Ousman Essa2026-02-272023https://etd.ftveti.edu.et/handle/123456789/48As the world population has increased, electricity demand and consumption have risen rapidly in recent years. As a result, fossil fuel costs have risen and the associated air pollution has become a global issue. A biomass boiler power plant is one of the most effective solutions to this problem. The boiler plant is a multi-input, multi-output, time-varying and nonlinear system by nature. The majority of biomass boiler controllers use classical PID controllers. The inability of these classical controllers to control time-varying and nonlinear systems is the source of the plant's poor performance. To make the controller better, first determine the system model of the nonlinear, MIMO and time-varying system by employing a data-driven Radial Basis Function Neural Network model and then input the model result into the model predictive controller.en-USThesis