Self-Calibration of Acoustic Scalar and Vector Sensor Arrays

In this work, we consider the self-calibration problem of joint calibration and direction-of-Arrival (DOA) estimation using acoustic sensor arrays. Unlike many previous iterative approaches, we propose solvers that can be readily used for both linear and non-linear arrays for jointly estimating the sensor gain, phase errors, and the source...

Multi-leader Adaptive Cruise Control Systems considering Sensor Measurement Uncertainties based on Deep Reinforcement Learning

Adaptive Cruise Control (ACC) relieves human drivers’ tasks by taking over the control of the throttle and braking of the vehicles automatically. However, it has been demonstrated in many empirical studies that current production ACC systems fail to guarantee string stability. It is believed that if vehicles can take the longitudinal dynamics...

Robust Output Regulation: Optimization-Based Synthesis and Event-Triggered Implementation

In this article, we investigate the problem of practical output regulation, i.e., to design a controller that brings the system output in the vicinity of a desired target value while keeping the other variables bounded. We consider uncertain systems that are possibly nonlinear and the uncertainty of their linear parts is modeled element wise...

A Two-Stage Bayesian optimisation for Automatic Tuning of an Unscented Kalman Filter for Vehicle Sideslip Angle Estimation

This paper presents a novel methodology to auto-tune an Unscented Kalman Filter (UKF). It involves using a Two-Stage Bayesian Optimisation (TSBO), based on a t-Student Process to optimise the process noise parameters of a UKF for vehicle sideslip angle estimation. Our method minimises performance metrics, given by the average sum of the states’...

Finite-sample analysis of identification of switched linear systems with arbitrary or restricted switching

For the identification of switched systems with measured states and a measured switching signal, this work aims to analyze the effect of switching strategies on the estimation error. The data is assumed to be collected from globally asymptotically or marginally stable switched systems under switches that are arbitrary or subject to an average...

Three Symmetries for Data-Driven Pedestrian Inertial Navigation

The last years have seen a growing body of literature on data-driven pedestrian inertial navigation. However, despite this, it is still unclear how to efficiently combine classical models and other a priori information with existing machine learning frameworks. In this paper, we first categorize existing approaches to data-driven pedestrian...

On Learning Discrete-Time Fractional-Order Dynamical Systems

Discrete-time fractional-order dynamical systems (DT-FODS) have found innumerable applications in the context of modeling spatiotemporal behaviors associated with long-term memory. Applications include neurophysiological signals such as electroencephalogram (EEG) and electrocorticogram (ECoG). Although learning the spatiotemporal parameters of...

Informative Path Planning in Random Fields via Mixed Integer Programming

We present a new mixed integer formulation for the discrete informative path planning problem in random fields. The objective is to compute a budget constrained path while collecting measurements whose linear estimate results in minimum error over a finite set of prediction locations. The problem is known to be NP-hard. However, we strive to...

Data-enabled predictive control with instrumental variables: the direct equivalence with subspace predictive control

Direct data-driven control has attracted substantial interest since it enables optimization-based control without the need for a parametric model. This paper presents a new Instrumental Variable (IV) approach to Data-enabled Predictive Control (DeePC) that results in favorable noise mitigation properties, and demonstrates the direct equivalence...

Sensitivities and prerequisites of the application of the Energy Flux Analysis to high-rise structures excited by wind using in situ measurements: Case: New Orleans tower, Rotterdam

As buildings get taller and lighter, structural engineers are increasingly faced with the consequences of the dynamic response of high-rise buildings to wind. Damping is an important property for the dynamic response of high-rise structures, but is a combination of many mechanisms, which makes it a complex phenomenon to account for in the...

Privatized distributed anomaly detection for large-scale nonlinear uncertain systems

In this article two limitations in current distributed model based approaches for anomaly detection in large-scale uncertain nonlinear systems are addressed. The first limitation regards the high conservativeness of deterministic detection thresholds, against which a novel family of set-based thresholds is proposed. Such set-based thresholds...

Co-operation and haptic assistance for tele-manipulated control over two asymmetric slaves

The success of future fusion power plants as a sustainable energy source greatly depends on their uptime. This uptime relies on the plant's maintenance, which must be performed via tele-manipulation. Tele-manipulated maintenance is challenging, as exemplified by strictly selected and highly trained operators who still require more time to work...

Drag resolution of a PIV wake rake for transiting models

The accuracy of the “PIV wake rake” method to measure the drag of transiting objects is evaluated. Tomographic Particle Image Velocimetry measurements are conducted on a sphere towed at different speeds, within a Reynolds number range where the drag coefficient is constant. In contrast to PIV wake rake application on steady models in wind...

Underwater Source Localization Using TDOA and FDOA Measurements with Unknown Propagation Speed and Sensor Parameter Errors

Underwater source localization problems are complicated and challenging: a) the sound propagation speed is often unknown and the unpredictable ocean current might lead to the uncertainties of sensor parameters (i.e. position and velocity); b) the underwater acoustic signal travels much slower than the radio one in terrestrial environments,...

Considering rain gauge uncertainty using kriging for uncertain data

In urban hydrological models, rainfall is the main input and one of the main sources of uncertainty. To reach sufficient spatial coverage and resolution, the integration of several rainfall data sources, including rain gauges and weather radars, is often necessary. The uncertainty associated with rain gauge measurements is dependent on...

Quantum preparation uncertainty and lack of information

The quantum uncertainty principle famously predicts that there exist measurements that are inherently incompatible, in the sense that their outcomes cannot be predicted simultaneously. In contrast, no such uncertainty exists in the classical domain, where all uncertainty results from ignorance about the exact state of the physical system....

High-accuracy absolute distance measurement with a mode-resolved optical frequency comb

Optical interferometry enables highly accurate non-contact displacement measurement. The optical phase ambiguity needs to be resolved for absolute distance ranging. In controlled laboratory conditions and for short distances it is possible to track a non-interrupted displacement from a reference position to a remote target. With large...