Speed Control of Induction Motor using LQG
DOI:
https://doi.org/10.18196/jrc.26138Keywords:
induction motor, speed, IFOC, LQGAbstract
The electric motor is one of the technological developments which can support the production process. Not only in the manufacturing, but also in the transportation sector. The AC motor is divided into the synchronous and asynchronous motor. One type of asynchronous motor which widely used is the induction motor. In this study, the application of the IFOC control method and the LQG speed control method will be used to control the speed of an induction motor. The PID algorithm is also used as a comparison. Tests were carried out using MATLAB software. The speed variation and load variation are tested to validate the controller performance. PID is superior in terms of settling time and IAE. On the other hand, LQG is better in energy consumption. In terms of IAE, LQG has a higher value compared to PID by up to 56.67%. On the other hand, LQG is superior in terms of energy, which is 8.38% more efficient.
References
H. Maghfiroh, C. Hermanu, M. H. Ibrahim, M. Anwar, and A. Ramelan, “Hybrid fuzzy-PID like optimal control to reduce energy consumption,” TELKOMNIKA, vol. 18, no. 4, pp. 2053–2061, 2020.
M. Swargiary, J. Dey, and T. K. Saha, “Optimal Speed Control of Induction Motor Based on Linear Quadratic Regulator Theory,” in 2015 Annual IEEE India Conference (INDICON), 2015.
O. S. Ebrahim and P. K. Jain, “LQR-based stator field oriented control for the induction motor drives,” Conf. Proc. - IEEE Appl. Power Electron. Conf. Expo. - APEC, no. 5, pp. 1126–1131, 2008.
M. Magzoub, N. Saad, R. Ibrahim and M. Irfan, An experimental demonstration of hybrid fuzzy-fuzzyspace- vector control on AC variable speed drives, Neural Computing & Applications, pp. 1-16, 2017.
Suetake M, da Silva IN, Goedtel A. Embedded DSP-based compact fuzzy system and its application for induction-motor speed control. IEEE Transactions on Industrial Electronics, vol. 58, pp. 750–60, 2011.
CMFS Reza, Islam MD, Mekhilef S. A review of reliable and energy efficient direct torque-controlled induction motor drives. Renewable Sustainable Energy Review, vol. 37, pp. 919–32, 2014.
Dos Santos TH, Goedtel A, da Silva SAO, Suetake M. Scalar control of an induction motor using a neural sensorless technique. Electrical Power Systm Research, vol. 108, pp. 322–30, 2014.
Allirani S, Jagannathan V. Direct torque control technique in induction motor drives – a review. Journal of Theory & Applications of Information Technology, vol. 60, 2014.
Sarhan H. Efficiency optimization of vector-controlled induction motor drive. International Journal of Advance Engineering Technology, vol. 7, 2014.
Demirtas M. DSP-based sliding mode speed control of induction motor using neuro-genetic structure. Expert System Applications, vol. 36, pp. 33–40, 2009.
Rong-Jong W, Jeng-Dao L, Kuo-Min L. Robust decoupled control of direct fieldoriented induction motor drive. 5th Asian Control Conference, pp. 1346–1353, 2004.
Hedjar R, Boucher P, Dumur D. Robust nonlinear receding-horizon control of induction motors. International Journal of Electrical Power Energy System, vol. 46, pp. 353–65, 2013.
Sutikno T, Idris NRN, Jidin A. A review of direct torque control of induction motors for sustainable reliability and energy efficient drives. Renewable Sustainable Energy Review, vol. 32, pp. 548–58, 2014
I. K. Bousserhanel, A. Hazzabl, M. Rahlw, M. Kamli, and B. Mazari, “Adaptive PI Controller using Fuzzy System Optimized by Genetic Algorithm for Induction Motor Control,” in IEEE International Power Electronics Congress, 2006.
A. Hazzab, I. K. Bousserhane, and M. Kamli, “Design of a Fuzzy Sliding Mode Controller by Genetic Algorithms for Induction Machine Speed Control,” Int. J. Emerg. Electr. Power Syst., vol. 1, no. 2, 2004.
