Optimum PID Controller with Fuzzy Self-Tuning for DC Servo Motor

M. A. Abdelghany, Abdelrady Okasha Elnady, Shorouk Ossama Ibrahim

Abstract


DC motors are simple and controllable, making them a popular choice for various applications. However, the speed and load characteristics of DC motors can change, making it difficult to control them effectively. This paper proposes an optimum PID controller with fuzzy self-tuning for DC servo motors. The controller uses two steps to adjust the PID gains: The ACS algorithm is employed to identify the optimal PID gains in the first step. A fuzzy logic (FLC) controller is employed in the second stage to further fine-tune the gains. The FLC considers two cost functions: the first function is the sum of the squares of the error between the controlled output and reference input. The second function is a mathematical expression that specifies the required characteristics of the system response. The fuzzy self-tune then uses a set of rules to adjust the PID gains in response to changes in the system. The rules are based on the two cost functions designed to maintain the optimum PID gains for various operating settings. The outcomes of the two functions are: Kp = 5.2381, Ki = 7.0427, and Kd = 0.49468, with rising time = 0.2503, overshoot = 2.5079, and settling time = 10.4824 in the first cost function. The second cost function outcomes are Kp = 8.1381; Ki = 8.6427; and Kd = 0.49468. The FST-PID controller's performance is evaluated using Matlab-Simulink. The proposed controller was tested on a DC servo motor, and the results showed good performance in both steady-state and transient responses. The controller also maintained the optimum PID gains in the event of changes or disturbances. So, the motor's speed can effectively control under a variety of conditions.

Keywords


DC Servo Motor; PID Controller; Ant ColonySystem; Fuzzy Self Tuning.

Full Text:

PDF

References


A. K. Mishra, V. K. Tiwari, R. Kumar, and T. Verma, "Speed control of dc motor using artificial bee colony optimization technique," 2013 International Conference on Control, Automation, Robotics and Embedded Systems (CARE), pp. 1-6, 2013, doi: 10.1109/CARE.2013.6733772.

A. Rodríguez-Molina, M. G. Villarreal-Cervantes, and M. Aldape-Pérez, “An adaptive control study for a DC motor using metaheuristic algorithms,” IFAC-PapersOnLine, vol. 50, no. 1, pp. 13114–13120, 2017.

A. Rodríguez-Molina, M. G. Villarreal-Cervantes, J. Álvarez-Gallegos, and M. Aldape-Pérez, “Bio-inspired adaptive control strategy for the highly efficient speed regulation of the DC motor under parametric uncertainty,” Appl. Soft Comput. J., vol. 75, pp. 29–45, 2019.

D. Potnuru, K. Alice Mary, and C. Sai Babu, “Experimental implementation of flower pollination algorithm for speed controller of a BLDC motor,” Ain Shams Eng. J., vol. 10, no. 2, pp. 287–295, 2019.

A. T. El-Deen, A. A. H. Mahmoud, and A. R. El-Sawi, “Optimal PID tuning for DC motor speed controller based on genetic algorithm,” Int. Rev. Autom. Control, vol. 8, no. 1, pp. 80–85, 2015.

Z. -L. Gaing, "A particle swarm optimization approach for optimum design of PID controller in AVR system," in IEEE Transactions on Energy Conversion, vol. 19, no. 2, pp. 384-391, 2004, doi: 10.1109/TEC.2003.821821.

L. Syafaah, Widianto, I. Pakaya, D. Suhardi, and M. Irfan, "PID designs using DE and PSO algorithms for damping oscillations in a DC motor speed," 2017 4th International Conference on Electrical Engineering, Computer Science and Informatics (EECSI), pp. 1-5, 2017, doi: 10.1109/EECSI.2017.8239138.

B. Hekimoğlu, “Optimal tuning of fractional order PID controller for DC motor speed control via chaotic atom search optimization algorithm,” IEEE Access, vol. 7, pp. 38100–38114, 2019.

X. Lin, Y. Liu, and Y. Wang, "Design and Research of DC Motor Speed Control System Based on Improved BAS," 2018 Chinese Automation Congress (CAC), pp. 3701-3705, 2018, doi: 10.1109/CAC.2018.8623171.

S. Duman, D. Maden, and U. Güvenç, "Determination of the PID controller parameters for speed and position control of DC motor using Gravitational Search Algorithm," 2011 7th International Conference on Electrical and Electronics Engineering (ELECO), pp. I-225-I-229, 2011.

