|تعداد مشاهده مقاله||24,113,149|
|تعداد دریافت فایل اصل مقاله||22,065,524|
Performance Evaluation of the Effect of Optimally Tuned IMC and PID Controllers on a Poultry Feed Dispensing System
|Journal of Advances in Computer Engineering and Technology|
|دوره 6، شماره 4 - شماره پیاپی 24، بهمن 2020، صفحه 213-226 اصل مقاله (1.01 M)|
|نوع مقاله: Original Research Paper|
|Jibril Bala 1؛ Olayemi Olaniyi 2؛ Taliha Folorunso 3؛ Tayo Arulogun 4|
|1Federal University of Technology, Minna, Nigeria|
|2Department of Computer Engineering, Federal University of Technology, Minna, Niger State, Nigeria|
|3Department of Mechatronics Engineering, School of Electrical Engineering and Technology, Federal University of Technology Minna Nigeria|
|4Ladoke Akintola University of Technology, Ogbomoso, Nigeria|
|Proportional-Integral-Derivative (PID) controllers and Internal Model Controllers (IMC) are effective tools in control analysis and design. However, parameter tuning, and inaccurate model representation often lead to unsatisfactory closed loop performance. In this study, we analyse the effect of PID controllers and IMCs tuned with Genetic Algorithm (GA) and Fuzzy Logic (FL), on a poultry feeding system. The use of GA and FL for tuning of the PID and IMC parameters was done to enhance the adaptability and optimality of the controller. A comparative analysis was made to analyse closed loop performance and ascertain the most effective controller. The results showed that the GA-PID and FL-PID gave a better performance in the aspect of rise time, settling time and Integrated Absolute Error (IAE). On the other hand, the GA-IMC and FL-IMC gave better performances in the aspect of the performance overshoot. Therefore, for processes in which a faster response and lower IAE are desired, the GA-PID and FL-PID are more effective while for processes in which the major objective is to minimise the overshoot, the GA-IMC and FL-IMC are more suitable.|
|PID Controller؛ Internal Model Controller؛ Poultry Feed؛ Fuzzy Logic؛ Genetic Algorithm|
 J. A. V. Selvi, T. K. Radhakrishnan, and S. Sundaram, “Performance assessment of PID and IMC tuning methods for a mixing process with time delay,” ISA Trans., vol. 46, no. 3, pp. 391–397, 2007.
 R. Cajo, S. Zhao, C. M. Ionescu, R. De Keyser, D. Plaza, and S. Liu, “IMC based PID Control Applied to the Benchmark PID18,” in 3rd IFAC Conference on Advances in Proportional- Integral-Derivative Control, Ghent, Belgium, May 9-11, 2018, 2018, pp. 728–732.
 P. V. Gopi Krishna Rao, M. V. Subramanyam, and K. Satyaprasad, “Design of internal model control-proportional integral derivative controller with improved filter for disturbance rejection,” Syst. Sci. Control Eng., vol. 2, no. 1, pp. 583–592, 2014.
 M. Akram Ahmad, K. Kishor, and P. Rai, “Speed control of a DC motor using Controllers,” Autom. Control Intell. Syst., vol. 2, no. 6–1, pp. 1–9, 2014.
 H. Ogawa, R. Tanaka, T. Murakami, and Y. Ishida, “Design of Internal Model Control Based on an Optimal Control for a Servo System,” J. Control Sci. Eng., vol. 2015, no. 1, pp. 1–5, 2015.
 H. Yu, H. R. Karimi, and X. Zhu, “Research of Smart Car’s Speed Control Based on the Internal Model Control,” Abstr. Appl. Anal., vol. 2014, pp. 1–5, 2014.
 Q. Zhu, L. Xiong, H. Liu, and Y. Zhu, “A New Robust Internal Model Controller and its Applications in PMSM Drive,” Intern. J. Innov. Comput. Inf. Control, vol. 12, no. 4, pp. 1257–1270, 2016.
 J. A. Bala, “Development of a Mobile Intelligent Poultry Feed Dispensing System using Particle Swarm Optimised PID Control Technique,” Federal University of Technology, Minna, Nigeria, 2015.
 B. Omosebi, “Development of a self-propelled poultry feed dispenser with Feed level detector,” Ladoke Akintola University of Technology, Nigeria, 2006.
