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We present a novel class of minimax optimal control problems with positive dynamics, linear objective function and homogeneous constraints. The proposed problem class can be analyzed with dynamic programming and an explicit solution to the Bellman equation can be obtained, revealing that the optimal control policy (among all possible policies) is linear. This policy can in turn be computed through

The AI Act’s (AIA) requirements for high-risk AI systems affect many aspects of modern software systems. Knowing which AIA-related technical challenges are relevant to different companies is essential to focus compliance-oriented research on the aspects that matter. We therefore conducted an interview study in collaboration with a case company that specializes in network video solutions within the

In this paper, we provide the following simple equivalent condition for a nonsymmetric Algebraic Riccati Equation to admit a stabilizing cone-preserving solution: an associated coefficient matrix must be stable. The result holds under the assumption that said matrix be cross-positive on a proper cone, and it both extends and completes a corresponding sufficient condition for nonnegative matrices i

Research efforts to push the integration density of circuits with technologies that transcend Moore's law have gained significant attention in recent years. This study investigates the silicon area gains of Sequential 3D technology, utilizing the third dimension of integrated circuits by accommodating nMOS and pMOS transistors in two stacked tiers with high-density and low-pitch 3D vias. The effic

This study investigates the interaction of KEIF, the intrinsically disordered N-terminal region of the magnesium transporter MgtA, with lipid bilayers mimicking cell membranes. Combining experimental techniques such as neutron reflectometry (NR), quartz-crystal microbalance with dissipation monitoring (QCM-D), synchrotron radiation circular dichroism (SRCD), and oriented circular dichroism (OCD),

When deploying deep neural networks on robots or other physical systems, the learned model should reliably quantify predictive uncertainty. A reliable uncertainty allows downstream modules to reason about the safety of its actions. In this work, we address metrics for uncertainty quantification. Specifically, we focus on regression tasks, and investigate Area Under Sparsification Error (AUSE), Cal

Contextual shifts are crucial for episodic memory, setting event boundaries during event segmentation. While lab research provides insights, it often lacks the complexity of real-world experiences. We addressed this gap by examining perceptual and conceptual boundaries using virtual reality (VR). Participants acted as salespeople, interacting with customers in a VR environment. Spatial boundaries

The automotive domain is becoming increasingly complex through the integration of new technologies. As a result, cybersecurity is recognized as a pressing issue. This study focuses on the ISO/SAE 21434:2021 standard for road vehicles cybersecurity engineering, evaluating the effectiveness of the standard’s risk assessment approach. The standard suggests a set of assessment steps, and previous rese

Atmospheric new particle formation (NPF) is a naturally occurring phenomenon, during which high concentrations of sub-10 nm particles are created through gas to particle conversion. The NPF is observed in multiple environments around the world. Although it has observable influence onto annual total and ultrafine particle number concentrations (PNC and UFP, respectively), only limited epidemiologic

Language exposure and use (LEU) are widely viewed as key factors in multilingual development, and research highlights the importance of considering not just the frequency and quantity of LEU, but also contextual factors such as when and where a language is used, with whom and why. In this study, we illustrate the complexity of LEU in two contexts (study abroad and migration) by applying sequential

We study dynamical optimal transport of discrete time systems (dDOT) with Lagrangian cost. The problem is approached by combining optimal control and Kantorovich duality theory. Based on the derived solution, a first order splitting algorithm is proposed for numerical implementation. While solving partial differential equations is often required in the continuous time case, a salient feature of ou

We investigate optimal mass transport problem of affine-nonlinear dynamical systems with input and density constraints. Three algorithms are proposed to tackle this problem, including two Uzawa-type methods and a splitting algorithm based on the Douglas-Rachford algorithm. Some preliminary simulation results are presented to demonstrate the effectiveness of our approaches.

This paper investigates the use of decentralised control architectures with heterogeneous dynamics for improving performance in large-scale systems. Our focus is on two well-known decentralised approaches; the 'predecessor following' and 'bidirectional' architectures for vehicle platooning. The former, utilising homogeneous control dynamics, is known to face exponential growth in disturbance ampli

This paper concerns control of a class of systems where multiple dynamically stable agents share a nonlinear and bounded control-interconnection. The agents are subject to a disturbance which is too large to reject with the available control action, making it impossible to stabilize all agents in their desired states. In this nonlinear setting, we consider two different anti-windup equipped propor

This letter presents and analyzes an adaptive data-driven controller that learns the optimal processing rate in a multi-unit processing network in the presence of disturbances. We formulate an optimization problem of linear cost, linear dynamics for the processing network model and an affine constraint on the dispatcher policy. A data-driven linear equation is constructed, based on which the onlin

The scattering formulation of characteristic mode decomposition is utilized to extend modal analysis to lossless scatterers breaking time-reversal symmetry. This enables characteristic modes analysis on devices containing gyrotropic or moving media. The resulting nonreciprocity introduces features not observed in reciprocal scenarios, such as asymmetric phase progression in characteristic far fiel

We present a method for optimal control with respect to a linear cost function for positive linear systems with coupled input constraints. We show that the Bellman equation giving the optimal cost function and resulting sparse state feedback for these systems can be stated explicitly, with the solution given by a linear program. Our framework admits a range of network routing problems with underly

Delivery care in Sweden is very safe, the incidence of maternal death is 5/100 000 and perinatal death <2/100 000. The perinatal death rate among babies born at or after week 41+0 decreased from 0.17 to 0.09% (p<0.001) and obstetric anal sphincter injuries have decreased from 3.5% to 2.6%; however interventions such as induction of labour increase. A national project to improve safety for newborns

We present an explicit solution to the discrete-time Bellman equation for minimax optimal control of positive systems under unconstrained disturbances. The primary contribution of our result relies on deducing a bound for the disturbance penalty, which characterizes the existence of a finite solution to the problem class. Moreover, this constraint on the disturbance penalty reveals that, in scenar