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Design of a Taguchi-GRA optimized PID and adaptive PID controllers for speed control of DC motor

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Języki publikacji
EN
Abstrakty
EN
DC motors have wide acceptance in industries due to their high efficiency, low costs, and flexibility. The paper presents the unique design concept of a multi-objective optimized proportional-integral-derivative (PID) controller and Model Reference Adaptive Control (MRAC) based controllers for effective speed control of the DC motor system. The study aims to optimize PID parameters for speed control of a DC motor, emphasizing minimizing both settling time (Ts )and % overshoot (% OS) of the closed-loop response. The PID controller is designed using the Ziegler Nichols (ZN) method primarily subjected to Taguchi-grey relational analysis to handle multiple quality characteristics. Here, the Taguchi L9 orthogonal array is defined to find the process parameters that affect Ts and % OS. The analysis of variance shows that the most significant factor affecting Ts and % OS is the derivative gain term. The result also demonstrates that the proposed Taguchi- GRA optimized controller reduces Ts and % OS drastically compared to the ZN-tuned PID controller. This study also uses MRAC schemes using the MIT rule, Lyapunov rule, and a modified MIT rule. The DC motor speed tracking performance is analyzed by varying the adaptation gain and reference signal amplitude. The results also revealed that the proposed MRAC schemes provide desired closed-loop performance in real-time in the presence of disturbance and varying plant parameters. The study provides additional insights into using a modified MIT rule and the Lyapunov rule in protecting the response from signal amplitude dependence and the assurance of a stable adaptive controller, respectively.
Rocznik
Strony
759--775
Opis fizyczny
Bibliogr. 26 poz., rys., tab., wz.
Twórcy
  • Department of Electronics and Communication Engineering Manipal Institute of Technology, Manipal Academy of Higher Education (MAHE) Manipal – 576104, Udupi District, Karnataka State, India
  • Department of Electronics and Communication Engineering Manipal Institute of Technology, Manipal Academy of Higher Education (MAHE) Manipal – 576104, Udupi District, Karnataka State, India
Bibliografia
  • [1] Trong T. N., The control structure for DC motor based on the flatness control, International Journal of Power Electronics and Drive Systems, vol. 8, no. 4, pp. 1814–1821 (2017), DOI: 10.11591/ijpeds.v8.i4.pp1814–1821.
  • [2] Li Z., Xia C., Speed control of brushless DC motor based on CMAC and PID controller, Proceedings of the 6th IEEE World Congress on Intelligent Control and Automation, Dalian, China, pp. 6318–6322 (2016).
  • 3] Wang M. S., Chen S. C., Shih C. H., Speed control of brushless DC motor by adaptive network-based fuzzy inference, Microsystem Technologies, vol. 24, no. 1, pp. 33–39 (2018), DOI: 10.1007/s00542-016-3148-0.
  • [4] Templos-Santos J. L., Aguilar-Mejia O., Peralta-Sanchez E., Sosa-Cortez R., Parameter tuning of PI control for speed regulation of a PMSM using bio-inspired algorithms, Algorithms, vol. 12, no. 3, pp. 54–75 (2019), DOI: 10.3390/a12030054.
  • [5] John D. A., Sehgal S., Biswas K., Hardware Implementation and Performance Study of Analog PIλDμ Controllers on DC Motor, Fractal and Fractional, vol. 4, no. 3, pp. 34–45 (2020), DOI: 10.3390/fractalfract4030034.
  • [6] Serradilla F., Cañas N., Naranjo J.E., Optimization of the Energy Consumption of Electric Motors through Metaheuristics and PID Controllers, Electronics, vol. 9, no. 11, pp. 1842–1858 (2020), DOI: 10.3390/electronics9111842.
  • [7] Hammoodi S.J., Flayyih K.S., Hamad A.R., Design and implementation speed control system of DC motor based on PID control and matlab Simulink, International Journal of Power Electronics and Drive Systems, vol. 11, no. 1, pp. 127–134 (2020), DOI: 10.11591/ijpeds.v11.i1.pp127-134.
  • [8] Zhang Y., An Y., Wang G., Kong X., Multi motor neural PID relative coupling speed synchronous control, Archives of Electrical Engineering, vol. 69, no. 1, pp. 69–88 (2020), DOI: 10.24425/aee.2020. 131759.
  • [9] Wu H., Su W., Liu Z., PID controllers: Design and tuning methods, Proceedings of the 9th IEEE Conference on Industrial Electronics and Applications, Hangzhou, China, pp. 808–813 (2014).
