Underactuated mechanical systems (UMS) feature prominently in robotics and aerospace, with aircraft, unmanned air vehicles, and aeroelastic wings as prime examples. These systems present multifaceted control challenges, ranging from inherent underactuation and stability concerns to state and control saturation and an overarching need for robustness. Crucially, reducing model dependency is a key strategy to enhance control robustness. Nonlinear Model Predictive Control (NMPC) is valued for addressing underactuation and constraints within complex nonlinear dynamics while considering future stages for immediate decision-making. However, implementing NMPC in UMS can pose challenges due to model uncertainties and external disturbances. To enhance NMPC's robustness in UMS control, we introduce a disturbance rejection NMPC strategy, which is tightly coupled with the incremental nonlinear dynamic inversion (INDI), a sensor-based adaptive control approach. The INDI is expected to reject most of the disturbances. Any disturbance residues are managed within a robust NMPC framework through constraint tightening. The efficacy of our method is exemplified through its application to two distinct UMS models. The proposed controller is first customized for a nonlinear aeroelastic system. Compared to the nominal NMPC, the simulation studies demonstrate up to 37.60% and 40.00% error reductions in plunge and pitch motions. Subsequently, we adapt this controller for quadrotor trajectory tracking tasks and compare the results with a benchmark control strategy that loosely coupled the NMPC with INDI. Extensive simulation validations have been performed to track agile trajectories, showing up to a 79.58% reduction in position error and up to a
44.08% reduction in heading error.

This chapter focuses on mainland coastal towns that have populations of between 10,000 and 50,000 inhabitants. Through six case studies, the chapter develops an understanding of the characteristics that shape each of the communities. By exploring the climate change hazards each of the case studies are experiencing now and forecast into the future, the physical and ecological profile and the human development condition, a view of the climate impacts for each is shaped. The six case study areas include towns that are large enough to be a regional centre, down to much less organised and resourced communities that are at a more subsistence level of development. The case studies include communities that range from tropical storm areas to more temperate climatic areas. Adaptation strategies for each case study are observed, drawing out the similarities and the differences. Insights and lessons learnt show that the bottom-up inclusion of all communities in shaping the adaptation approach is crucial, together with alignment of policy between governments from national to local. Also crucial is the resourcing of local councils which sit on the front line of many adaptation initiatives. The role of universities and other research organisations to provide data, skills training and a toolbox of methodologies to those in the front line leadership roles. An important insight is the collaborative opportunity for universities, communities and agencies to draw out the innovative adaptation strategies that can inform other coastal communities from the smallest village to the largest city.