相关论文: Hybrid Model-Based and Data-Driven Wind Velocity E…

The use of state estimation technique offers a means of inferring the rotor-effective wind speed based upon solely standard measurements of the turbine. For the ease of design and computational concerns, such estimators are typically built…

To enable autonomous wind estimation for energy-efficient flight in small unmanned aerial vehicles (UAVs), this study proposes a method that estimates flight states and wind using only the low-cost essential onboard sensors required for…

Present energy demand and modernization are leading to greater fossil fuel consumption, which has increased environmental pollution and led to climate change. Hence to decrease dependency on conventional energy sources, renewable energy…

This thesis presents a solution that enables aerial robots to reason about surrounding wind flow fields in real time using on board sensors and embedded flight hardware. The core novelty of this research is the fusion of range measurements…

Accurate real-time wind vector estimation is essential for enhancing the safety, navigation accuracy, and energy efficiency of unmanned aerial vehicles (UAVs). Traditional approaches rely on external sensors or simplify vehicle dynamics,…

Unmanned Aerial Vehicles (UAVs) play a crucial role in meteorological research, particularly in environmental wind field measurements. However, several challenges exist in current wind measurement methods using UAVs that need to be…

Control performance of Unmanned Aerial Vehicles (UAVs) is directly affected by their ability to estimate their states accurately. With the increasing popularity of autonomous UAV solutions in real world applications, it is imperative to…

Modern autonomous navigation for unmanned ground vehicles relies on different estimators to fuse inertial sensors and GNSS measurements. However, the constant noise covariance matrices often struggle to account for dynamic real-world…

The fusion between an inertial navigation system and global navigation satellite systems is regularly used in many platforms such as drones, land vehicles, and marine vessels. The fusion is commonly carried out in a model-based extended…

In this paper, we consider the problem of multirotor flying robots physically interacting with the environment under wind influence. The result are the first algorithms for simultaneous online estimation of contact and aerodynamic wrenches…

Hybrid wind-wave energy system, integrating floating offshore wind turbine and wave energy converters, has received much attention in recent years due to its potential benefit in increasing the power harvest density and reducing the…

An unscented Kalman filter with joint state and parameter estimation is proposed for aerodynamics, states and wind conditions for airborne wind energy converters. The proposed estimator relies on different measurement setups. Due to the…

This paper presents an external wrench estimator that uses a hybrid dynamics model consisting of a first-principles model and a neural network. This framework addresses one of the limitations of the state-of-the-art model-based wrench…

The rapid growth of the wind energy sector underscores the urgent need to optimize turbine operations and ensure effective maintenance through early fault detection systems. While traditional empirical and physics-based models offer…

The literature is rich with studies, analyses, and examples on parameter estimation for describing the evolution of chaotic dynamical systems based on measurements, even when only partial information is available through observations.…

This paper develops a hybrid system modeling framework for inverters that switch between grid-following and grid-forming control schemes. In particular, such inverters are modeled as hybrid automata with guard conditions on voltage and…

We develop data-driven algorithms to fully automate sensor fault detection in systems governed by underlying physics. The proposed machine learning method uses a time series of typical behavior to approximate the evolution of measurements…

In this article, we study the well known problem of wind estimation in atmospheric turbulence using small unmanned aerial systems (sUAS). We present a machine learning approach to wind velocity estimation based on quadcopter state…

Attitude estimation for small, low-cost unmanned aerial vehicles is often achieved using a relatively simple complementary filter that combines onboard accelerometers, gyroscopes, and magnetometer sensing. This paper explores the limits of…

The autonomous operation of flexible-wing aircraft is technically challenging and has never been presented within literature. The lack of an exact modeling framework is due to the complex nonlinear aerodynamic relationships governed by the…