  • [10] Sheel S., Gupta O., New techniques of PID controller tuning of a DC motor-development of a toolbox, MIT International Journal of Electrical and Instrumentation Engineering, vol. 2, no. 2, pp. 65–69 (2012).
  • [11] Kumar P., Raheja J., Narayan S., Design of PID Controllers Using Multiobjective Optimization with GA and Weighted Sum Objective Function Method, International Journal of Technical Research, vol. 2, no. 2, pp. 52–56 (2013).
  • [12] Chiha I., Liouane N., Borne P., Tuning PID Controller using Multi-objective Ant Colony Optimization, Applied Computational Intelligence and Soft Computing, Article ID 536326, 7 pages (2012), DOI: 10.1155/2012/536326.
  • [13] de Moura Oliveira P.B., Hedengren J.D., Pires E.J., Swarm-Based Design of Proportional Integral and Derivative Controllers Using a Compromise Cost Function: An Arduino Temperature Laboratory Case Study, Algorithms, vol. 13, no. 12, pp. 315–332 (2020), DOI: 10.3390/a13120315.
  • [14] Dewantoro G., Multi-objective optimization scheme for PID-controlled DC motor, International Journal of Power Electronics and Drive Systems, vol. 7, no. 3, pp. 31–38 (2016), DOI: 10.11591/ijpeds.v7.i3.pp734-742.
  • [15] Achuthamenon Sylajakumari P., Ramakrishnasamy R., Palaniappan G., Taguchi Grey Relational Analysis for Multi-Response Optimization of Wear in Co-Continuous Composite, Materials, vol. 11, no. 9, pp. 3–17 (2018), DOI: 10.3390/ma11091743.
  • [16] El-Samahy A. A., Shamseldin M. A., Brushless DC motor tracking control using self-tuning fuzzy PID control and model reference adaptive control, Ain Shams Engineering Journal, vol. 9, no. 3, pp. 341–352 (2018), DOI: 10.1016/j.asej.2016.02.004.
  • [17] Neogi B., Islam S. S., Chakraborty P., Barui S., Das A., Introducing MIT rule toward the improvement of adaptive mechanical prosthetic arm control model, In Progress in Intelligent Computing Techniques: Theory, Practice, and Applications, Springer, Singapore, pp. 379–388 (2018).
  • [18] Akbar M. A., Naniwa T., Taniai Y., Model reference adaptive control for DC motor based on Simulink, Proceeding of the 6th IEEE International Annual Engineering Seminar (InAES), Yogyakarta, Indonesia pp. 101–106 (2016).
  • [19] Sethi D., Kumar J., Khanna R., Design of fractional order MRAPIDC for inverted pendulum system, Indian Journal of Science and Technology, vol. 10, no. 31, pp. 1–5 (2017), DOI: 10.17485/ijst/2017/v10i31/113893.
  • [20] Jain P., Nigam M. J., Design of a model reference adaptive controller using modified MIT rule for a second-order system, Advances in Electronic and Electric Engineering, vol. 3, no. 4, pp. 477–484, (2013).
  • [21] Dimeas I., Petras I., Psychalinos C., New analog implementation technique for fractional-order controller: a DC motor control, AEU-International Journal of Electronics and Communications, vol. 78, pp. 192–200 (2017), DOI: 10.1016/j.aeue.2017.03.010.
  • [22] Qader M. R., Identifying the optimal controller strategy for DC motors, Archives of Electrical Engineering, vol. 68, no. 1, pp. 101–114 (2019), DOI: 10.11591/ijra.v6i4.pp252-268.
  • [23] George M.A., Kamath D.V., OTA-C voltage-mode proportional- integral- derivative (PID) controller for DC motor speed control, Proceedings of the Academicsera 461st International Conference on Science, Technology, Engineering and Management (ICSTEM), Paris, France, pp. 21–26 (2019).
  • [24] Swarnkar P., Jain S. K., Nema R. K., Adaptive control schemes for improving the control system dynamics: a review, IETE Technical Review, vol. 31, no. 1, pp. 17–33 (2014), DOI: 10.1080/02564602.2014.890838.
  • [25] Hägglund T., The one-third rule for PI controller tuning, Computers & Chemical Engineering, vol. 127, pp. 25–30 (2019), DOI: 10.1016/j.compchemeng.2019.03.027.
  • [26] George M. A., Kamath D. V., Thirunavukkarasu I., An Optimized Fractional-Order PID (FOPID) Controller for a Non-Linear Conical Tank Level Process, Proceedings of IEEE Applied Signal Processing Conference (ASPCON), Kolkata, India, pp. 134–138 (2020).
Uwagi
Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2021).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-afdd17ba-ded6-4be2-bb61-e0777fde98ce
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