相关论文: A Central Chilled Water Plant Model for Designing …
Greenhouse climate control is concerned with maximizing performance in terms of crop yield and resource efficiency. One promising approach is model predictive control (MPC), which leverages a model of the system to optimize the control…
Wave energy conversion is emerging as a promising technology for generating energy from renewable sources. Large-scale implementation of this technology requires the installation of parks of devices. We study the problem of optimizing the…
3D integrated circuit (3D-IC) technology gained acceptance due to the ability to achieve extremely high level of integration, where hundreds of ICs are stacked vertically. Such level of integration can result in local power dissipation of…
We develop a mathematical framework for the optimal scheduling of flexible water desalination plants (WDPs) as hybrid generator-load resources. WDPs integrate thermal generation, membrane-based controllable loads, and renewable energy…
Combating the detrimental effects of noise remains a major challenge in realizing a scalable quantum computer. To help to address this challenge, we introduce a model realizing a controllable qubit-bath coupling using a sequence of LC…
A novel framework for closed-loop control of turbulent flows is tested in an experimental mixing layer flow. This framework, called Machine Learning Control (MLC), provides a model-free method of searching for the best function, to be used…
This note presents the design and analysis of an adaptive controller for a class of linear plants in the presence of output feedback. This controller makes use of a closed-loop reference model as an observer, and guarantees global stability…
There are six service buildings uniformly spaced along the perimeter of MI (Main Injector). A total of 18 LCW pumps were installed around the MI ring with 3 pumps per building. Approximately 8,000 GPM of LCW is required to cool magnets, bus…
Water treatment facilities are critical infrastructure they must accommodate dynamic demand patterns without system disruption. These patterns can be scheduled, such as daily residential irrigation, or unexpected, such as demand spikes from…
Parabolic trough Concentrating Solar Power (CSP) plants operate large hydraulic networks of collector loops that must deliver a uniform outlet temperature despite spatially heterogeneous optical performance, heat losses, and pressure drops.…
We present a three-way catalyst (TWC) cold-start model, calibrate the model based on experimental data from multiple operating points, and use the model to generate a Pareto-optimal cold-start controller suitable for implementation in…
This work presents a case study of optimal energy management of a large Heating Ventilation and Cooling (HVAC) system within a university campus in Australia using Reinforcement Learning (RL). The HVAC system supplies to nine university…
Capacitors are typically connected together in one of two configurations: either in series, or in parallel. Here we study a capacitor-within-capacitor (CWC). Simulations and experiments indicate that the overall capacitance of the…
Energy consumption for hot water production is a major draw in high efficiency buildings. Optimizing this has typically been approached from a thermodynamics perspective, decoupled from occupant influence. Furthermore, optimization usually…
A centralized model predictive controller (MPC), which is unaware of local uncertainties, for an affine discrete time nonlinear system is presented. The local uncertainties are assumed to be matched, bounded and structured. In order to…
We develop a physics-informed learning framework for energy-shaping control of port-Hamiltonian (pH) systems from trajectory data. The proposed approach co-learns a pH system model and an optimal energy-balancing passivity-based controller…
Thermostatically Controlled Loads (TCLs) such as air conditioners and water heaters typically maintain their temperature within a preset range using on/off actuation. These types of loads are inherently flexible: many different power…
With the current high levels of energy consumption of data centers, reducing power consumption by even a small percentage is beneficial. We propose a framework for thermal-aware workload distribution in a data center to reduce cooling power…
We develop a new approach for efficient and scalable simulations of measurement and control of quantum systems built upon existing phase-space methods, namely the Truncated Wigner Approximation (TWA). We benchmark against existing…
We present a stochastic model predictive control (MPC) framework for central heating, ventilation, and air conditioning (HVAC) plants. The framework uses real data to forecast and quantify uncertainty of disturbances affecting the system…