Physics Informed Neural Net Model for the Parameter Estimation of EV Charger

The impedance-based approach is promising to analyse the harmonic emission and stability of a converter-based system, e.g., an EV fast charging station. When extracting the accurate impedance model of an EV charger, the knowledge of the charger’s circuit and controller parameters is indispensable. However, EV chargers’ manufacturers do not...

Comparison Studies of Estimators for the Generalized Gamma Distribution and New Findings

The Generalized Gamma Distribution (GGD) is a three-parameter distribution with desirable properties. For certain values of the parameters, the GGD can reduce to the gamma, exponential and lognormal distribution, among others. This makes it a flexible distribution that can be used in various scenarios. The problem with implementation of the GGD...

Determining operating parameters for Reverse Water Gas Shift reaction with respect to carbon formation and methanation for syngas production

CO2 is the major contributor of green houses gases in the atmosphere. Two notable branches that revolutionized the approach toward reducing the CO2 in the atmosphere are Carbon Capture Storage (CCS) and Carbon Capture Utilization (CCU). CCS has its shortcomings in the long run, a study from MIT shows that the united states have an adequate land...

Bayesian system identification of civil engineering structures using high resolution optic fibre measurements and surrogate modelling

Bayesian system identification has been extensively adopted in Structural Health Monitoring as a way to probabilistically infer unobservable parameters of the physical model of a structure using measurement data. Combining the Bayesian approach with distributed optic fibre sensors can potentially improve the accuracy and reduce the uncertainty...

An effective scheme of joint migration inversion in the pseudo-time domain

Traditional full-waveform inversion is a non-linear and ill-posed inversion problem. To reduce the non-linearity of it, joint migration inversion (joint migration inversion) was proposed as an alternative. Joint migration inversion tries to minimize the mismatch between measured and modelled reflection data. One key feature of joint migration...

Real-time train motion parameter estimation using an Unscented Kalman Filter

Train movement dynamics are usually modelled by means of Newton's second law. The resulting dynamic equation can be very precise if the parameters that it depends on are determined accurately. However, these parameters may vary in time and show wide variations, making the calibration task nontrivial and jeopardizing the performance of a broad...

On the Convergence of DEM’s Linear Parameter Estimator

The free energy principle from neuroscience provides an efficient data-driven framework called the Dynamic Expectation Maximization (DEM), to learn the generative model in the environment. DEM’s growing potential to be the brain-inspired learning algorithm for robots demands a mathematically rigorous analysis using the standard control system...

Efficient temperature estimation for thermally stratified storage tanks with buoyancy and mixing effects

Estimating the state thermal storage devices is key to use them efficiently to reduce the uncertainty of renewable sources. Although stratified storage tanks are one of the most efficient and cost-effective storage systems, they lack accurate state estimation methods. In this paper, we propose a general methodology for estimating the state of...

Parameter estimation for a global tide and surge model with a memory-efficient order reduction approach

Accurate parameter estimation for the Global Tide and Surge Model (GTSM) benefits from observations with long time-series. However, increasing the number of measurements leads to a large computation demand and increased memory requirements, especially for the ensemble-based methods that assimilate the measurements at one batch. In this study,...

Embedding Adaptive Features in the ArduPilot Control Architecture for Unmanned Aerial Vehicles

The operation of Unmanned Aerial Vehicles (UAVs) is often subject to state-dependent alterations and unstructured uncertainty factors, such as unmodelled dynamics, environmental weather disturbances, aerodynamics gradients, or changes in inertia and mass due to payloads. While a large number of autopilot solutions have been proposed to operate...

System Parameter Identification of Thermal Generation Unit in the Mongolian Electrical Grid: Real-Life Frequency Response Test

Mongolian power grid (MPG) is becoming more eco-friendly as the power system is continuously integrating renewable energy, which reached 20% of the total installed capacity of Mongolia in 2020. The daily operation and the safety of the MPG have become very challenging because of increased levels of energy in the system. Therefore, the dynamic...

Modelling, analysis and verification of the biological coherent feedforward loop network

The world of molecular biology is composed by a complex network of interactions that are analogous to electric circuits. They govern the functions required for life, from metabolism to locomotion. In these networks, the presence of network motifs were identified, recurring elements supposedly kept by evolution. One of them is called the...

Analysing confidence intervals with a strict method: The difference between the classic and a conditional testing-estimation

How humans use preview information in manual control

The introduction of ever-advancing automatic control systems is rapidly changing traditional manual control tasks such as piloting of aircraft and steering of cars. In order to predict how human controllers will interact with new technology, a thorough understanding of the human’s adaptive manual control capabilities and limitations is essential...

Rheological characterisation of concentrated domestic slurry

The much over-looked element in new sanitation, the transport systems which bridge the source and treatment facilities, is the focus of this study. The knowledge of rheological properties of concentrated domestic slurry is essential for the design of the waste collection and transport systems. To investigate these properties, samples were...

QUInSAR: Temporal Parameter and Ambiguity Estimation Using Recursive Least-Squares: A Methodology for Persistent Scatterer Interferometry

Parameter and ambiguity estimation in the temporal domain, for arcs of differential phase observations between two persistent scatterers (PS), is a critical part in Persistent Scatterer Interferometry (PSI). Deformation models, used as constraint in the parameter estimation, often do not capture the full extent of the deformation behaviour. This...

3D surface-wave estimation and separation using a closed-loop approach

Surface waves in seismic data are often dominant in a land or shallow-water environment. Separating them from primaries is of great importance either for removing them as noise for reservoir imaging and characterization or for extracting them as signal for near-surface characterization. However, their complex properties make the surface-wave...

Model-based Individualization of Human-like Steering Controllers: Parameter Estimation of a Cybernetic Steering Model Using Global Optimization Technique

Current autonomous steering controllers are designed based on either optimal control strategies or on average human driver steering behavior. Individual drivers may wish to steer differently than those controllers do. Such conflicts can be mitigated by customizing individual steering behavior. This thesis aims to develop a method to...