It has been proven that advanced building control, like model predictive control (MPC), can
notably reduce the energy use and mitigate greenhouse gas emissions. However, despite …

Abstract Process Systems Engineering (PSE) is the scientific discipline of integrating scales
and components describing the behavior of a physicochemical system, via mathematical …

Quadrotors are among the most agile flying robots. However, planning time-optimal
trajectories at the actuation limit through multiple waypoints remains an open problem. This …

Accurate trajectory-tracking control for quadrotors is essential for safe navigation in cluttered
environments. However, this is challenging in agile flights due to nonlinear dynamics …

In this article, we present an optimization-based framework for multicopter trajectory
planning subject to geometrical configuration constraints and user-defined dynamic …

Gaussian process (GP) regression has been widely used in supervised machine learning
due to its flexibility and inherent ability to describe uncertainty in function estimation. In the …

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This paper introduces GEKKO as an optimization suite for Python. GEKKO specializes in
dynamic optimization problems for mixed-integer, nonlinear, and differential algebraic …

OpenModelica is a unique large-scale integrated open-source Modelica-and FMI-based
modeling, simulation, optimization, model-based analysis and development environment …

Many practical applications lead to optimization problems that can either be stated as
quadratic programming (QP) problems or require the solution of QP problems on a lower …