As climate change becomes a more pressing issue, there is increasing research being performed to investigate greenhouse gas reduction strategies such as carbon capture technology and sustainable fuels. To this end, chemical-looping (CL) technologies such as chemical-looping combustion (CLC) and chemical-looping gasification (CLG) are being explored to improve the sustainability of energy generation. In addition, biomass has recently been studied as a renewable fuel for this process. Various works into CL technologies have been performed, but further investigation is required in the areas of process design and control in order to verify whether this technology can feasibly be implemented for energy generation and to determine the most effective implementation strategies for CL processes. The aim of this thesis is to determine reactor design and control strategies which can be implemented to improve the energy generation, gasification efficiency, and carbon capture effectiveness of packed bed CLC and CLG. In this work, optimal control strategies for large-scale packed bed CLC are obtained by implementing nonlinear model predictive control (NMPC). For NMPC, a multiscale model is developed to simulate the plant behaviour and validated against multiple sources of experimental data, while a pseudo-homogeneous model is used as the internal NMPC model to reduce computational costs for implementation of feedback control. By manipulating the inlet air and inert gas fluxes in the oxidation stage, and the inlet fuel flux in the reduction stage, the outlet temperature and CO2 selectivity could be controlled in order to improve the energy generation and carbon capture effectiveness of the process. Then, a reactor network model was proposed to simulate packed bed biomass-fueled CLG and CLC, and validated using experimental data under both CLG and CLC conditions. Using this model, a variety of oxygen carrier (OC) bed lengths and locations were assessed to evaluate the resulting impact on the performance of CLG and CLC. For CLG, ...