J. Agarwal, G. Parmar, R. Gupta, and A. Sikander, “Analysis of grey wolf optimizer based fractional order PID controller in speed control of DC motor,” Microsyst. Technol., vol. 24, no. 12, pp. 4997–5006, 2018.

U. Bhatnagar and A. Gupta, “Application of grey wolf optimization in optimal control of DC motor and robustness analysis,” SKIT Research Journal, vol. 8, no. 1, pp. 19–25, 2018.

M. H. Jasim, “Tuning of a PID controller by bacterial foraging algorithm for position control of DC servo motor,” Engineering and Technology Journal, vol. 36, no. 3A, pp. 287-294, 2018.‏

L. J. Qiu, M. F. Qu, and X. Y. Liu, “Position Sensorless Control of Brushless DC Motor Based on Sliding Mode Observer,” In International Conference on Advanced Hybrid Information Processing, pp. 342-355, 2021.

S. A. Fayad, M. Shaban, M. Attia, and S. A. M. Abdelwahab, “Performance Enhancement of Speed and Position Control for DC Servo Motor Using Artificial Intelligence Technique,” International Journal on Electrical Engineering and Informatics, vol. 14, no. 3, pp. 552-566, 2022.

A. A. Emhemed and R. B. Mamat, “Modelling and simulation for industrial DC motor using intelligent control,” Procedia Engineering, vol. 41, pp. 420-425, 2012.‏

S. Simon and P. Rajalakshmy, “Speed Control of DC Motor using PSO Based Fuzzy Logic Controller,” International Journal of Research & Technology (IJERT), vol. 3, no. 2, pp. 877-880, 2014.

I. Petrás, “Fractional-order feedback control of DC motor,” Journal of Electrical Engineering, vol. 60, no. 3, pp. 117–128, 2009.

R. Morales, J. A. Somolinos, and H. S. Ramírez, “Control of a DC motor using algebraic derivative estimation with real time experiments,” Measurement, Vol. 47, pp. 401–17, 2014.

R. Bai, “Neural network control-based adaptive design for a class of DC motor systems with the full state constraints,” Neurocomputing, vol. 168, pp. 65–9, 2015.

S. Saxena and Y. V. Hote, “Design and validation of fractional-order control scheme for DC servomotor via internal model control approach,” IETE Technical Review, vol. 36, no. 1, pp. 49-60, 2019.

H. Yang, D. Dong, Y. Ren, J. Xu, and S. Yang, "Study on Fuzzy PID Control in Double Closed-Loop DC Speed Regulation System," 2011 Third International Conference on Measuring Technology and Mechatronics Automation, pp. 465-469, 2011, doi: 10.1109/ICMTMA.2011.687.

T. Ravichandran and F. Karray, "Knowledge based approach for online self-tuning of PID-control," Proceedings of the 2001 American Control Conference, vol. 4, pp. 2846-2851, 2001, doi: 10.1109/ACC.2001.946328.

G. Y. Long, L. H. Long, and F. J. Bo, "Design and Simulation of Cascade Fuzzy Self - Adaptive PID Speed Control of Thyristor-Driven DC Motor", International Conference on Machine Learning and Cybernetics, pp. 655-660, 2006.

P. Thepsatorn, A. Numsomran, V. Tipsuwanporn, and T. Teanthong, "DC Motor Speed Control using Fuzzy Logic based on LabVIEW," 2006 SICE-ICASE International Joint Conference, pp. 3617-3620, 2006, doi: 10.1109/SICE.2006.314890.

B. B. Alagoz, A. Ates, and C. Yeroglu, “Auto-tuning of PID controller according to fractional-order reference model approximation for DC rotor control,” Mechatronics, vol. 23, pp. 789–97, 2013.

K. -Y. Cheng and Y. -Y. Tzou, "Fuzzy optimization techniques applied to the design of a digital PMSM servo drive," in IEEE Transactions on Power Electronics, vol. 19, no. 4, pp. 1085-1099, July 2004, doi: 10.1109/TPEL.2004.830036.

C. Xia, P. Guo, T. Shi, and M. Wang, “Speed control of brushless DC motor using genetic algorithm based fuzzy controller,” In Proceeding of the 2004 International Conference on Intelligent Mechatronics and Automation, Chengdu, China, 3rd edn. A Treatise on Electricity and Magnetism, vol. 2, pp. 68-73, 2004.

L. Wang, H. Li, and Y. Sun, "Fuzzy Control Based on Self-adjusted Parameter for Brushless DC Motor," 2007 International Conference on Mechatronics and Automation, pp. 2352-2356, 2007, doi: 10.1109/ICMA.2007.4303921.

