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This paper presents two wind energy forecast methods for control of an airborne wind energy system (AWE). The primary objective is to maximize the energy production of the AWE system under a spatio-temporally varying environment with uncertainty in the future wind speed. The controller for the AWE system is formulated as a model predictive controller (MPC). We employ data-driven models to generate probabilistic forecasts of the wind using vector auto-regression (VAR) and time-of-day forecasts. Bayesian optimization is employed to find the optimum of an unknown and expensive to evaluate...

Lithium-ion battery electrode-level online state estimation using high-fidelity nonlinear electrochemical models remains a key challenge. This is particularly due to weak observability inherited from the complex model structure, even for reduced-order electrochemical models. This letter presents a systematic and rigorous strategy to analyze the local observability of a single particle model (SPM) with both electrodes, which is commonly known to be locally unobservable from current-voltage measurements. Estimating the essential states, e.g., state of charge (SOC) and solid-phase lithium...

Numerous mobile robotic applications require agents to persistently explore and exploit spatiotemporally varying, partially observable environments. Ultimately, the mathematical notion of regret, which quite simply represents the instantaneous or time-averaged difference between the optimal reward and realized reward, serves as a meaningful measure of how well the agents have exploited the environment. However, while numerous theoretical regret bounds have been derived within the machine learning community, restrictions on the manner in which the environment evolves preclude their...

This paper examines both mathematical formulation and practical implementation of an ecological adaptive cruise controller (ECO-ACC) with connected infrastructure. Human errors are typical sources of accidents in urban driving, which can be remedied by rigorous control theories. Designing an ECO-ACC is, therefore, a classical research problem to improve safety and energy efficiency. We add two main contributions to the literature. First, we propose a mathematical framework of an online ECO-ACC for plug-in hybrid electric vehicle (PHEV). Second, we demonstrate ECO-ACC in a real world, which...