 O. T. Arulogun, O. M. Olaniyi, A. O. Oke, and D. O. Fenwa, “Development of Mobile Intelligent Poultry Feed Dispensing System,” Medwell J. Eng. Appl. Sci., vol. 5, no. 3, pp. 229–233, 2010.
 V. I. Umogbai, “Development of a Mechanical Family Poultry Feeder,” J. Emerg. Trends Eng. Appl. Sci., vol. 4, no. 6, pp. 837–846, 2013.
 O. M. Olaniyi, O. F. Salami, O. O. Adewumi, and O. S. Ajibola, “Design of an Intelligent Poultry Feed and Water Dispensing System Using Fuzzy Logic Control Technique,” Control Theory Informatics, vol. 4, no. 9, pp. 61–72, 2014.
 A. Adejumo, “Design and Development of a Mobile Intelligent Poultry Liquid Feed Dispensing System using GA Tuned PID Control Technique,” Federal University of Technology, Minna, Nigeria, 2015.
 O. M. Olaniyi, T. A. Folorunso, J. G. Kolo, and J. A. Bala, “A Mobile Intelligent Poultry Feed Dispensing System Using Particle Swarm Optimized PID Control Technique,” in Proceedings of ISTEAMS Multidisciplinary Cross Border Conference, University of Professional Studies, Accra, Ghana, 2016, pp. 185–194.
 S. Rajvanshi and P. Juneja, “Performance Evaluation of Various Controllers Designed for an Industrial First Order plus Delay Process,” Int. J. Adv. Res. Electr. Electron. Instrum. Eng., vol. 2, no. 4, pp. 1307–1311, 2013.
 O. M. Olaniyi, T. A. Folorunso, J. G. Kolo, O. T. Arulogun, and J. A. Bala, “Performance Evaluation of Mobile Intellligent Poultry Feed Dispensing System Using Internal Model Controller and Optimally Tuned PID Controllers Performance Evaluation of Mobile Intellligent Poultry Feed Dispensing System Using Internal Model Controller a,” Adv. Multidiscip. Res. J., vol. 2, no. 2, pp. 45–58, 2016.
 N. M. Darwish, “PID controller design in the frequency domain for time-delay systems using direct method,” Trans. Inst. Meas. Control, vol. 40, no. 3, pp. 940–950, 2018.
 H. O. Bansal, R. Sharma, and P. R. Shreeraman, “PID Controller Tuning Techniques : A Review,” J. Control Eng. Technol., vol. 2, no. 4, pp. 168–176, 2012.
 A. T. Kambiz and A. Mpanda, “PID Control Theory,” 2012. [Online]. Available: http://www.intechopen.com. [Accessed: 22-Feb-2015].
 S. Saxena and Y. V. Hote, “Simple Approach to Design PID Controller via Internal Model Control,” Arab. J. Sci. Eng., vol. 41, no. 9, pp. 3473–3489, 2016.
 A. S. Omar, M. Waweru, and R. Rimiru, “Application of Fuzzy Logic in Qualitative Performance Measurement of Supply Chain Management,” Int. J. Inf. Commun. Technol. Res., vol. 5, no. 6, 2015.
 B. Singh and A. K. Mishra, “Fuzzy Logic Control System and its Applications,” Int. Res. J. Eng. Technol., vol. 2, no. 8, pp. 742–746, 2015.
 P. Singhala, D. N. Shah, and B. Patel, “Temperature Control using Fuzzy Logic,” Int. J. Instrum. Control Syst., vol. 4, no. 1, pp. 1–10, 2014.
 A. Shrestha and A. Mahmood, “Improving Genetic Algorithm with Fine-Tuned Crossover and Scaled Architecture,” J. Math., vol. 2016, pp. 1–10, 2016.
 J. Xu, L. Pei, and R. Zhu, “ScienceDirect ScienceDirect Application of a Genetic Algorithm with Random Crossover and Application of a Genetic Algorithm with Random Crossover and Dynamic Mutation on the Travelling Salesman Problem Dynamic Mutation on the Travelling Salesman Problem,” Procedia Comput. Sci., vol. 131, pp. 937–945, 2018.
 L. Haldurai, T. Madhubala, and R. Rajalakshmi, “A Study on Genetic Algorithm and its Applications,” Int. J. Comput. Sci. Eng., vol. 4, no. 10, pp. 139–143, 2016.
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