S. Wang, S. Yu, and Z. Feng, " A method for controlling a loading system based on a fuzzy PID controller," Mechanical Science and Technology for Aerospace Engineering, vol. 30, no. 1, pp. 166-172, 2011.

Y. Lv, H. Luo, and Y. Cai, "Research on tuning method for fuzzy PID," The Fourth International Workshop on Advanced Computational Intelligence, pp. 334-337, 2011, doi: 10.1109/IWACI.2011.6160027.

I. H. Altas and A. M. Sharaf, “A generalized direct approach for designing fuzzy logic controllers in Matlab/Simulink GUI environment,” International journal of information technology and intelligent computing, vol. 1, no. 4, pp. 1-27, 2007.

A. Z. Alassar, I. M. Abuhadrous, and H. A. Elaydi, "Modeling and control of 5 DOF robot arm using supervisory control," 2010 The 2nd International Conference on Computer and Automation Engineering (ICCAE), pp. 351-355, 2010, doi: 10.1109/ICCAE.2010.5451398.

M. S. A. Omar, T. Y. Khedr, and B. A. A. Zalam, "Particle swarm optimization of fuzzy supervisory controller for nonlinear position control system," 2013 8th International Conference on Computer Engineering & Systems (ICCES), pp. 138-145, 2013, doi: 10.1109/ICCES.2013.6707189.

Z. Bingül and O. Karahan, “A Fuzzy Logic Controller tuned with PSO for 2 DOF robot trajectory control,” Expert Systems with Applications, vol. 38, no. 1, pp. 1017-1031, 2011.

S. Tiwari, A. Bhatt, A. C. Unni, J. G. Singh, and W. Ongsakul, "Control of DC Motor Using Genetic Algorithm Based PID Controller," 2018 International Conference and Utility Exhibition on Green Energy for Sustainable Development (ICUE), pp. 1-6, 2018, doi: 10.23919/ICUE-GESD.2018.8635662.

J. Agarwal, G. Parmar, R. Gupta, and A. Sikander, “Analysis of grey wolf optimizer based fractional order PID controller in speed control of DC motor,” Microsystem Technologies, vol. 24, pp. 4997-5006, 2018.

V. Yadav and V. K. Tayal, "Optimal Controller Design for a DC Motor using PID Tuner," 2018 International Conference on Power Energy, Environment and Intelligent Control (PEEIC), pp. 442-445, 2018, doi: 10.1109/PEEIC.2018.8665658.

N. Thomas and D. P. Poongodi, “Position control of DC motor using genetic algorithm based PID controller,” In Proceedings of the world congress on engineering, vol. 2, pp. 1-3, 2009.

L. S. Mezher, “Characteristics of servo DC motor with PID controller,” Journal of Mechanical Engineering Research and Developments, vol. 44, no. 2, pp. 392-400, 2021.

P. K. Meena and B. Bhushan, “Simulation for Position Control of DC Motor using Fuzzy Logic,” International Journal of Electronics, Electrical and Computation System (IJEECS), vol. 6, no. 6, 2017.

B. Li, X. Wang, L. Wang, W. Yang, and J. Xia, "Adaptive Event-triggered Fuzzy Control for DC Motor Servo Systems," 2021 IEEE 10th Data Driven Control and Learning Systems Conference (DDCLS), pp. 1101-1105, 2021, doi: 10.1109/DDCLS52934.2021.9455634.

H. Wang, P. X. Liu, and B. Niu, "Robust fuzzy adaptive tracking control for nonaffine stochastic nonlinear switching systems", IEEE Transactions on Cybernetics, vol. 48, no. 8, pp. 2462-2471, 2018.

J. W. Xia, J. Zhang, J. E. Feng, Z. Wang, and G. M. Zhuang, "Command filter-based adaptive fuzzy control for nonlinear systems with unknown control directions", IEEE Transactions on Systems Man and Cybernetics: Systems, vol. 51, no. 3, pp. 1945-1953, 2021.

M. M. Algreer and Y. R. Kuraz, “Design fuzzy self tuning of PID controller for chopper-fed DC motor drive,” Al-Rafidain Engineering, vol. 16, no. 2, pp. 54-66, 2008.‏

H. X. Li and S. K. Tso, “Quantitative design and analysis of fuzzy proportional-integralderivative control a step towards autotuning,” International Journal of Systems Science, vol. 31, no. 5, pp. 545-553, 2000.

