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http://ir.futminna.edu.ng:8080/jspui/handle/123456789/18785
Title: | Performance Evaluation of Mobile Intelligent Poultry Feed Dispensing System Using Internal Model Controller and Optimally Tuned PID Controllers |
Authors: | Olaniyi, Olayemi Mikail Folorunso, Taliha Abiodun Kolo, Jonathan Gana Arulogun, Oladiran Tayo Bala, Jibril Abdullahi |
Keywords: | PID Controller Particle Swarm Optimization Genetic Algorithm Feed Dispensing Internal Model Controller |
Issue Date: | 2016 |
Publisher: | Advances in Multidisciplinary Research Journal |
Citation: | O. M. Olaniyi, T. A. Folorunso, J. G. Kolo, O. T. Arulogun, and J. A. Bala,(2016) "Performance Evaluation of Mobile Intelligent Poultry Feed Dispensing System Using Internal Model Controller and Optimally Tuned PID Controllers", Advances in Multidisciplinary Research Journal, Vol 2, No.2, 2016, Pp 45- 58 |
Abstract: | This paper presents the performance evaluation of a mobile intelligent poultry liquid feed dispensing system by using a Genetic Algorithm (GA) tuned Proportional Integral Derivative (PID) controller, a Particle Swarm Optimization (PSO) tuned PID controller and an Internal Model Controller (IMC). The performances of the various controllers were evaluated using system responses in terms of the transient response as well as the Integral Absolute error. The obtained results showed that the IMC has the least performance as compared to the optimally tuned PID controllers with respect to the rise time, settling time and internal of the Absolute error. However, the IMC proffers a better solution with respect to the zero overshoot. On the overall the PSO Tuned PID controller offers significant performance enhancement to the system, thus ensuring a better and improve return on investment, reduced human involvement as well as improved productivity on the use of the system. |
URI: | http://repository.futminna.edu.ng:8080/jspui/handle/123456789/18785 |
Appears in Collections: | Mechatronics Engineering |
Files in This Item:
File | Description | Size | Format | |
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AIMS 2016.pdf | 543.11 kB | Adobe PDF | View/Open |
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