL, G., A particle swarm optimization approach for optimum design of PID controller in AVR system. IEEE Trans Energy Convers, 2004. 19: p. 91-384.
[5] Chih-Cheng Kao, C.-W.C., Rong-Fong Fung, The self-tuning PID control in a slider–crank mechanism system by applying particle swarm optimization approach. Mechatonics, 2006. 16(8): p. 513-522.
[6] Gaing, Z.-L., A Particle Swarm Optimization Approach for Optimum Design of PID Controller in AVR System. IEEE Transactions on Energy Conversion, 2004. 19(2).
[7] Ang, K.H., G. Chong, and Y. Li, PID control system analysis, design, and technology IEEE Transactions on Control Systems Technology, 2005. 13(4): p. 559-576.
[8] Rujisak Muangsong, D.K., Anak Khantachawana, Panadda Niranatlumpong, A particle swarm optimization approach for optimal design of PID controller for position control using Shape Memory Alloys in Electrical Engineering / Electronics, Computer, Telecommunication and Information Technology2008, IEEE: Krabi Thailand.
[9] Saghafinia, A., H. Ping, and M. Uddin, Designing Self-Tuning Mechanism On Hybrid Fuzzy Controller For High Performance And Robust Induction Motor Drive. International Journal of Advanced Technology & Engineering Research, 2013. 3: p. 65-72.
[10] R.Arulmozhiyal and K. Baskaran, Space Vector pulse Width Modulation Based Speed Control of Induction Motor using Fuzzy PI Controller. international Journal of Computer and Electrical Engineering 2009. 1: p. 5-7.
[11] Chih-Cheng Kao, C.-W.C., Rong-Fong Fung, The self-tuning PID control in a slider–crank mechanism system by applying particle swarm optimization approach, in Mechanical and Automation Engineering2006, National Kaohsiung First University of Science and Technology,: Taiwan. p. 513-522.
[12] Liu Y, Z.J., Wang S. Optimization design based on PSO algorithm for PID controller. in Proc Fifth World Congr on Intelligent Control and Automation,. 2004. Instabul Turkey.
[13] Shi, Y.H. and R.C. Eberthart, A Modified Particle Swarm Optimizer. IEEE International Conference on Evolutionary Computation, 1998: p. 7.
[14] Noordin, M.A.B.M., scaler control of three phase induction motor 2007, University Teknikal: Malaysia.
[15] Raji, C.T., S.P. Stivastava, and P. Agarwal, Particle Swarm and Fuzzy Logic Based Optimal Energy control of Induction Motor for a Hoist Load Diagram. International Journal of Computer Science, 2009. 36: p. 17-25.
[16] Pillay, P. and R. Krishnan, Modeling, Simulation, and Analysis of Permanent-Magnet Motor Drives , Part I: The Permanent-Magnet Synchronous Motor Drive. IEEE Transaction on Industry Application, 1989. 25(2): p. 9.