L. Reznik, O. Ghanayem, and A. Bourmistrov, “PID plus fuzzy controller structures as a design base for industrial applications,” Engineering applications of artificial intelligence, vol. 13, no. 4, pp. 419-430, 2000.

H. Alzarok, "Towards achieving an optimum speed performance for DC servo motors via Fuzzy logic controllers," 2022 IEEE 2nd International Maghreb Meeting of the Conference on Sciences and Techniques of Automatic Control and Computer Engineering (MI-STA), pp. 1-8, 2022, doi: 10.1109/MI-STA54861.2022.9837780.

N. L. Ismail, K. A. Zakaria, N. S. Nazar, M. Syaripuddin, A. S. N. Mokhtar, and S. Thanakodi, “DC motor speed control using fuzzy logic controller,” In AIP conference proceedings, vol. 1930, no. 1, 2018.

Y. A. Almatheel and A. Abdelrahman, "Speed control of DC motor using Fuzzy Logic Controller," 2017 International Conference on Communication, Control, Computing and Electronics Engineering (ICCCCEE), pp. 1-8, 2017, doi: 10.1109/ICCCCEE.2017.7867673.

Q. Zeng and G. Tan, "Optimal Design of PID Controller Using Modified Ant Colony System Algorithm," Third International Conference on Natural Computation (ICNC 2007), pp. 436-440, 2007, doi: 10.1109/ICNC.2007.518.

W. Zhang, Y. Fang, R. Ye, and Z. Wang, “Analysis and design of a double fuzzy PI controller of a voltage outer loop in a reversible three-phase PWM converter,” Energies, vol. 13, no. 15, p. 3778, 2020‏.

E. W. Suseno and A. Ma’arif, “Tuning of PID controller parameters with genetic algorithm method on DC motor,” International Journal of Robotics and Control Systems, vol. 1, no. 1, pp. 41-53, 2021.

D. Somwanshi, M. Bundele, G. Kumar, and G. Parashar, “Comparison of fuzzy-PID and PID controller for speed control of DC motor using LabVIEW,” Procedia Computer Science, vol. 152, pp. 252-260, 2019.

M. Omar, M. Soliman, A. A. Ghany, F. Bendary, “Optimal tuning of PID controllers for hydrothermal load frequency control using ant colony optimization,” International journal on electrical engineering and informatics, vol. 5, no. 3, p. 348, 2013.‏

M. G. Abdolrasol, “Artificial neural networks based optimization techniques: A review,” Electronics, vol. 10, no. 21, p. 2689, 2021.

H. Albalawi, S. A. Zaid, M. E. El-Shimy, and A. M. Kassem, “Ant Colony Optimized Controller for Fast Direct Torque Control of Induction Motor,” Sustainability, vol. 15, no. 4, p. 3740, 2023.

M. A. George, D. V. Kamat, and C. P. Kurian, "Electronically Tunable ACO Based Fuzzy FOPID Controller for Effective Speed Control of Electric Vehicle," in IEEE Access, vol. 9, pp. 73392-73412, 2021, doi: 10.1109/ACCESS.2021.3080086.

M. Omar, M. Soliman, A. M. A. Ghany, and F. Bendary, "Ant Colony Optimization based PID for single area load frequency control," 2013 5th International Conference on Modelling, Identification and Control (ICMIC), pp. 119-123, 2013.

S. Prainetr, T. Phurahong, K. Janprom, and N. Prainetr, "Design Tuning PID Controller for Temperature Control Using Ant Colony Optimization," 2019 IEEE 2nd International Conference on Power and Energy Applications (ICPEA), pp. 124-127, 2019, doi: 10.1109/ICPEA.2019.8818517.

M. Akar and I. Temiz, “Motion controller design for the speed control of dc servo motor,” International Journal of Applied Mathematics and Informatics, vol. 1, no. 4, pp. 131-137, 2007.‏




DOI: https://doi.org/10.18196/jrc.v4i4.18676

Refbacks

  • There are currently no refbacks.


Copyright (c) 2023 M. A. Abdelghany, Abdelrady Okasha Elnady, Shorouk Ossama Ibrahim

Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

 

Journal of Robotics and Control (JRC)

P-ISSN: 2715-5056 || E-ISSN: 2715-5072
Organized by Peneliti Teknologi Teknik Indonesia
Published by Universitas Muhammadiyah Yogyakarta in collaboration with Peneliti Teknologi Teknik Indonesia, Indonesia and the Department of Electrical Engineering
Website: http://journal.umy.ac.id/index.php/jrc
Email: jrcofumy@gmail.com

Kuliah Teknik Elektro Terbaik