Pareto optimality based multi-objective genetic algorithm: Application for livestock building system using an independent PID controller

The aim of this research is to stabilize the indoor relative humidity and temperature for the poultry house system. The control of these parameters appears as a big challenge due to the mutual interaction existing between the variables affecting the climate livestock building. To achieve this purpose, a developed independent PID controller based on Pareto optimality is proposed in conjunction with a multi-criterion genetic algorithm (MOGA). The broiler house model is decomposed into two independent single input single output (SISO) model using a static output feedback technique (SOF). Then, a multi-criterion genetic algorithm based on Pareto optimality is used to separately design the optimal parameters of the PID controller. The effectiveness of the developed controller is tested very successfully trough numerical simulations and comparison with the Ant Colony Optimization (ACO) and Ziegler Nichols (ZN) method.