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Performance Improvement of a Chicken Chicks’ Banda Using Neuro-Fuzzy Logic Controller

2021; Volume: 11; Issue: 1 Linguagem: Inglês

2162-9455

Patrick O. M. Ogutu, Nicholas O. Oyie, Winston Ojenge,

Fuzzy Logic and Control Systems

This paper is about performance improved chicken chicks’ Banda, which uses the environmental conditions to measure and control the cage humidity and temperature. The change in environmental condition is used to turn on the heater and the fan so as to achieve the expected temperature and humidity. The research l developed the system mathematical model depicting the chicken chicks’ Banda, designed a prototype humidity and temperature controller and use the learned behavior to implement a simulation of two systems that is the fuzzy logic and neuro fuzzy logic to analyze the behavior by using the Matlab tool box. Neural fuzzy logic is used to monitor and control the chicken chicks’ cage desired temperature and humidity which is of set target of 27°C and 60% respectively. The result should show that the process controller is able to keep track on the reference input and the resultant response of neural fuzzy control so as to better track and optimize performance in comparison with fuzzy only controllers. The hybrid optimization method which consist of least square estimator and Back propagation should be used in the process and the training done using gradient descent method. The result show that there is improved performance as depicted by a settling time of 0.8 seconds to 0.5 seconds and overshoot improvement from 30% to 0.935% as a result of neuro- fuzzy technique.