Climate control system of a poultry house using sliding mode control

This work focuses on the application of Sliding Mode Controller with uncertainty learning and control gain estimation techniques to provide the desired climatic conditions in the poultry house. The nonlinear dynamics mathematical model was derived from physical governing equations of the industrial scale system and was validated under the hot and humid climate conditions of Thailand, along with fluctuation of temperature and humidity of the ambient air. The control law was developed by employing Multi-Sliding Modes control scheme. The uncertainty learning and compensation technique were applied to eliminate the unknown nonlinear characteristic and disturbances of the system. The simulation result indicated that the proposed controller was able to improve the control performance of the plant comparing to traditional on/off control, and robust adaptive PI control law provided in previous work. The saturation of control input did not occur while the system response showed fluctuation-free.