Algorithms, Volume 13, Issue 3

This paper considers nonlinear model predictive control for simultaneous path-following and collision avoidance of connected autonomous vehicles. For each agent, a nonlinear bicycle model is used to predict a sequence of the states and then optimize...

Uncertainty propagation is used to quantify the uncertainty in model predictions in the presence of uncertain input variables. In this study, we analyze a steady-state point-model for two-phase gas-liquid flow. We present prediction intervals for hol...

Providing useful resources to patients is essential in achieving the vision of participatory medicine. However, the problem of identifying pertinent content for a group of patients is even more difficult than identifying information for just one. Nev...

This paper proposes a fractional-order sliding mode controller (FOSMC) for the robust control of a nonlinear process subjected to unknown parametric disturbances. The controller aims to ensure optimal growth in photobioreactors of native microalgae i...

Approximation and uncertainty quantification methods based on Lagrange interpolation are typically abandoned in cases where the probability distributions of one or more system parameters are not normal, uniform, or closely related distributions, due...