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In dual control, the manipulated variables are used to both regulate the system and identify unknown parameters. The joint probability distribution of the system state and the parameters is known as the hyperstate. The paper proposes a method to perform dual control using a deep reinforcement learning algorithm in combination with a neural network model trained to represent hyperstate transitions.
Accurate characterization of large-scale antenna arrays is growing in importance and complexity for the fifth-generation (5G) and beyond systems, as they feature more antenna elements and require increased overall performance. The full 3D patterns of all antenna elements in the array need to be characterized because they are in general different due to construction inaccuracy, coupling, antenna ar
Strain and interactions at grain boundaries during solid-phase crystallization are known to play a significant role in the functional properties of polycrystalline materials. However, elucidating three-dimensional nanoscale grain morphology, kinetics, and strain under realistic conditions is challenging. Here, we image a single-grain growth during the amorphous-to-polycrystalline transition in tec
For linear time-invariant systems with uncertain parameters belonging to a finite set, we present a purely eterministic approach to multiple-model estimation and propose an algorithm based on the minimax criterion using constrained quadratic programming. The estimator tends to learn the dynamics of the system, and once the uncertain parameters have been sufficiently estimated, the estimator behave
Weakly-hard models have been used to analyse real-time systems subject to patterns of deadline hits and misses. However, the tools that are available in the literature have a set of shortcomings. The analysis they offer is limited to a single weaklyhard constraint and to patterns that specify the number of misses, rather than the number of hits. Furthermore, the scalability of the tools is limited
The multi-armed bandit (MAB) problem models a decision-maker that optimizes its actions based on current and acquired new knowledge to maximize its reward. This type of online decision is prominent in many procedures of Brain-Computer Interfaces (BCIs) and MAB has previously been used to investigate, e.g., what mental commands to use to optimize BCI performance. However, MAB optimization in the co
A corpus study and a combined behavioural and neurophysiological study tested how phonetic and phonological features of the Danish creaky voice feature ‘stød’ influence predictive processing. Being associated with certain word endings, stød and its modal voice counterpart non-stød can cue upcoming speech. Stød has two phases. The first shows phonetic differences in pitch while the second, characte
This article introduces a 28-nm CMOS digitally controlled oscillator (DCO) based on eight oscillator cores, where the number of active cores can be reconfigured to be either 2, 4, 6, or 8, trading power consumption for phase noise without incurring an additional phase noise penalty. The impact of the reconfiguration pMOS switches on the phase noise performance is determined through a simple yet ri
Homogeneous Charge Compression Ignition (HCCI) is a promising but challenging combustion engine concept. The potential for good fuel economy and low emissions is high but the transient performance required for automotive applications presents a few problems still to be solved. The focus of this work is identification of the process dynamics. An ARX type model is fitted to input-output data. A meth
Homogeneous Charge Compression Ignition (HCCI) combustion lacks direct ignition timing control, instead the auto ignition depends on the operating condition. Since auto ignition of a homogeneous mixture is very sensitive to operating condition a fast combustion timing control is necessary for reliable operation, the ignition timing control design requiring appropriate models and system output vari
This paper offers a two-zone, physical, NOx model with low computational cost, implemented in C on an embedded system. The model is able to compute NOx-emission formation with high time resolution during an engine cycle. To do this the model takes cylinder pressure and injected fuel amount as inputs and produces NO concentration as output. The model as such is not new, nevertheless the physical ba
In this paper, we apply an optimal Linear Quadratic (LQ) controller, which has an inherent structure that allows for a distributed implementation, to an irrigation network. The network consists of a water reservoir and connected water canals. The goal is to keep the levels close to the set-points when farmers take out water. The LQ controller is designed using a first-order approximation of the ca
Nondestructive testing of composite materials is important in aerospace applications, and mm-wave imaging has been increasingly used for this purpose. Imaging is traditionally performed using Fourier methods, with inverse methods being an alternative. This communication presents a mm-wave imaging method with an inverse approach intended for nondestructive testing of singly curved composite panels
Driven by the idea to use alarm data to explore machine learning across Industry 4.0 applications, the goal of this pilot study was to explore how to collect, store, manage and share data from the ESS Control System. Generally, we seek to make any control system data available for research and innovation but started with alarms as a feasible domain in which to explore machine learning. The goals w
Service meshes factor out code dealing with inter-micro-service communication, such as circuit breaking. Circuit breaking actuation is currently limited to an "on/off" switch, i.e., a tripped circuit breaker will return an application-level error indicating service unavailability to the calling micro-service. This paper proposes a soft circuit breaker actuator, which returns cached data instead of
This is the second component of a two-part paper dealing with a unification of characteristic mode decomposition. This second part addresses modal tracking, interpolation, the role of ohmic losses, and presents several numerical examples for surface-based method-of-moment formulations. A new tracking algorithm based on algebraic properties of the transition matrix is developed, achieving excellent
We study the stability of oscillation in two different multi-mode harmonic oscillators by means of Barkhausen’s criterion, involving a minimum of mathematical machinery in favor of a more intuitive, circuit-based approach. The results of the theoretical analysis match very closely those obtained through transient simulations, confirming occasionally surprising outcomes of the latter.
Modern society is increasingly dependent on IT-systems. Due to this dependence it is importantthat IT-networks are designed to be resilient, meaning that they will either maintain or quickly recover theirfunctionality when exposed to strain. Simulation-based methods that consider supply network topology as wellas system responsible for repairing supply network have previously been used and found t
Context: It is an enigma that agile projects can succeed ‘without requirements’ when weak requirements engineering is a known cause for project failures. While agile development projects often manage well without extensive requirements test cases are commonly viewed as requirements and detailed requirements are documented as test cases.Objective: We have investigated this agile practice of using t
