This paper presents a novel data-driven nested optimization framework that addresses the
problem of coupling between plant and controller optimization. This optimization strategy is …

This paper presents a novel data-driven nested optimization framework that aims to solve
the problem of coupling between plant and controller optimization. This optimization strategy …

This paper presents and experimentally evaluates a nested combined plant and controller
optimization (co-design) strategy that is applicable to complex systems that require …

This paper presents a nested codesign (combined plant and controller design) formulation
that uses optimal design of experiments (DoE) techniques at the upper level to globally …

This paper presents a framework by which a data-driven optimization technique known as
Bayesian Optimization can be used for real-time optimal control. In particular, Bayesian …

This paper presents a combined plant and controller optimization process for airborne wind
energy systems (AWEs) that fuses numerical optimization with lab-scale experimental …

This paper presents a unique nested optimization framework for the co-design of a physical
system (plant) and controller, which leverages optimal Design of Experiments (DoE) …

This study presents a data-driven approach for optimizing the operating altitude of Airborne
Wind Energy (AWE) systems to maximize net energy production. Determining the optimal …

Active power control of wind farms remains an open challenge due to inherent noise in wind
power that arises from uncertain wind speed measurements and plant/model mismatch. To …

This research presents an iterative framework for optimizing the plant and controller for
complex systems by fusing expensive but valuable experiments with cheap yet less accurate …