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pyParticleest : A Python framework for particle-based estimation methods

Particle methods such as the particle filter and particle smoothers have proven very useful for solving challenging nonlinear estimation problems in a wide variety of fields during the last decade. However, there are still very few existing tools available to support and assist researchers and engineers in applying the vast number of methods in this field to their own problems. This paper identifi

On Motion Control and Machine Learning for Robotic Assembly

Industrial robots typically require very structured and predictable working environments, and explicit programming, in order to perform well. Therefore, expensive and time-consuming engineering work is a major obstruction when mediating tasks to robots. This thesis presents methods that decrease the amount of engineering work required for robot programming, and increase the ability of robots to ha

Towards a New Generation of Relay Autotuners

The relay autotuner for PID control is based on the simple idea of investigating process dynamics by the oscillation obtained when the PID controller is replaced by a relay unction. In this paper an asymmetric relay function is used, which provides an equation for the static gain of the process. A method to find the normalized time delay is proposed and the benefits of this is discussed. Ways to f

Performance overhead comparison between hypervisor and container based virtualization

The current virtualization solution in the Cloud widely relies on hypervisor-based technologies. Along with the recent popularity of Docker, the container-based virtualization starts receiving more attention for being a promising alternative. Since both of the virtualization solutions are not resource-free, their performance overheads would lead to negative impacts on the quality of Cloud services

Control-Theoretical Software Adaptation: A Systematic Literature Review

Modern software applications are subject to uncertain operating conditions, such as dynamics in the availability of services and variations of system goals. Consequently, runtime changes cannot be ignored, but often cannot be predicted at design time. Control theory has been identified as a principled way of addressing runtime changes and it has been applied successfully to modify the structure an

Scalable Design of Heterogeneous Networks

A systematic approach to the analysis and design of a class of large dynamical systems is presented. The approach allows decentralized control laws to be designed independently using only local subsystem models. Design can be conducted using standard techniques, including loopshaping based on Nyquist and Popov plots, H methods, and μ-synthesis procedures. The approach is applied to a range of netw

Event-Driven Bandwidth Allocation with Formal Guarantees for Camera Networks

Modern computing systems are often formed by multiple components that interact with each other through the use of shared resources (e.g., CPU, network bandwidth, storage). In this paper, we consider a representative scenario of one such system in the context of an Internet of Things application. The system consists of a network of self-adaptive cameras that share a communication channel, transmitt

Knowledge for Synchronized Dual-Arm Robot Programming

We present our successful efforts to improve intuitive programming of synchronized dual-arm operations in industrialrobotic assembly tasks. To this end we extend an earlier proposed skill representation (based on our work with ontologies for industrial robots) and our respective programminginterface to integrate options for the specification, adaptationand refinement of synchronization points, syn

Distributed Semidefinite Programming with Application to Large-scale System Analysis

Distributed algorithms for solving coupled semidefinite programs (SDPs) commonly require many iterations to converge. They also put high computational demand on the computational agents. In this paper we show that in case the coupled problem has an inherent tree structure, it is possible to devise an efficient distributed algorithm for solving such problems. The proposed algorithm relies on predic

Feedback for increased robustness of forwarding graphs in the cloud

Cloud computing technology provides the means to share physical resources among multiple users and data center tenants by exposing them as virtual resources. There is a strong industrial drive to use similar technology and concepts to provide timing sensitive services. One such domain is a chain of connected virtual network functions. This allows the capacity of each function to be scaled up and d

On the Remarkable Performance of the Series-Resonance CMOS Oscillator

Common harmonic oscillator topologies, such as class-B and class-C, are typically unable to meet ultra stringent phase noise requirements, due to the exceedingly large capacitance (and, symmetrically, low inductance) that would be required in the parallel resonator. In this paper, we show that an oscillator making use of series resonators is ideally able to overcome this limitation, with the addit

Dynamic control of NFV forwarding graphs with end-to-end deadline constraints

There is a strong industrial drive to use cloud computing technologies and concepts for providing timing sensitive services in the networking domain since it would provide the means to share the physical resources among multiple users and thus increase the elasticity and reduce the costs. In this work, we develop a mathematical model for user-stateless virtual network functions forming a forwardin

Qualitative and quantitative responses to press perturbations in ecological networks

Predicting the sign of press perturbation responses in ecological networks is challenging, due to the poor knowledge of the strength of the direct interactions among the species, and to the entangled coexistence of direct and indirect effects. We show in this paper that, for a class of networks that includes mutualistic and monotone networks, the sign of press perturbation responses can be qualita

A bounded complementary sensitivity function ensures topology-independent stability of homogeneous dynamical networks

This paper investigates the topology-independent stability of homogeneous dynamical networks, composed of interconnected equal systems. Precisely, dynamical systems with identical nominal transfer function F(s) are associated with the nodes of a directed graph whose arcs account for their dynamic interactions, described by a common nominal transfer function G(s). It is shown that topology-independ

Robust computation of pulse pressure variations

Evidence of arterial pulse pressure variations caused by cardio-pulmonary interactions, and their connection to volume status via the Frank–Starling relationship, are well documented in the literature. Computation of pulse pressure variations from arterial pressure measurements is complicated by the fact that systolic and diastolic peaks are not evenly spaced in time. A robust, structurally uncomp

Reviews and syntheses : Systematic Earth observations for use in terrestrial carbon cycle data assimilation systems

The global carbon cycle is an important component of the Earth system and it interacts with the hydrology, energy and nutrient cycles as well as ecosystem dynamics. A better understanding of the global carbon cycle is required for improved projections of climate change including corresponding changes in water and food resources and for the verification of measures to reduce anthropogenic greenhous

AutoSAC: automatic scaling and admission control of forwarding graphs

There is a strong industrial drive to use cloud computing technologies and concepts for providing timing sensitive services in the networking domain since it would provide the means to share the physical resources among multiple users and thus increase the elasticity and reduce the costs. In this work, we develop a mathematical model for user-stateless virtual network functions forming a forwardin