A stochastic control model is proposed as a paradigm for the design of optimal timing of greenhouse gases (GHG) emissions abatement. The resolution of uncertainty concerning climate sensitivity and the technological breakthrough providing access to a carbon-free production economy are modeled as controlled stochastic jump processes. The optimal policy is characterized using the dynamic programm...

Information federations promise an enhanced collaboration between individual stakeholders in the life cycle of commercial products, including software and hardware products from arbitrary business sectors. However, information sharing across corporate borders must be controlled by tailored mechanisms for enforcing individual business confidentiality and integrity requirements. One influential c...

In this report, we reexamine the foundations of classical control theory with reference to eigenvalue geometry via a new set of graphical controls tools, gain plots. These plots depict eigenvalue trajectory as an explicit function of gain. Various classical control concepts are generalized in nine theorems and demonstrated in three simple, yet pedagogical, examples. University Libraries Carnegi...

High-precision positioning of two underwater mobile robots is investigated in this work. To achieve good performance communication, control algorithms are implemented to maintain the position receiver robot aligned with that transmitter presence measurement noise and process uncertainty. Although recent research works have successfully integrated Extended Kalman Filter (EKF) estimator track des...

Inspired by the success of control barrier functions (CBFs) in addressing safety, and rise data-driven techniques for modeling functions, we propose a non-parametric approach online synthesis CBFs using Gaussian Processes (GPs). A dynamical system is defined to be safe if subset its states remains within prescribed set, also called <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xl...