Humidity Control Scheme for Chicken Chick Banda for Improved Performance using Particle Swarm Optimization
Patrick O. M. Ogutu1, Nicholas Oyie2, Winston Ojenge3
1Mr. Patrick O.M. Ogutu, PhD, Department of Diploma in Electrical and Electronic Engineering, Mombasa Polytechnic Collage, Murang’a University, Kenya.
2Dr. Nicholas Oyie, Lecturer and Chairman, Department of Electrical and Electronics Engineering, Murang’a University of Technology, Kenya.
3Dr Winston Ochieng Ojenge, PhD, Department of Computer Science, Murang’a University of Technology, Kenya.
Manuscript received on 09 May 2022. | Revised Manuscript received on 17 May 2022. | Manuscript published on 30 June 2022. | PP: 101-104 | Volume-11 Issue-5, June 2022. | Retrieval Number: 100.1/ijeat.E35700611522 | DOI: 10.35940/ijeat.E3570.0611522
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The research is about developing of prototype Humidity control unit of a chicken chick Banda for maximum reduction in energy wastage and ensuring conducive environmental condition for bird’s growth and development using the proportional integral differential (PID) controller and the particle swarm optimization (PSO) technique for comparison purposes. The PSO stated here in is a stochastic optimization method working on the movement of swarm so as to achieve convergence. The study is achieved through designing of a prototype of the humidity environment controller to achieve two states or conditions that is for the controlled case and for the uncontrolled case. Environmental humidity control is achieved using a programmed Arduino and the DC FAN. The process is then designed using the MATLAB simulation software operating at the Simulink model designing platform. The same design is connected to the PID controller and then also tuned using the PID tuning platform on the Matlab. The same design is implemented on the workspace using particle swarm optimization method and it is then run to see the system behavior in terms of settling time, rising time and peak overshoot. The major reason of the study is to demystify the myth that one can only use conventional PID controller techniques in performance improvement and that there is a better method which can similarly be used with better results and cheaper. Most poultry farmers are stack with their old ways of achieving good performance therefore the results of this work will be an eye opener for them to embrace new techniques in the market The presented particle swarm optimization techniques shows impressive performance in terms of the settling time, rise time and over shoot.
Keywords: MATLAB Simulink, PID controllers, Overshoot controller, stochastic, Particle swarm optimization
Scope of the Article: Swarm Intelligence