A. Alwadie, “A Concise Review of Control Techniques for Reliable and Efficient Control of Induction Motor,” Int J. Power Electron. Drive Syst., vol. 9, no. 3, pp. 1124–1139, 2018.
M.A. Hannan, Jamal A. Ali, Azah Mohamed, Aini Hussain, Optimization techniques to enhance the performance of induction motor drives: a review, Renewable and Sustainable Energy Reviews, 2017.
A. J. Fattah and I. A. Qader, “Performance and Comparison Analysis of Speed Control of Induction Motors using Improved Hybrid PID-Fuzzy Controller,” in 2015 IEEE Int. Conference on Electro/Information Technology (EIT), 2015, pp. 575–580.
B. Umesh and S. Sanjay, “Speed Control of Three Phase Induction Motor Using Fuzzy-PID Controller,” Int. J. Eng. Res. Technol., vol. 2, no. 11, pp. 3794–3799, 2013.
Lin FJ, Huang PK, Chou WD. A genetic algorithm based recurrent fuzzy neural network for linear induction motor servo drive. J Chin Inst Eng 2007; 30:801–17.
Lin C-K. Radial basis function neural network-based adaptive critic control of induction motors. Appl Softw Comput 2011; 11:3066–74.
Bousserhane IK, Hazzab A, Rahli M, Kamli M, Mazari B. Adaptive PI Controller using Fuzzy System Optimized by Genetic Algorithm for Induction Motor Control. 10th IEEE International Power Electronics Congress, pp. 1-8, 2006.
Ali JA, Hannan M, Mohamed A. Improved indirect field-oriented control of induction motor drive based PSO algorithm. Jurnal Teknologi, vol. 78, 2016.
Ali JA, Hannan M, Mohamed A. Gravitational search algorithm-based tuning of a PI speed controller for an induction motor drive. IOP Conference Series: Earth and Environmental Science: IOP Publishing. pp. 12001- 12004, 2016.
W. M. W. Syahidah, O. Rosli, M. A. Joraimee, and A. Norhidayah, “Linear Quadratic Gaussian ( LQG ) Controller Design for Servo Motor,” AENSI J., vol. 8, no. 4, pp. 700–713, 2014.
N. K. Roy, H. R. Pota, M. A. Mahmud, and M. J. Hossain, “Voltage control of emerging distribution systems with induction motor loads using robust LQG approach,” Int Trans. Electr. Energy Syst., no. April 2013, pp. 927–943, 2014.
N. H. M. Nasir, K. K. Ib, and M. K. I. Ahmad, “Comparative Study on Mathematical and Black Box Modelling Approaches of Musculoskeletal System,” in International Seminar on the Application of Science & Mathematics, 2011, pp. 1–8.
Ilham, “KENDALI KECEPATAN MOTOR INDUKSI 3 PHASA MENGGUNAKAN LQR ( LINEAR QUADRATIC REGULATOR ),” Inspir. J. Teknol. Inf. dan Komun., vol. 3, no. 1, pp. 61–68, 2013.
O. S. Ebrahim, M. F. Salem, P. K. Jain, and M. A. Badr, “Application of linear quadratic regulator theory to the stator field-oriented control of induction motors,” IET Electr. Power Appl., vol. 4, no. 8, p. 637, 2010.
T. Abut, “Modeling and Optimal Control of a DC Motor,” Int. J. od Eng. Trends Technol., vol. 32, no. 3, pp. 146–150, 2016.
A. Ramelan, J. S. Saputro, C. Hermanu, M. H. Ibrahim, and S. Pramono, “Desain and Simulation Linear Quadratic Gaussian (LQG) for Pan-Tilt Face Tracking Camera Servos,” in AIP Conference Proceedings, 2020.
I. Ajiprasetyo and D. Wibawa, “Design and Implementation Control LQG for DC Motor Velocity,” e-Proceeding Eng., vol. 2, no. 2, 2015.

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