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The aim of this chapter is to provide an introduction to the field programmable gate array (FPGA)-based digital control system design for motion control. It is intended as a reference for the undergraduate students in science and engineering, professionals, and enthusiastic people who have a basic knowledge in discrete control theory and digital systems using reconfigurable logic. The scope of this chapter includes the analysis, simulation, and implementation of classic control algorithms. The presented topics serve as a foundation for the implementation of more complex systems. An experimental section is provided, which validates the proposed digital design.

Computational models are increasingly being used for the dynamic analysis of structures with nonlinear or uncertain behavior, such as cables in stayed bridges, which nowadays are progressively more used as an alternative for long span and slim structures. In this work, a 3D nonlinear model is described to evaluate the wind dynamic effects on cables for this type of bridges under different scenarios, but also for health monitoring and structural simulation to guarantee performance, evaluate load capacity and estimate life prediction. Fatigue is one of the most relevant and complex failure causes in highway bridges, particularly on the anchorage elements of the cables in stayed bridges; where dampers may be used to minimize the dynamic behavior of the structure and reduce fatigue damage. With this nonlinear simulation model, different damper locations and configurations are evaluated to find the optimal position. A feasibility function is used as a weighting function to take into account the damper's size and design. Analysis is particularly focused for a real cable stayed bridge in the state of Veracruz in México.Although the geometry, the forces and the stresses on cable structures are a challenge, even for structural specialists, the results from this work using the proposed 3D nonlinear model showed to be accurate for the simulation of many different wind scenarios, and damper's location and orientations. Finally, the feasibility weighting function enabled the geometrical limitations to estimate the best location of a damper system to minimize the risk for fatigue failure.