Background: A short-term protocol for evaluation of National Football League (NFL) athletes incur... more Background: A short-term protocol for evaluation of National Football League (NFL) athletes incurring concussion has yet to be fully defined and framed in the context of the short-term potential team and career longevity, financial risk, and performance. Purpose: To compare the short-term career outcomes for NFL players with concussions by analyzing the effect of concussions on (1) franchise release rate, (2) career length, (3) salary, and (4) performance.
LHD (load-haul-dump) vehicles are used extensively in underground mining operations for ore trans... more LHD (load-haul-dump) vehicles are used extensively in underground mining operations for ore transporting, primarily in tunnels where access is difficult or dangerous. To ensure underground efficient and safe LHD's performance, a robust feedback control strategy is needed. A state estimation based MPC scheme was designed for control purposes, and evaluated by simulation. The state estimator was developed by testing four approaches, in order to select the optimal one: the extended Kalman Filter, Particle Filter, Moving Horizon Estimator and a genetic algorithm based Moving Horizon Estimatior. The simulation shows that non-linear MPC performs better than linear MPC for path tracking.
Background: A short-term protocol for evaluation of National Football League (NFL) athletes incur... more Background: A short-term protocol for evaluation of National Football League (NFL) athletes incurring concussion has yet to be fully defined and framed in the context of the short-term potential team and career longevity, financial risk, and performance. Purpose: To compare the short-term career outcomes for NFL players with concussions by analyzing the effect of concussions on (1) franchise release rate, (2) career length, (3) salary, and (4) performance.
LHD (load-haul-dump) vehicles are used extensively in underground mining operations for ore trans... more LHD (load-haul-dump) vehicles are used extensively in underground mining operations for ore transporting, primarily in tunnels where access is difficult or dangerous. To ensure underground efficient and safe LHD's performance, a robust feedback control strategy is needed. A state estimation based MPC scheme was designed for control purposes, and evaluated by simulation. The state estimator was developed by testing four approaches, in order to select the optimal one: the extended Kalman Filter, Particle Filter, Moving Horizon Estimator and a genetic algorithm based Moving Horizon Estimatior. The simulation shows that non-linear MPC performs better than linear MPC for path tracking.
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Papers by Sergio Navarro