Haotian Chen

High-efficiency real-time rice leaf disease classification using convolutional neural network accelerator on FPGA for edge computing in precision agriculture

Jingwen Zheng, Zhengbing Lv, Dayang Li, Chengbo Lu et autres

cn (code pays fourni par la source)

A Barometer-Enhanced State Adaptive Indirect Kalman Filter for 3-D Indoor Navigation

Zhipeng Sun, Haotian Chen, Jian Chu, Jinhui Song

In order to achieve accurate 3D indoor positioning, a state adaptive indirect Kalman filter (SA-IKF) framework is proposed, which integrates the state recognition algorithm and the barometric height constraint algorithm. The state recognition algorithm can enhance the horizontal positioning by identifying three …

cn (code pays fourni par la source)

Are Politicians Responsive to Mass Shootings? Evidence from U.S. State Legislatures

Haotian Chen, Jack Kappelman

The United States leads the world in the number of mass shootings that occur each year, even as policy making on firearms remains polarized along party lines. In the face of increasing violence and public demand for policy action, we ask whether …

Analysis and Design of Suspension State Observer for Wheel Load Estimation

Tianyi Zeng, Zeyu Liu, Chenyu He, Zimo Zeng et autres

Tire forces and moments play an important role in vehicle dynamics and safety. X-by-wire chassis components including active suspension, electronic powered steering, by-wire braking, etc can take the tire forces as inputs to improve vehicle’s dynamic performance. In order to measure the …

cn (code pays fourni par la source)

Wheel Load Estimation and Anti-Roll Bar Control Using Suspension Analysis with Neural Network

Tianyi Zeng, Tianyi Wang, Liyang Yu, Zeyu Liu et autres

cn (code pays fourni par la source)

Virtual Synchronous Generator Control Using Twin Delayed Deep Deterministic Policy Gradient Method

Oroghene Oboreh-Snapps, Buxin She, Shah Fahad, Haotian Chen et autres

This article presents a data-driven approach that adaptively tunes the parameters of a virtual synchronous generator to achieve optimal frequency response against disturbances. In the proposed approach, the control variables, namely, the virtual moment of inertia and damping factor, are transformed into …

us (code pays fourni par la source)

Real-time engine model development based on time complexity analysis

Haotian Chen, Kun Zhang, Kangyao Deng, Yi Cui

Real-time simulation models play an important role in the development of engine control systems. The mean value model (MVM) meets real-time requirements but has limited accuracy. By contrast, a crank-angle resolved model, such as the filling -and-empty model, can be used to …

cn (code pays fourni par la source)

Modeling State Transition and Head-Dependent Efficiency Curve for Pumped Storage Hydro in Look-Ahead Dispatch

Siyuan Wang, Jian Liu, Haotian Chen, Rui Feng Bo et autres

As one of the most widely installed utility-scale storage facilities, pumped storage hydro (PSH) plays an essential role in providing flexibility for power systems worldwide. Thus, to accurately quantify the flexibility of PSH units in operational optimization problems is important. The conventional …

us (code pays fourni par la source)

Optimal scheduling for profit maximization of energy storage merchants considering market impact based on dynamic programming

Jian Liu, Rui Feng Bo, Siyuan Wang, Haotian Chen

us (code pays fourni par la source)

Cross-Market Price Difference Forecast Using Deep Learning for Electricity Markets

Ronit Das, Rui Feng Bo, Waqas ur Rehman, Haotian Chen et autres

Price forecasting is in the center of decision making in electricity markets. Many researches have been done in forecasting energy prices while little research has been reported on forecasting price difference between day-ahead and real-time markets due to its high volatility, which …

us (code pays fourni par la source)

Exploring Reinforcement Learning Method in Bidding Strategy Development for Day-Ahead Electricity Market

Haotian Chen, Rui Feng Bo, Ronit Das, Donald C. Wunsch

This paper introduces the detailed process of applying reinforcement learning to solve market participant bidding strategy problem. The process includes the setup of market clearing environment, reinforcement learning structure, and Q-learning algorithm. A comprehensive study on three specially designed problems demonstrates the …

us (code pays fourni par la source)

Estimating and Controlling the Renewable Microgrid States Using IoT Infrastructure

Md Masud Rana, Rui Feng Bo, Haotian Chen

Abstract This paper considers the optimal filter design issue for microgrid state estimation and stabilisation under packet loss conditions. The considered internet of things (IoT) technologies collect system state information from sensors and send control messages to actuators where they are connected …

us (code pays fourni par la source)