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Observer-Based Strictly Positive Real (SPR) Variable Structure Output Feedback Control

This paper considers switching output feedback control of linear systems and variable structure systems. Theory for stability analysis and design for a class of observer-based feedback control systems is presented. A circle-criterion approach can be used to design an observer-based state feedback control which yields a closed-loop system with specified robustness characteristics. The approach is r

Performance Improvement of a Phase Space Detection Algorithm for Electrocardiogram Wave Morphology Classification

An algorithm based on embedding phase space signal was developed by the authors in previous works. The algorithm detects the characteristic points of the waves of a multilead electroacardiogram (ECG). In the present work, the parameters of this algorithm are optimized to improve its performance. The algorithm uses 2 configurable parameters to obtain the phase spacethe dimension of the phase space

HEp-2 Staining Pattern Classification

Classifying images of HEp-2 cells from indirect immunofluorescence has important clinical applications. We have developed an automatic method based on random forests that classifies an HEp-2 cell image into one of six classes. The method is applied to the data set of the ICPR 2012 contest. The previously obtained best accuracy is 79.3% for this data set, whereas we obtain an accuracy of 97.4%. The

Practical Robust Two-View Translation Estimation

Outliers pose a problem in all real structure from motion systems. Due to the use of automatic matching methods one has to expect that a (sometimes very large) portion of the detected correspondences can be incorrect. In this paper we propose a method that estimates the relative translation between two cameras and simultaneously maximizes the number of inlier correspondences. Traditionally, outlie

Online Spike Detection in Cloud Workloads

We investigate methods for detection of rapid workload increases (load spikes) for cloud workloads. Such rapid and unexpected workload spikes are a main cause for poor performance or even crashing applications as the allocated cloud resources become insufficient. To detect the spikes early is fundamental to perform corrective management actions, like allocating additional resources, before the spi

Generalized Roof Duality for Pseudo-Boolean Optimization

The number of applications in computer vision that model higher-order interactions has exploded over the last few years. The standard technique for solving such problems is to reduce the higher-order objective function to a quadratic pseudo-boolean function, and then use roof duality for obtaining a lower bound. Roof duality works by constructing the tightest possible lower-bounding submodular fun

Using a Gaussian Channel Twice

The problem of communicating one bit over a memoryless Gaussian channel with an energy constraint is discussed. It is assumed that the channel is allowed to be used only two times. An ideal feedback channel is also supposed available. The optimal feedback strategy and the bit-error probability are derived. It is shown that feedback gives a significant performance gain and that the optimal strategy

Increasing Time-Efficiency and Accuracy of Robotic Machining Processes Using Model-Based Adaptive Force Control

Machining processes in the industry of today are rarely performed using industrial robots. In the cases where robots are used, machining is often performed using position control with a conservative feed-rate, to avoid excessive process forces. There is a great benefit in controlling the process forces instead, so as to improve the time-efficiency by applying the maximum allowed force, and thus re

Scalable Positivity Preserving Model Reduction Using Linear Energy Functions

In this paper, we explore positivity preserving model reduction. The reduction is performed by truncating the states of the original system without balancing in the classical sense. This may result in conservatism, however, this way the physical meaning of the individual states is preserved. The reduced order models can be obtained using simple matrix operations or using distributed optimization m

Rao-Blackwellized Auxiliary Particle Filters for Mixed Linear/Nonlinear Gaussian models

The Auxiliary Particle Filter is a variant of the common particle filter which attempts to incorporate information from the next measurement to improve the proposal distribution in the update step. This paper studies how this can be done for Mixed Linear/Nonlinear Gaussian models, it builds on a previously suggested method and introduces two new variants which tries to improve the performance by u

LuGre-Model-Based Friction Compensation

A tracking problem for a mechanical system is considered. We start with a feedback controller that is designed without attention to disturbances, which are assumed to be adequately described by a dynamic LuGre friction model. We are interested in deriving a superimposed observer-based compensator to annihilate or reduce the influence of such a disturbance. We exploit a recently suggested approach

Shoreline response to a single shore-parallel submerged breakwater

Submerged breakwaters (SBWs) are becoming a popular option for coastal protection, mainly due to their low aesthetic impact on the natural environment. However, SBWs have rarely been employed for coastal protection in the past and therefore, their efficacy remains largely unknown. The main objective of the present study was to investigate the structural and environmental conditions that govern the

Hybrid Stiff/Compliant Workspace Control for Robotized Minimally Invasive Surgery

This paper presents a novel control architecture for hybrid stiff and compliant control for minimally invasive surgery which satisfies the constraints of zero lateral velocity at the entry point for serial manipulators. For minimally invasive surgery it is required that there is no sideways motion at the point where the robots enter the abdomen. This is necessary to avoid any damage to the patient

Optimal preconditioning and iteration complexity bounds for gradient-based optimization in model predictive control

In this paper, optimization problems arising in model predictive control (MPC) and in distributed MPC aresolved by applying a fast gradient method to the dual of the MPC optimization problem. Although the development of fast gradient methods has improved the convergence rate of gradient-based methods considerably, they are still sensitive to ill-conditioning of the problem data. Since similar opti

Individualized closed-loop control of propofol anesthesia: A preliminary study

This paper proposes an individualized approach to closed-loop control of depth of hypnosis during propofol anesthesia. The novelty of the paper lies in the individualization of the controller at the end of the induction phase of anesthesia, based on a patient model identified from the dose-response relationship during induction of anesthesia. The proposed approach is shown to be superior to admini

Bandwidth-Efficient Controller-Server Co-Design with Stability Guarantees

Many cyber-physical systems comprise several control applications implemented on a shared platform, for which stability is a fundamental requirement. This is as opposed to the classical hard real-time systems where often the criterion is meeting the deadline. The stability of control applications depends on not only the delay experienced, but also the jitter. Therefore, the notion of deadline is c

Comparison of Hybrid Control Techniques for Buck and Boost DC-DC Converters

Five recent techniques from hybrid and optimal control are evaluated on two power electronics benchmark problems. The benchmarks involve a number of practically interesting operating scenarios for fixed-frequency synchronous dc-dc converters. The specifications are defined such that good performance can only be obtained if the switched and nonlinear nature of the problem is accounted for during th

Adaptation and Learning for Manipulators and Machining

This thesis presents methods for improving the accuracy and efficiency of tasks performed using different kinds of industrial manipulators, with a focus on the application of machining. Industrial robots offer a flexible and cost-efficient alternative to machine tools for machining, but cannot achieve as high accuracy out of the box. This is mainly caused by non-ideal properties in the robot joint

Runtime Voltage/Frequency Scaling for Energy-Aware Streaming Applications

Power and energy consumption, today essential in all types of systems, can be reduced by scaling the voltage/frequency at runtime and/or powering down idle components. Efficient management requires not only pertinent decisions, but also early access to workload information, as well as domain specific solutions. This paper focuses on runtime energy management for streaming applications running on m