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This paper presents an adaptive video encoder that can be used to compare the behavior of different adaptation strategies using multiple actuators to steer the encoder towards a global goal, composed of multiple conflicting objectives. A video camera produces frames that the encoder manipulates with the objective of matching some space requirement to fit a given communication channel. A second obj
Self-adaptation provides a principled way to deal with change during operation. As more systems with strict goals require self-adaptation, the need for guarantees in self-adaptive systems is becoming a high-priority concern. Designing adaptive software using principles from control theory has been identified as one of the approaches to provide guarantees. However, current solutions can only handle
The pervasiveness and growing complexity of software systems are challenging software engineering to design systems that can adapt their behavior to withstand unpredictable, uncertain, and continuously changing execution environments. Control theoretical adaptation mechanisms have received growing interest from the software engineering community in the last few years for their mathematical groundi
In the near future, the number of connected mobile devices and data-rates are expected to dramatically increase. Demands exceed the capability of the currently deployed (4G) wireless communication systems. Development of 5G systems is aiming for higher data-rates, better coverage, backward compatibility, and conforming with “green communication” to lower energy consumption. Massive Multiple-Input
The field of robotics offers a wide array of estimation problems, ranging from kinematic and dynamic calibration to pose estimation and computer vision. This thesis presents a set of methods to solve estimation problems encountered in robotics, with an emphasis on industrial robotics. The researched topics are all practically motivated and have found immediate use in applications.Industrial roboti
Online 3D reconstruction has been an active research area for a long time. Since the release of the Microsoft Kinect Camera and publication of KinectFusion [11] attention has been drawn how to acquire dense models in real-time. In this paper we present a method to make online 3D reconstruction which increases robustness for scenes with little structure information and little texture information. I
The focus of this contribution is the estimation of multi-step-ahead linear multivariate predictors of the output making use of finite input-output data sequences. Different strategies will be presented, the common factor being the exploitations of geometric operations on appropriate subspaces spanned by the data. In order to test the capabilities of the proposed methods in predicting new data, a
The concept of dynamical movement primitives (DMPs) has become popular for modeling of motion, commonly applied to robots. This paper presents a framework that allows a robot operator to adjust DMPs in an intuitive way. Given a generated trajectory with a faulty last part, the operator can use lead-through programming to demonstrate a corrective trajectory. A modified DMP is formed, based on the f
Recently, several authors have shown local and global convergence rate results for Douglas–Rachford splitting under strong monotonicity, Lipschitz continuity, and cocoercivity assumptions. Most of these focus on the convex optimization setting. In the more general monotone inclusion setting, Lions and Mercier showed a linear convergence rate bound under the assumption that one of the two operators
We introduce the 'security index' of a discrete-time, linear time-invariant system under sensor attacks as a quantitative representation-free measure on the vulnerability of an observable system. Ideas from linear coding theory are employed in providing conditions for attack detection and correction in terms of a system's security index, along with methods for its computation based on different re
We consider the problem of finding an event-based sampling scheme that optimizes the trade-off between average sampling rate and control performance in a linear-quadratic-Gaussian (LQG) control problem setting with output feedback. Our analysis is based on a recently presented sampled-data controller structure, which remains LQG-optimal for any choice of sampling scheme. We show that optimization
The figure-ground segmentation of humans in images captured in natural environments is an outstanding open problem due to the presence of complex backgrounds, articulation, varying body proportions, partial views and viewpoint changes. In this work we propose classspecific segmentation models that leverage parametric max-flow image segmentation and a large dataset of human shapes. Our contribution
Automatic video captioning is challenging due to the complex interactions in dynamic real scenes. A comprehensive system would ultimately localize and track the objects, actions and interactions present in a video and generate a description that relies on temporal localization in order to ground the visual concepts. However, most existing automatic video captioning systems map from raw video data
Resilience has become a key aspect in the design of contemporary infrastructure networks. This comes as a result of ever-increasing loads, limited physical capacity, and fast-growing levels of interconnectedness and complexity due to the recent technological advancements. The problem has motivated a considerable amount of research within the last few years, particularly focused on the dynamical as
Two 60-GHz band voltage controlled oscillators (VCOs) designed in a 28-nm ultrathin body and buried oxide fully depleted silicon on insulator (UTBB FD-SOI) CMOS process are demonstrated and compared. Both VCOs have identical cross-coupled nMOS cores and dissipate 3.15 mW from a 0.9-V supply. The first design uses a standard FET current source and achieves a figure of merit (FOM) of −181 dBc/Hz, wh
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
This paper presents the mathematical conditions and the associated design methodology of an active fault diagnosis technique for continuous-time linear systems. Given a set of faults known a priori, the system is modeled by a finite family of linear time-invariant systems, accounting for one healthy and several faulty configurations. By assuming bounded disturbances and using a residual generator,
We consider flow-inducing networks, a class of models that are well-suited to describe important biochemical systems, including the MAPK pathway and the interactions at the trans-Golgi network. A flow-inducing network is given by the interconnection of subsystems (modules), each associated with a stochastic state matrix whose entries depend on the state variables of other modules. This results in
In modern day industry, robots are indispensable for achieving high production rates and competitiveness. In small and medium scale enterprises, where the production may shift rapidly, it is vital to be able to reprogram robots quickly. Kinesthetic teaching, also known as lead-through programming (LTP), provides a fast approach for teaching a trajectory. In this approach, a trajectory is demonstra
