skip to main content
US FlagAn official website of the United States government
dot gov icon
Official websites use .gov
A .gov website belongs to an official government organization in the United States.
https lock icon
Secure .gov websites use HTTPS
A lock ( lock ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.

Explore Research Products in the PAR
It may take a few hours for recently added research products to appear in PAR search results.


  • NSF Public Access
  • Search Results
  • A Reinforcement Learning-Based Hierarchical Speed Control of an Infinitely Variable Transmission for Tidal Current Energy Converters
Title: A Reinforcement Learning-Based Hierarchical Speed Control of an Infinitely Variable Transmission for Tidal Current Energy Converters
Abstract A tidal current energy converter (TCEC) is a device specifically designed to harness the kinetic energy present in tidal energy and convert it into stable mechanical rotational energy, which can then be used to generate electricity. The core component of the TCEC is an infinitely variable transmission (IVT), which adjusts the speed ratio to maintain a stable output speed regardless of the input speed changes caused by tidal changes. In order to ensure the efficient driving performance of the IVT system, a closed-loop control strategy based on IVT state measurement data is studied in this paper. This method can effectively track the expected output speed of the IVT system in general TCEC. Based on the proposed speed control strategy, the speed regulation of the whole IVT system under different conditions is studied in theory and simulation. These promising results could directly contribute to future research to improve the efficiency of tidal energy harvesting.  more » « less
Award ID(s):
2329791
PAR ID:
10612859
Author(s) / Creator(s):
; ;
Publisher / Repository:
American Society of Mechanical Engineers
Date Published:
ISBN:
978-0-7918-8789-9
Format(s):
Medium: X
Location:
Anaheim, California, USA
Sponsoring Org:
National Science Foundation
More Like this
  1. ; ; ; (, Machines)
    This study investigates dynamic behaviors of hypoid gear rotor systems under variable tidal current energy harvesting conditions through numerical simulations and experimental validation. The study examines dynamic responses of a hypoid gear rotor system induced by cyclical tidal current variations, which generate fluctuating loads and bidirectional rotational speeds in tidal energy conversion systems. Two hypoid gear pairs, modified through precise manufacturing parameters, are evaluated to optimize tooth contact patterns for bidirectional tidal loading conditions. A coupled torsional vibration model is developed, incorporating variable transmission error and mesh stiffness. Experimental validation of dynamic performances of hypoid gear pairs was conducted on a bevel gear testing rig, which can measure both torsional and translational vibrations across diverse tidal speed profiles. The experimental results demonstrate that second-order primary resonances exhibit heightened vibration intensity during flow-reversal phases. This phenomenon has significant implications for system power efficiency and acoustic emissions. The findings extend the current understanding of hypoid gear optimization for tidal energy-harvesting applications. 
    more » « less
  2. ; ; (, IET Generation, Transmission & Distribution)
    Abstract The ability to withstand and recover from disruptions is essential for seaport energy systems, and in light of the growing push for decarbonization, incorporating clean energy sources has become increasingly imperative to ensure resilience. This paper proposes a resilience enhancement planning strategy for a seaport multi‐energy system that integrates various energy modalities and sources, including heating, cooling, hydrogen, solar, and wind power. The planning strategy aims to ensure the reliable operation of the system during contingency events, such as power outages, equipment failures, or extreme weather incidents. The proposed optimization model is designed as a mixed‐integer nonlinear programming formulation, in which McCormick inequalities and other linearization techniques are utilized to tackle the model nonlinearities. The model allocates fuel cell electric trucks (FCETs), renewable energy sources, hydrogen refueling stations, and remote control switches such that the system resilience is enhanced while incorporating natural‐gas‐powered combined cooling, heating, and power system to minimize the operation and unserved demand costs. The model considers various factors such as the availability of renewable energy sources, the demand for heating, cooling, electricity, and hydrogen, the operation of remote control switches to help system reconfiguration, the travel behaviour of FCETs, and the power output of FCETs via vehicle‐to‐grid interface. The numerical results demonstrate that the proposed strategy can significantly improve the resilience of the seaport multi‐energy system and reduce the risk of service disruptions during contingency scenarios. 
    more » « less
  3. (, 2022 IEEE 61st Conference on Decision and Control (CDC))
    This paper investigates a control strategy in which the state of a dynamical system is driven slowly along a trajectory of stable equilibria. This trajectory is a continuum set of points in the state space, each one representing a stable equilibrium of the system under some constant control input. Along the continuous trajectory of such constant control inputs, a slowly varying control is then applied to the system, aimed to create a stable quasistatic equilibrium that slowly moves along the trajectory of equilibria. As a stable equilibrium attracts the state of system within its vicinity, by moving the equilibrium slowly along the trajectory of equilibria, the state of system travels near this trajectory alongside the equilibrium. Despite the disadvantage of being slow, this control strategy is attractive for certain applications, as it can be implemented based only on partial knowledge of the system dynamics. This feature is in particular important for the complex systems for which detailed dynamical models are not available. 
    more » « less
  4. (, Mathematische Nachrichten)
    Abstract Three control problems for the system of two coupled differential equations governing the dynamics of an energy harvesting model are studied. The system consists of the equation of an Euler–Bernoulli beam model and the equation representing the Kirchhoff's electric circuit law. Both equations contain coupling terms representing the inverse and direct piezoelectric effects. The system is reformulated as a single evolution equation in the state space of 3‐component functions. The control is introduced as a separable forcing term on the right‐hand side of the operator equation. The first control problem deals with an explicit construction of that steers an initial state to zero on a time interval [0,T]. The second control problem deals with the construction of such that the voltage output is equal to some given function (with being given as well). The third control problem deals with an explicit construction of both the force profile, , and the control, , which generate the desired voltage output . Interpolation theory in the Hardy space of analytic functions is used in the solution of the second and third problems. 
    more » « less
  5. ; ; ; ; ; ; ; ; (, Review of Scientific Instruments)
    Active feedback control in magnetic confinement fusion devices is desirable to mitigate plasma instabilities and enable robust operation. Optical high-speed cameras provide a powerful, non-invasive diagnostic and can be suitable for these applications. In this study, we process high-speed camera data, at rates exceeding 100 kfps, on in situ field-programmable gate array (FPGA) hardware to track magnetohydrodynamic (MHD) mode evolution and generate control signals in real time. Our system utilizes a convolutional neural network (CNN) model, which predicts the n = 1 MHD mode amplitude and phase using camera images with better accuracy than other tested non-deep-learning-based methods. By implementing this model directly within the standard FPGA readout hardware of the high-speed camera diagnostic, our mode tracking system achieves a total trigger-to-output latency of 17.6 μs and a throughput of up to 120 kfps. This study at the High Beta Tokamak-Extended Pulse (HBT-EP) experiment demonstrates an FPGA-based high-speed camera data acquisition and processing system, enabling application in real-time machine-learning-based tokamak diagnostic and control as well as potential applications in other scientific domains. 
    more » « less
  • Citation Formats
  • MLA
  • APA
  • Chicago
  • BibTeX
  • Save / Share this Record
  • Send to Email